Keywords: Linear Systems
Abstract: The paper presents a new criterion for exponential stability of linear neutral type time delay systems. It is based on the idea to supplement one of the classical conditions of the Krasovskii theorem, namely the positive definiteness of the functional, by a special set of functions satisfying a Razumikhin-type inequality and a similar inequality on the derivative. A functional, whose derivative is given as a negative definite quadratic form, is used. It is shown that this functional admits a quadratic lower bound on the mentioned set of functions.

Keywords: Linear Systems, Control System Design, Optimization
Abstract: Badly-scaled matrices or matrix pencils can reduce the reliability and accuracy of computed results for various numerical problems, including the computation of spectra and bases of invariant or deflating subspaces, which are used in many basic procedures for optimal and robust control, model reduction, spectral factorization, and other domains. Standard balancing techniques can often improve the results, but sometimes the solution of the scaled problem is much worse than that for the original problem. This paper presents an improved balancing technique for general or structured matrices and matrix pencils, and illustrates its good performance in solving eigenvalue problems and algebraic Riccati equations for large sets of examples from well-known benchmark collections.

Keywords: Linear Systems, Robust Control, System Identification and Modelling
Abstract: The paper focuses on the analysis of sensitivity and robustness for linear dynamical systems. A variation on the Kharitonov theorem is presented to provide a simple visual and quantitative measurement of system performances given parameter modifications. The method is applied in a tutorial approach to determine the component tolerance influences on two commonly-used notch filter topologies. The frequency responses of the filters are correlated to the pole-zero placement in the complex plane.

Keywords: Linear Systems, Real Time Applications
Abstract: This work is inspired from a challenging project conducted with undergraduate students within Automatic Control and Computer Engineering Faculty of Iasi. A bicycle type system was implemented and analyzed. In order to control this type of system, fast sampling rate is required. The finite precision nature of the existing digital hardware involves the choice of computational operations restricted to a finite number of bits. Even more so, the control algorithms must be implemented on these limited word length control units in the context of fast sampling. On the other hand, the mathematical design approach gives infinite-precision ideal values. The implementation stage is a critical step since the representation in finite precision must be performed as close to the ideal one. The discrete time delta (δ) domain representation is proposed due to its accuracy loss minimization at high sampling frequency comparing to discrete time shift (q) representation counterpart. The advantage of using δ operator is even stronger as the number of bits used for finite word length implementation is smaller. In this paper, a dynamic analysis of a real bicycle system is performed and discrete time δ domain representation is proposed, considering low bit number representation. Hence, δ domain representation allows implementation of different algorithms on cheaper processors without loss of performances.

Keywords: Linear Systems, Embedded Systems, Control System Design
Abstract: Adaptive regulation of sampling period has gained significant attention in research community in recent times and some encouraging techniques has been reported in this research direction. One such promising technique is commonly referred as multi-rate sampling. A linear control system that uses multi-rate sampling contains a collection of sampling periods and appropriately designed controllers for the corresponding sampling modes. Further, the switching between the sampling modes may depend upon some switching guards. In this paper, we address the problem of the multi-rate sampling associated with linear time invariant control systems, by formalizing the basis of selecting the sampling periods for the different sampling modes, such that overall system stability under arbitrary switching can be guaranteed. We also present a framework for controller synthesis in a multi-rate setting, such that our primary goal is achieved. Further, we present a case study using standard academic example and provide results in support of our proposed methodology.

Keywords: Hybrid Systems, Control System Design
Abstract: We have analysed existence and uniqueness of solutions and continuous dependence on the initial condition (well-posedness) of reset control systems with delay. We have elaborated sufficient conditions, using a concept of well-posedness of reset instants, for existence and uniqueness of solutions of reset control systems with input delay. Moreover, we have extended the results of continuous dependence for delay differential equations to discontinuous initial conditions. Finally, we have used the Hausdorff distance between nominal and perturbed trajectories to develop a concept of continuous dependence, and we have used the previous result to obtain a sufficient condition for continuous dependence on the initial condition for reset control systems with delay.

Keywords: Computational Intelligence, Internet of Things, Hybrid Systems
Abstract: With the growth of the Internet, recommendations have become a fact of life and there is a big competition between companies to get as much market share as possible. This is achievable not only through fast to market solutions but also by constantly providing high quality services.

Considering the speed of current technological advancements, it is impossible to conceive a world without some form of prediction. Traditionally, recommendations have been computed using the collaborative filtering method, but the growth of available information has pushed research into other directions such as content based, demographic based, utility-based, knowledge-based and hybrids.

This paper provides an introduction to collaborative filtering and content based methods, describing the underlying concepts, and discusses possible improvements using overclassification. Individual results are presented and then compared with the overclassification approach.

Keywords: Agent-based Systems, Computational Intelligence
Abstract: Software agents are a recognized way of introducing computer simulations to board games. Here, we consider one of the classic board games, called “Scotland Yard”, which belongs to the category of hider-seeker games, and involves six policemen that try to capture Mr. X. The aim of this paper is to discuss how software agents and AI-based strategies can be used to develop simulation in a hider-seeker game, named Warsaw’s Backyard. Specifically, it is shown how A* and IDDFS algorithms influence the seekers and hider performance. Furthermore, Move Filtering is introduced. It allows approximating the position of the hider better. Performance of the proposed approach is experimentally evaluated.

Keywords: Agent-based Systems, Discrete Event Systems, Manufacturing Systems
Abstract: This paper presents a coordination mechanism for solving the scheduling problem in holonic systems. The proposed approach is based on a combination between the method of distributed constraint satisfaction problem and the contract net protocol. After presenting the coordination scheme, a Coloured Petri net model is introduced. This allowed more simulation experiments to be carried out that revealed conclusions on the usefulness of the proposed method.

Keywords: Agent-based Systems, Distributed Systems, Software Engineering
Abstract: Management of a fleet of cars for hire (e.g. taxis) involves number of issues that should be solved to provide high quality service to the customers, while keeping drivers ``happy''. In this paper we show how a software agent system can be used to solve some of them and, potentially, improve both customer service and driver experience. We discuss the design and implementation of the system and illustrate (through a simulation) how application of the system supports fleet management and facilitates better driver workload balance / pay.

Keywords: Internet Security, Agent-based Systems, Communication Systems
Abstract: The advances in technology within the past decade have been huge and now we use it in almost every aspect of our lives. As a result, security has become a pressing issue, whether we are talking about the security of communications, of stored data, privacy and more. A compromised system will be an unreliable system, therefore detecting attacks as soon as possible is of crucial importance. With complex systems, such as cyber-physical systems, the efficient use of resources is also important, especially when using security methods like encryption, which require a fair amount of resources. The present paper aims to bring a solution to all of these issues. Cryptography will be used to ensure data and communications security, but also access control, while a platform called WSO2 Data Analytics Server will be used for attack detection and for increasing the efficiency of communications within the system.

Keywords: Education and Training, Software Engineering, Other Topics
Abstract: In previous papers the present authors have covered personalized study planning framework, and also have implemented study planning system (SPS) prototype, which allows to create a personalized study program, and then to plan the course learning, setting the courses in the required sequence, and make structure analysis thus detecting the most significant nodes in the graph structure. In this paper authors describe the application of eight common graph visualization algorithms – Tree, Circular, EfficientSugiyama Fruchterman-Reingold – FR, BoundedFR, ISOM, Kamada - Kawai – KK; LinLog – for representing study plans and course structures in the personalized study planning system.

Keywords: Hybrid Systems, Fault Diagnosis and Fault Tolerant Control
Abstract: In this paper, we proposed a new way that allows the identification and the compensation of sensor fault at the same time for hybrid switched systems. Indeed, to compensate this fault we chose the additive fault tolerant control (FTC). The synthesis of this FTC requires two important stages. The first step, provide the estimation of the fault by using Data-based Projection Method (MPD). The second step, is to generate the additive control and then to add it to the nominal control. The importance of the combination between the additive fault tolerant control and the Data-based Projection Method to estimate and to compensate the fault has been shown by an example. Index Terms- Hybrid switched system, sensor fault, Data-based Projection Method, additive fault tolerant control.

Keywords: Hybrid Systems, Predictive Control
Abstract: In this paper, a nonlinear hybrid system predictive control approach is developped. Hybrid process identification is based on PieceWise AutoRegressive eXogenous (PWARX) models. The identificaion problem deals with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. Model Predictive Control (MPC) strategy is based on Mixed Logical Dynamical (MLD) models and considers different operating features. The control methodology returns to solve a mixed-integer quadratic programming (MIQP) optimization problem. Simulation results show the efficiency of non-linear system predictive control application based on PWARX models.

Keywords: Hybrid Systems, System Identification and Modelling
Abstract: The work presented in this paper deals with the active mode identification problem for switched linear systems based on a measurement data set. This problem is an issue closely related to the classification problem of input-output measure data. Indeed, each data group associated with their most appropriate sub-model presents a mode (discrete state) of operation. Therefore, we propose a method for discrete state estimation based on a clustering algorithm combined with a decision mechanism. The clustering algorithm provides the class centers which will be exploited by the decision mechanism in order to identify the discrete state. Simulation results are presented to illustrate the performance of the proposed method.

Keywords: Linear Systems, Hybrid Systems
Abstract: The paper considers switched positive linear systems that operate with either arbitrary switching or average dwell time. For each operation manner, two types of stability criteria with complementary forms are presented, which provide distinct sufficient conditions for exponential stability of the system. The complementarity refers to analytical constructions relying on two types of copositive functions, namely linear and max-type. The developments cover, in parallel, both continuous- and discrete-time dynamics. A comparative study of the results reveals a dual mechanism valid for each operation framework, allowing the paired applicability of the criteria to any primal system, concomitantly with its dual. Two numerical examples are presented, associated with the two operation frameworks – with arbitrary switching and with average dwell time.

Keywords: Robust Control, Optimization, Control System Design
Abstract: A new method to extend the classical parameter space approach for switching systems by using a Lyapunov stability mapping method is presented. This extension is a enhancement to the classical approach which is only applicable to low order LTI systems. Moreover, this method has several advantages over the existing parameter space approaches. Currently, the calculation of the root boundaries relies on parameter gridding as well as frequency sweeping. The proposed method avoids this practice while reducing the computational complexity and increasing the practicality at the same time. The proposed procedure handles systems with arbitrary switching which is still a very problematic system class for actual approaches. To avoid the conservatism which comes along with the Lyapunov based method an numerical algorithm, is proposed. This algorithm optimises the estimation of the stability region. The suitability of the procedures is demonstrated on three benchmark examples.

Keywords: Linear Systems, Robust Control, Control System Design
Abstract: Many Parameter Space Approach (PSA) based methods have been proposed previously to determine the stabilizing controller parameter spaces for discrete-time systems. The PSA approach is based on sweeping over the whole range of singular frequencies which leads to an expensive numerical computation to find the boundaries of the stability region. These PSA based methods were used for obtaining the stability boundaries for parameter uncertain discrete-time systems as well. However, this results in extremely high computational complexity in addition to other drawbacks. In this study, an approach to determine the stabilizing controller parameter regions of linear discrete-time systems with uncertain parameters is proposed. This novel procedure makes use of the Strong Kharitonov theorem for getting over the high computational complexity resulted due to the uncertainty of the system. Moreover, the asserted approach utilizes a novel Lyapunov based mapping technique for avoiding the drawbacks accompanied with the previously presented PSA based methods in literature. Two different case studies are included in the paper to illustrate the advantages and effectiveness of the proposed method.

Keywords: Robotics, Modelling, Simulation and CAD Tools, Nonlinear Systems
Abstract: In this study a cam and a flat-faced follower mechanism are analyzed. The dynamic analysis presents follower displacement driven by a cam rotating at a uniform angular velocity. There is a clearance between the follower and the guide. The mechanism is analyzed using simulations taking into account the impact and the friction between the flat-faced follower and the guide. Four different follower guide clearances have been used in the simulations and the largest Lyapunov exponents have been calculated and analyzed. The effect of guide clearance is investigated for different angular velocities of the cam with the aid of phase plane contour.

Keywords: Robotics, Optimization
Abstract: In this paper we consider the problem of using mobile robots to collect a set of samples that are arbitrarily distributed in the environment. The robots are not necessarily identical and each one has a finite capacity, being able to transport only a given number of samples at each time. Furthermore, the number of transporting routes for robots can be also upper bounded. The problem is addressed in this paper by using a mathematical programming approach, namely developing a Mixed Integer Linear Program (MILP). The solution provides the optimal assignment of robots to samples, with respect to gathering all samples in a storage area in minimum time. The method is supported through simulation examples implemented in Matlab by using the CPLEX MILP solver.

Keywords: Robotics, Real Time Applications, Computer Vision
Abstract: This work presents answers to some implementation issues that can be encountered in robot-to-area allocations for exploration problems. The purpose of this research is to plan and control a team of mobile agents to visit a set of regions identified in the workspace. A reduced set of robot-to-region allocations with some particular cases that can appear in practical implementation are considered. The encountered issues for adapting the analytical solution are highlighted and specific centralized methods for coping with them are proposed. Real-time implementation results are offered for evaluation of the proposed method.

Keywords: Discrete Event Systems, Robotics, Hybrid Systems
Abstract: This paper describes the structure of a mobile robot suitable for laboratory experiments. The robot is developed with the ideas of minimizing the production costs and of executing motion commands received from an external computer that runs the (possible computational intensive) planning algorithms. The proposed system is a differential wheeled robot built based on an Arduino platform, it has a small physical size and it is capable of wireless communication. These characteristics make it useful for validating planning algorithms for mobile robots in computer-guided laboratory experiments, while lowering the expenses required by such a setup. Moreover, in order to compensate the communication delay between the central computer and the robot, an estimation algorithm is implemented on the robot for obtaining a smoother motion.

Keywords: Robotics, Computer Vision, Theory of Algorithms
Abstract: The iterative closest point (ICP) problem is very important in multiple fields such as robotics, machine vision, automotive or assistive technologies. The problem is to find the optimal transformation that can align two sets of 3D points. Even if in the recent year new variations of ICP were proposed, the algorithm may get trapped in local minima due to the nonconvexity of the problem. This issue may be overcome if the initial guess is chosen as close as possible to the true solution. In this paper a tensorial based method is proposed for choosing the initial guess of the iterative closest point problem. This new approach is strongly connected with the parameters that can be used to describe the displacement of rigid bodies. Using an isomorphism between the special Euclidean group SE3 and the orthogonal dual tensors group SO3, a detailed procedure is described on how to compute the initial guess for the iterative closest point problem. An evaluation of the proposed method is done using a Matlab framework that implements the ICP algorithm.

Keywords: Computer Vision, Software Engineering, Real Time Applications
Abstract: The research on assisting visually impaired people to navigate in unknown environments commonly employs image processing or computer vision techniques. One key element that needs to be identified in the surrounding environment of a blind user is the ground plane. Its accurate detection is highly important because the user is able to move freely in that area. An assistive device should primarily assist the user in avoiding the obstacles that lie on the ground surface. The images that will be further processed are usually acquired using depth acquisition devices worn by the user. Therefore, in contrast with automotive or robotics applications, which also heavily rely on ground plane extraction for obstacle detection, the camera orientation has more degrees of freedom. This leads to the requirement of designing more complex solutions for the ground plane detection in the case of assistive systems for the visually impaired. In this paper we introduce an algorithm to detect the ground plane taking into consideration the orientation of the camera, namely its pitch and roll. The proposed algorithm is based on an efficient processing of the v-disparity map associated to each frame. A two-step decision making approach to determine the most suited area that corresponds to the ground plane is described. Experimental results with synthetic datasets are provided to prove the efficiency and robustness of the proposed approach.

Keywords: Biologically Inspired Systems, Embedded Systems, Hardware Design
Abstract: Spiking neural networks are designed for modeling the natural neural tissue physiology in order to increase the biological plausibility of the artificial neural structures. The best option to obtain real time response of spiking neural networks is to implement the artificial neurons in analogue hardware. Despite the fast operation, a disadvantage of analogue spiking neural networks is the difficulty in prototyping of high complexity artificial neural areas because the connections between neurons, as well as, between neural areas should be hardwired. A solution that allows fast reconfiguration of spiking neural networks during prototyping represents wireless communication that also ensures communication at significant distance between artificial neural areas. This paper presents a method to implement wireless communication in RF range between areas of electronic neurons. Also, we tested using a microcontroller how this method affects the normal operation of the electronic neural network taking into account that wireless synapses implies conversion of voltage levels to digital values, data transmission delay and restoration of voltage levels. The results showed that the difference between the energies generated by the neural network with and without modeled wireless synapses is not significant and the delay induced by the digital data transmission is reduced by the neural network activity.

Keywords: Biologically Inspired Systems, Theory of Algorithms, Computational Intelligence
Abstract: In this paper, we present a new, computationally inexpensive method for preventing premature convergence in multimodal evolutionary algorithms by population injection. Our method avoids the premature convergence of the population around one or multiple local optima by maintaining an adequate amount of genetic diversity. The technique does not require any setup or maintenance effort during runtime as is the case for other proposed techniques addressing the same issue (e.g., island, cellular, or diffusion model EAs as population models or specific operators for increasing genetic diversity in mutation and recombination).

We present experimental results comparing a (μ, λ) EA using our method, which has been named population injection evolutionary algorithm (PI-EA), against cellular EA and classical (μ, λ) EA for some standard benchmark functions. In the results it can be observed that applying population injection improves the results produced by (μ, λ) EAs for all benchmarks under consideration, in one case even up to 59%.

Keywords: Biomedical Engineering
Abstract: This study explored the spatial pixels disorder in cerebral structures of brain magnetic resonance (MR) images. A method used for searching for the correlation between spatial pixels distribution and microstructure attributes of Alzheimer’s, Pick’s and cerebral calcinosis neurodegenerative diseases and radiography image acquisition way has been proposed. Entropy is used as local descriptor and dissimilarity indexes as global descriptors in order to assess the efficacy of the acquisition process and image types for various neurodegenerative diseases. The image types such as T1w, T2w and proton density (PDw), two conventional measures (i.e. structural similarity - SSIM and feature-similarity - FSIM), and entropy as a measure of information uncertainty carried by pixels are used. The dissimilarity analysis indicates highly disordered structures belong to the PDw images and the most disordered pixel distribution has been found in the case of cerebral calcinosis. The entropic characterization indicates PDw images having the higher disorder at microscopic level reflecting the pixels’ disorder and cerebral calciosis disease having the most heterogeneous microstructure.

Keywords: Biomedical Engineering, Control System Design, Nonlinear Systems
Abstract: This paper designs a discrete-time state-feedback output tracking control for the heart rate during treadmill exercise. Initially, the nonlinear model describing the relationship between the heart rate and the speed of a treadmill is discretized. Afterwards, a feedback linearization-based control law is proposed to achieve perfect output tracking. The control objective is to make the runner's heart rate follow a heart rate reference profile set by especialists as reference. The set-up of the problem in discrete time allows taking into consideration the effect of sampling during the controller design procedure instead of relegating it to the implementation stage. It will be shown that a linear state feedback controller is enough to make the nonlinear model's output track the reference profile regardless its posssibly complex time variation. Since the full state is not available for measurement a reduced order state observer is incorporated into the discrete-time control law. Then, the continous control command is generated by using a zero order hold (ZOH). The designed control system is tested on the original continuous-time nonlinear model by computer simulation to demonstrate the effectiveness of the proposed method to achieve the required objective.

Keywords: Biomedical Engineering, Web Services
Abstract: The advances in internet innovation have made possible techniques for the conveyance of healthcare. Networking infrastructure and common access can encourage sharing of patient data and clinical information; make the internet a perfect tool for remote patient observing applications. In this paper, we portray an experimental model designed for monitoring and checking the health condition of the patients based on sensors. The framework depends on e-health sensor shield associated with a cloud platform which gathers the data from the sensors. The sensors measure various parameters, such as a glucometer, airflow and patient position which are transmitted via microcontroller by a gateway to a cloud storage platform. The data collected in the cloud platform is accessible for further handling, for the investigation of some correlations among measured parameters and health state of the patients.

Keywords: Automotive Control Systems, Control System Design
Abstract: The paper proposes a new motor control strategy for safety relevant systems that are using two phase electric motors. Safety relevant applications requires the evaluation of the safe state of the system to be an operating mode without an unreasonable level of risk. Using this new control algorithm, the range where the unsafe state is defined as off and understood as deactivated can be diminished. A case study in normal and fault operating regimes for a two phase permanent magnet synchronous motor was conducted. By applying this new properly developed control strategy within a simulation model using Matlab/Simulink environment proves the ability to overcome inserted failures in different condition tests.

Keywords: Automotive Control Systems, Robust Control, Adaptive Control
Abstract: This paper proposes a control strategy for a high power Externally Excited Synchronous Machine (EESM) based on Simple Adaptive Control technique. A cascade control scheme is designed in the rotor reference frame. In the current control loop a SAC approach is described, while for the speed control loop a robust controller is proposed. The rotor and stator reference currents are determined based on a Maximum Torque per Ampere (MTPA) and Field Weakening (FW) strategies. Variations of parameters are simulated in order to evaluate the performance of the control method. Numerical simulations are performed in Matlab-Simulink.

Keywords: Automotive Control Systems, Nonlinear Systems, Control System Design
Abstract: This study gives a method employing the state dependent Riccati equation for the control of nonlinear quarter vehicle active suspension system. Hydraulic actuator is used as force actuator in the quarter vehicle active suspension system and its dynamic behavior is nonlinear. Then, the nonlinear state equations written for the dynamics of the quarter vehicle model are rearranged in a state dependent coefficient form. After that, a cost function is written in order to minimize the sprung mass acceleration, suspension deflection, sprung mass velocity, tire deflection, unsprung mass velocity, pressure decrease through the piston, and rate of pressure decrease through the piston. Finally, control input is obtained as the state dependent Riccati equation variables and the state variables. Quarter vehicle suspension system model of a Ford Fiesta Mk2 is considered in numerical studies to show the efficiency of the technique.

Keywords: Automotive Control Systems, System Identification and Modelling, Signal Processing
Abstract: In this paper, we study modelling of road roughness for full-car models from power spectrum and coherence measurements of parallel tracks. The modelling problem is cast as a spectral factorization problem and solved via subspace-based identification algorithms. Two different spectral factorization problems are formulated. In the first formulation, four road inputs are directly identified in innovation form while in the second formulation, an excitation model for the front axle is first identified and then, the excitation model for the rear axle is derived from the front axle model via P'ade approximation of a time-delay. The numerical study performed on real data shows that both factorization formulations have similar performances despite the direct approach yields less complex models.

Keywords: Automotive Control Systems
Abstract: Abstract — This paper propose to estimate the state of charge for a pack of lithium-ion cells used in the electric vehicles. For this purpose, experimental tests are made with Simscape-Matlab and serious effort is put on estimating the SoC of cells series lithium-ion battery with adaptive data driven. For avoiding the variations inside of a battery pack, it is necessary a filtering strategy for getting the performances of capacity, resistances conformity in battery pack. It is the intention to use Kalman filter algorithm, because of his advantages, only the last estimation value must be memorized, to obtain a clear SoC inside of battery pack. The multi-cells pack model will be simplified by the unit model. Different methods has been used to estimate the SoC of battery packs, a common way is the ampere-hour (Ah), based on current measurement and integration. Most of the time the performances are related to the measuring precision of the current. In open-loop the calculations can lead to errors because of uncertain disturbances. There are also other methods for estimating the SoC, like artificial neural networks, fuzzy logic, the extended Kalman filtering based estimators which is the most optimal method for minimize the variations. The main disadvantage of the methods mention above for battery packs is represented by the fact that inside of each individual cell there are constructive elements which cannot be ignored and mainly the purpose is to estimate the SoC for a battery cell. In this case for an optimal battery management calculation should be made for SoC and the lowest value will represent a reference point. In order to this strategy over-discharge will be avoid.

Keywords: Manufacturing Systems, Modelling, Simulation and CAD Tools, Nonlinear Systems
Abstract: Compressor facilities of an engineering enterprise were considered as a controlled object. Based on the analysis of the functional structure of the controlled object a group of tasks has been allocated to manage the compression facilities. To complete the tasks software was developed, which includes a set of mathematical models of the controlled object.

Keywords: Manufacturing Systems, Optimization
Abstract: Constrained models of manufacturing processes frequently provide an integral character of decision variables, which lead in general to weak duality and suboptimal solutions. Starting from the general transportation paradigm, this paper proposes two network constrained models of a minimum cost manufacturing process for a batch requiring different operations for different products, processed on several identical or different machines. Implications of strong duality are discussed within low-scale examples. Finally an IBM-ILOG implementation solution of a real job shop planning model is presented.

Keywords: Modelling, Simulation and CAD Tools
Abstract: The selection of the appropriate cloud services and Cloud providers (CPs) according to the cloud users' requirements is a complex problem, given the increased number of CPs. In the paper is proposed a new decision making framework for obtaining the criteria weights in the process of selection of a CP. The decision making framework for criteria weights is based on the hybrid DANP method - a combination of Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and Analytical Network Process (ANP) method. We have illustrated the applicability of the decision making framework using a case study.

Keywords: Modelling, Simulation and CAD Tools, Predictive Control, Optimization
Abstract: Energy consumption in buildings is the most significant component of the overall energy consumption in western countries, but also worldwide. There are some important initiatives which aim at developing new ways of decreasing the consumption of energy related to buildings. New types of buildings, like the passive ones are part of these initiatives. Local energy production and consumption is the most effective way of harnessing the maximum benefit from energy, but because of the limited possibility to generate clean energy locally, the management of local energy production should be optimized up to the maximum. Smart control systems and high energy performance buildings combined with predictive control strategies will not only reduce the overall cost related to energy, but will also help monetizing the local production in the future.

Keywords: Modelling, Simulation and CAD Tools, System Identification and Modelling, Hardware Design
Abstract: This paper focuses on reducing costs for CAD – CAM software convertor and on position control of the motors used on modern CNC. To achieve the proposed goal free software packages were used and integrated with low cost motion controllers. A G code to TrioBASIC language convertor was developed and validated using an experimental CNC machine for printed circuit boards milling.

Keywords: System Identification and Modelling, Modelling, Simulation and CAD Tools, Automotive Control Systems
Abstract: This paper proposes a simulation scenario in order to compare a proposed model of a motorcycle in cornering condition. The behaviours obtained by considering a linearized roll dynamic and a nonlinear roll dynamic have been investigated in order to evaluate their use in designing automatic stability controls of a motorcycle. The former model shows a linear dependency on the roll angle and the steer angle. The second model starts from the former and removes the roll angle linearization. The comparative analysis of the results shows how the linearized model is able to describe adequately the cornering dynamics for sufficiently large values of roll angle. These performances are suitable for designing a motorcycle active safety device controlling the lateral dynamics for preventing lateral falls.

Keywords: System Identification and Modelling, Optimization, Other Topics
Abstract: The ability to control the HR in treadmill exercise is of great importance in the design of exercise routines. In order to perform the HR control, as a model relating HR with speed is needed. There are several models but a key issue is the parameter estimation. This work considers the parameter estimation problem formulated as an optimization one and solved using Particle Swarm Optimization (PSO). This algorithm is used for the first time in this field.Achieved results and comparisons show the better improvement with respect to other estimation methods.

Keywords: System Identification and Modelling, Predictive Control, Optimization
Abstract: A combined nonlinear model predictive control with extended Kalman filter strategy has been proposed for optimal input design. As the designed controller depend on the identified parameters, the achievable performance highly depends on the quality of the identified information. The degradation in achieving the desired control performance is quantified by introducing an optimality criteria which minimize the error covariance matrix of the identified parameters. The major contribution is using the information of the system parameter at every sample time to improve the control performance at next time step. The the performance of the proposed algorithm is verified by numerical simulations for a example system.

Keywords: Fault Diagnosis and Fault Tolerant Control, Control System Design, Robust Control
Abstract: This paper presents a fault diagnosis (FD) method for on line monitoring of stator winding partial inter-turn fault and severe faults, in permanent magnet synchronous generator (PMSG) used in shaft generator system in marine applications. The faulty machine is represented in state space model based on the dq-frame transformation. The Extended Kalman Filter (EKF) parameters estimation technique is used to estimate the value of stator winding short-circuit parameters of the machine. The proposed technique has been simulated for different fault scenarios using Matlab®/Simulink®. Simulation results show that the proposed technique is robust and effective. Moreover it can be applied at different operating conditions to prevent development of complete failure.

Keywords: Fault Diagnosis and Fault Tolerant Control, Industrial Applications, Other Topics
Abstract: In this work the problem of robustness to temperature variations in pipeline leak detection and isolation is considered, extending preliminary attempts in this direction. The approach is restricted to pipelines short enough so that the spatial variations of the temperature can be neglected, and only time variations are addressed. The methodology is here based on a model taking into account the variations in all the parameters subject to temperature changes, like friction factor, water density, etc. A temperature measurement is then used to compensate for such variations in an Extended Kalman Filter used as a state observer, and real-time experimental tests are provided showing how an accurate leak identification is achieved when this compensation is done, while it fails otherwise.

Keywords: Fault Diagnosis and Fault Tolerant Control, Nonlinear Systems, Adaptive Control
Abstract: This paper presents a structure for faults detection and localization for a class of nonlinear systems described by equations specific fluid flow through pipes, using a method based on model and residues methods. We study the actuator’s faults detection and the leakages of pipes using residual vectors. This method was experimentally verified using the mathematical model for the lab installation. The simulation was developed under Matlab Simulink.

Keywords: Automotive Control Systems, Predictive Control, Agent-based Systems
Abstract: Vehicle platooning (enforcing the vehicles to follow each other and to maintain a safe distance between them) could be the solution to the stringent problems that appear on existing highways. Moreover, it has been already proved that by including communication between vehicles (yielding cooperative vehicles) the performances of the resulting platoons are much greater than those obtained without communication between vehicles. The specific particularities of the vehicle platoons, i.e., the chain structure of the involved sub-systems (vehicles), make them suitable as distributed model predictive control applications. As such, this paper intends to make a survey on the recent results regarding distributed model predictive control for the vehicle platooning problem, starting with inter-vehicle communications in a platoon, vehicle and platoon modeling and control, distributed model predictive control solutions and ending with some conclusions and future research directions.

Keywords: Automotive Control Systems, Control System Design, Robotics
Abstract: In this paper, a predictive control approach to increase the energy efficiency in a vehicle is presented. Even if the car’s CO2 emissions have been decreased in the last years and fulfill the EU specifications, the overall green-house gas missions is increasing. Thus, we present a proof-of-concept strategy which takes into account the road elevation in order to reduce the fuel consumption and implicit the CO2 emissions. Starting from the hypothesis that the road tomography is available an advanced control approach (MPC) is designed. In our simulation, the EPSAC (Extended Prediction Self-Adaptive Control) predictive controller was implemented using as prediction the road profile. The obtained results were compared against the classical PID controller. From the results it’s clear that the predictions can substantially enhance the control performance. An MPC-like implementation seems to be the most suitable way to cope with the system constraints while benefiting from future information about the road variability.

Keywords: Automotive Control Systems, Predictive Control, Agent-based Systems
Abstract: This paper proposes a distributed model predictive control algorithm applied in a vehicle platooning control problem. The control objective of each vehicle in the platoon is to follow a imposed position trajectory by means of distributed model predictive control, while maintaining a constant spacing between vehicles. A delay-free communication architecture is proposed and two cases are evaluated, namely: i) an unconstrained optimization problem and ii) an optimization problem in which the constraints are imposed based on the received information. The simulation results show that introducing constraints helps improving the results.

Keywords: Automotive Control Systems, Predictive Control, Control System Design
Abstract: The purpose of this paper is the development of a centralized model predictive control strategy for vehicle dynamics with focus on autonomous driving vehicles. The employed predictive control is multivariable, controlling the steering maneuvers and longitudinal speed. The vehicle speed is controlled based on the powertrain dynamics, while the steering maneuvers are controlled based on the vehicle lateral dynamics. The proposed algorithm makes use of linear models of vehicle and powertrain in the controller design, and for reliable results, simulation are carried out by considering a nonlinear vehicle model as the plant. For ensuring system stability, control Lyapunov functions are also included in the optimization algorithm. The obtained simulation results show that the proposed multivariable predictive control approach could provide very good performances in practical use.

Keywords: Automotive Control Systems, Adaptive Control, Control System Design
Abstract: The semnificative growth of the number of vehicles around the world can conduct to a condensation of the highway traffic. Therefore, the research to find optimal solutions for a higher vehicle flow on highways in a shorter time and with less accidents is ongoing. The organization of vehicles in platoons represents an appropriate method for increasing the roads’ capacities. This type of organization permits the decreasing of the distances between vehicles using an electronic coupling made by suitable devices. This functionality allows the simultaneous acceleration or deceleration of all vehicles in the platoon. Moreover, the intelligent vehicles are capable to automatically join or leave the platoon. Another advantage of this system is the decreasing of the fuel consumption and implicitly of the pollution. In this paper, a design approach for cooperative adaptive cruise control (CACC) of vehicle platooning is presented together with a performance evaluation through simulations. The proposed CACC system is based only on the communication with the directly preceding vehicle and consists of a cruise control system for the leader vehicle and a combination of feedback and feed-forward control systems for the followers. An ACC feedback controller is used to keep the desired inter-vehicle distance and a feed-forward one to reduce the effect of measurable disturbances.

Keywords: Biologically Inspired Systems, Software Engineering, Other Topics
Abstract: Artificial Neural Networks (ANNs) have been used as modeling tools for prediction of drug release patterns from bicomponent hydrogel systems based on poly(N-isopropylacrylamide) and sodium alginate. The process modeling was performed using an artificial neural network trained with an evolutionary algorithm, the last one having the role of developing the neural model in an optimal form. The ANN was trained with this algorithm using the available experimental data as the training set. The divergence of the root mean squared error (RMSE) between the output and target values of test set was used as stop criterion. The simulation results showed that drug release profiles from the chosen hydrogels can be modeled accurately using ANNs, the model predictions being closely correlated with the experimental data.

Keywords: Modelling, Simulation and CAD Tools, Computational Intelligence, Biologically Inspired Systems
Abstract: This paper is concerned with the numerical and analog modeling issues for a class of parabolic transport equations of the type reaction-advection-diffusion. The computational procedure relies on the Method of Lines concept and the canonical cell-based neural networks paradigm. It is derived from a recently proposed procedure for solving hyperbolic propagation equations with non-standard boundary conditions. The resulted highly structured and repetitive computational device allows both computational and analog modeling of the considered distributed parameter system. The procedure is applied to a nonlinear bioreactor distributed parameter model of the type reaction-advection-diffusion with Hadane kinetic function.

Keywords: Robotics
Abstract: AMiRo is a novel modular robot platform that can be easily extended and customized in hardware and software. Built up of electronic modules that fully exploit recent technology and open-source software for sensor processing, actuator control, and cognitive processing, the robot facilitates rich autonomous behaviors. Further contribution lies in the completely open-source software habitat: from low-level microcontroller implementations, over high-level applications running on an embedded processor, up to hardware accelerated algorithms using programmable logic. This paper describes in detail the motivation, system architecture, and software design of the AMiRo, which surpasses state-of-the-art competitors.

Keywords: Computational Intelligence, Optimization, Biologically Inspired Systems
Abstract: Conciliating between multiple objectives involves managing partially sorted solutions. In this regard, the main difficulties consist in finding proper ranking strategies able to preserve the genetic diversity, while guiding the search towards the areas preferred by practitioners (e.g. the middle of the best Pareto-fronts). This paper presents a new approach based on adaptive ranking. The adaptive techniques analyze the layout of fronts specific to the current population, in order to extract necessary information about the conflicting relationship between objectives and the behavior of genetic search. This feedback is used for configuring the preferred area and the ranking policies, as well. In this context, one contribution refers to the procedure proposed for investigating the distribution of fronts. It monitors the layout of fronts via distances based on activation scalarization function, which are likely non-conflicting with the closeness to the Pareto-optimal solutions. The benefits provided by this metric are also exploited by two other new procedures. One of them labels the preferred solutions by directly controlling the extent of the best fronts included in the preferred area. The other one corrects the spread of the best fronts via ranks’ adjustment. The performances of the approach are illustrated on several bi-objective optimizations involving weakly/strongly conflicting objectives, as well as different layouts of Pareto-fronts.

Keywords: Networked Control, Biologically Inspired Systems, Computational Intelligence
Abstract: In this study, the effects of missing or broken elements on the memory preservation in classical and quantum neural networks are analyzed. The networks were built by considering each node as a bit or qubit neuron-like processing unit. The qubit-neurons are analyzed from two perspectives, one that involves consideration of quantum coupling between them alongside with specific network connections and another that uses only non quantum network connections between them. The same classical architecture and learning are applied to both networks that contain classical and quantum nodes. The analysis of memory preservation in such networks consists in monitoring changes in memory states as results of interruption of different connections between nodes. From this perspective, the comparative classical and quantum network response to broken or missing elements are analyzed, compared and contextualized.

Keywords: Computer Vision, Signal Processing, Software Engineering
Abstract: This research evaluates the cell growth stages in a culture of Saccharomyces cerevisiae yeast using image processing algorithm. This algorithm is able to detect intracellular patterns, cell size and other parameters which determines the growth stage of cells (young, mature, in division, old, dead cell) using image clustering methods. The images studied in the present work were captured using a regular laboratory microscope and a microscope color camera of 1.3 megapixels resolution. Laboratory analysis aiming to validate the algorithm results were performed for every sample.

Keywords: Signal Processing, Real Time Applications
Abstract: Physicians as the most important tool in the diagnosis of acute and chronic heart conditions leverage the Electrocardiogram (ECG) data. The huge volume of data that needs to be gathered; processed as well as transmitted burdens the communication channel by obstructing the implementation of the ECG applications in telemedicine and remote monitoring scenarios. This has triggered the need for computationally efficient and advanced compression methods permitting the reconstruction of the destination’s original signal. This paper focuses on proposing a highly efficient compression method relying on both run length coding (RLC) and fast lifting wavelet transform (FLWT) for both 1 and 2 dimensional ECG data. The basic wavelets that had been used are Daubechies (Db4); Cohen-Daubechies-Feauveau (CDF 2.2) and Haar. The algorithm that has been proposed is deployed as well as tested on different ECH data signals that stem from an open MIT-BIH arrhythmia database. It has been seen that Db4 offers greater performance via lower error and greater compression ratio when opposed to the other wavelets stated here.

Keywords: Computer Vision
Abstract: In recent years, due to the computing capability, fingerprint identification is one of the most used and known biometrics. Individuals, in order to avoid automatic identification based on fingerprints, altered them by various means such as abrading, burning, cutting or through transplantation. Therefore, methods to detect altered fingerprints were developed in order to be distinguished from the natural ones. The most used methods for altered fingerprint detection are based on orientation field descriptors able to find singular regions generated by alterations. The aim of this paper is to comparatively test and assess the performance of three orientation field descriptors used for detecting the altered fingerprints. These descriptors have been tested against a non-altered fingerprint and two different fingerprint alterations by simulated central rotation: the first by cutting square regions and the second circular regions. The comparative analysis highlighted the descriptors ability to find altered fingerprints and the accuracy with which the detection is done.

Keywords: Computer Vision, Signal Processing, Robotics
Abstract: This paper develops a new method based on intelligent feature selection for aerial image segmentation. In order to select the best feature for segmentation we considered different regions of interest like floods and roads, taking into account information about color and texture. The features investigated derived from the inter-spectral co-occurrence matrices between the color channels RGB and HSV and from LBP approach. The proposed algorithm consists of two phases: the learning and the segmentation, respectively. In the learning phase we proposed a selection algorithm of features for each region of interest based on trace of confusion matrices. In the segmentation phase we proposed a classification algorithm based on a voting scheme for each selected feature. The experimental results were done on aerial images taken by a fixed-wing type UAV.

Keywords: Biomedical Engineering, Signal Processing
Abstract: The tagging of blood vessels from medical images is an essential step in the computer aided diagnosis of the vessels’ diseases. Different approaches, such as the Frangi vesselness filtering, the seeded region growing, and the adaptive thresholding are tested in order to obtain the vessels mask from the X-ray cardiac angiograms. The spurs are cleaned with morphological operations and the final results are tested with gold standard images.

Keywords: Industrial Applications, Real Time Applications, Fault Diagnosis and Fault Tolerant Control
Abstract: Fault or leak detection in the utilities distribution and energy fluids networks represents an objective with significant implications, where, the pollution and safety of life are priorities included. Reality and scientific literature contain dedicated solutions, proposed by theory and validated in time, and industry. Starting from a few of these, this paper proposes and analyzes some applicative solutions based on the models identification, (mathematical) modeling and supervision of normal and fault operation in the transportation and distribution networks for (liquid/fluid) utilities. Proposed supervisory structure is based on sensors/data acquisition and control architecture. The main purpose is to detect the fault situation as fast as possible and to indicate more accurately the affected area/point. The methods have been real time hardware and software implemented and validated with experimental laboratory facility.

Keywords: Linear Systems, System Identification and Modelling
Abstract: The structural identifiability analysis of linear lossy Port Controlled Hamiltonian(PCH) systems is proposed in this paper, by means of the observability and controllability concepts, which characterize a dynamic system. A general result is proved and proposed for the observability of linear lossy PCH systems. As example for the structural identifiability analysis, a DC motor is considered.

Keywords: Control System Design, Nonlinear Systems, Industrial Applications
Abstract: In the paper there is considered a benchmark application for control in co-generation composed of a steam turbine with one steam extraction connected to the steam consumer by a long steam pipe. It is discussed the linearized model starting from the conservation laws of the barotropic fluid and the Saint Venant model of the subcritical flow. The model validation relies on the association of a system of functional differential equations of neutral type. For the last system the inherent stability is discussed and a control Liapunov functional is constructed allowing feedback controller synthesis. There is presented also the analysis of the closed loop system thus obtained.

Keywords: Automotive Control Systems, Modelling, Simulation and CAD Tools, Hybrid Systems
Abstract: Renewable energy generators show an accelerated growth both production wise as well as in research fields. Focusing only on photovoltaic panels, the produced energy has the disadvantage of being strongly oscillatory in evolution. The classical solution is to create a network between photovoltaic farms spanning on large distances, in order to share the total energy before sending it to the clients. A solution that was recently proposed is to use hydrogen in order to store the energy surplus. Fuel Cells (FCs) represent energy generators whose energy vector is usually hydrogen. These have already started the transition from the laboratory context towards commercialization. Due to their high energy density as well as their theoretical infinite storage capacity through hydrogen, configurations based on electrolyzers and FCs are seen as high potential storage systems, both for vehicle and for stationary applications. Therefore, a study on such distributed control systems is of high importance. This paper analyzes existing solutions, with emphasis on a particular case where a supervisory system is developed and tested in a specialized simulation software.

Keywords: Control System Design, Optimization, Embedded Systems
Abstract: In this paper a methodology for extremal control of photovoltaic panels has been designed through the use of an embedded polynomial controller using robust approaches and algorithms. Also, a framework for testing solar trackers in a hardware in the loop (HIL) configuration has been established. Efficient gradient based optimization methods were put in place in order to determine the parameters of the employed photovoltaic panel, as well as for computing the Maximum Power Point (MPP). Further a numerical RST controller has been computed in order to allow the panel to follow the movement of the sun to obtain a maximum energetic efficiency. A robustness analysis and correction procedure has been done on the RST polynomial algorithm. The hardware in the loop configuration allows for the development of a test and development platform which can be used for bringing improvements to the current design and also test different control approaches. For this, a microcontroller based solution was chosen. The achieved performances of the closed loop photovoltaic panel (PP) system are validated in simulation using the MATLAB / SIMULINK environment and the WinPim & WinReg dedicated software. As it will be seen further in this paper, the extremal control of this design resides in a sequential set of computations used for obtaining the new Maximum Power Point at each change in the system.