Keywords: Motion control, Control algorithms implementation, Autonomous Ssystems
Abstract: The trajectory tracking problem for a fully-actuated real-scaled surface vessel is addressed in this paper by designing a backstepping controller with a multivariable integral action, considering the thruster allocation problem. The performance and robustness of this controller are evaluated in simulation, taking into account environmental disturbance forces and modeling mismatch, using a docking maneuver as a reference trajectory. Furthermore, a comparison between the backstepping controller and a nonlinear position PID-Control with flatness based-feedforward is also analyzed.

Keywords: Modeling and simulation, Mechatronics, Estimations and identification
Abstract: During the past decade, control engineers spent more effort making an interface between the practical applications and the theoretical models. System identification includes methods going from observed data to an accurate mathematical model. A precise mathematical model of the system assists engineers in designing high-performance model-based controllers. In this study, we obtained a detailed mathematical model of a conventional two-axis gimbal system considering the coupling effects of the gimbal axes. Then, we comprehensively compared the experimental data and the simulation results. We constructed the simulation model in MATLAB Simscape Multibody environment. We performed our analysis in both the time domain and frequency domain. The results show that an accurate model can be obtained considering the nonlinear effects of the system.

Keywords: Modeling and simulation, Modeling of complex systems, Robotics
Abstract: For many years simulations are an important tool for researchers in many fields of application. With ongoing improvements in computing power and the rising requirements in the industry, simulation software has to shift the focus more towards industrial use cases. Especially in robotics and machine learning applications, the physical behavior has to be reproduced as realistic as possible to avoid unwanted collisions during runtime. In general, applications such as mounting or bin picking with an automated robot shall be evaluated. Therefore this paper investigates three in-use and one newly published software environment with included physics engine for realistic simulations that are commercially available. For comparison, a benchmark with collisions between two gears to imitate a mounting process is implemented and key features are defined. Only two of the simulation software manage to pass the benchmark. Despite that, both of them show restrictions revealing a lack of reliable software for realistic robot interaction simulation.

Keywords: Mechatronics, Motion control, Robotics
Abstract: In the last few years, the problem of automatically tracking a moving object has become a topic of interest, being therefore the subject of several studies. This work aims at presenting two distinct control approaches to solve the tracking problem for a visual servoing system with Pan-Tilt structure. Linear and nonlinear (gain scheduling) Proportional-Derivative controllers are implemented in an actual microncontroller (Arduino Mega). The experimental results show a satisfactory level of efficiency of the systems established through the adopted methods, both for step and ramp shaped input errors.

Keywords: Robotics, Modeling and simulation
Abstract: The handling of flexible components, such as rubber sealings or cables, is an essential part of industrial manufacturing. Automating such processes through robotics is still a major challenge. Machine learning-based training of robots in combination with simulation has led to promising results in other areas of robotics. This approach can potentially be applied to assembly tasks as well. However, current simulation tools for robotics generally do not have capabilities for simulating flexible bodies. In this work, an approach for modeling such flexible bodies is proposed, which can be implemented with most common robotic simulation programs. Using the example of a rubber O-ring sealing, this approach was tested in such program and the results were compared with a professional multi-body physics engine. Realistic behavior of the O-ring was achieved with relatively low computation times.

Keywords: Modeling and simulation, Control applications, Transportation systems
Abstract: Traffic flow rising in urban areas makes road networks more congested. This leads to delays, slow-downs and length queuing of vehicles. These issues impact directly the environment, the cities atmosphere, and harms society as well. Therefore, in order to minimize these negative impacts, urban traffic requires adequate regulation methods. To this end, we propose in this paper an adaptive traffic light control technique at signalized intersections. It is a dynamic control approach where the number of vehicles and their arrival times at urban intersections are considered for decision-making regarding lights switching. The dynamic behavior of the studied physical system can be seen as a discrete events system. As powerful modeling and analysis tool we use Timed-Synchronized-Petri-Net (TSPN). The technique of ”Master-Slaves” is adopted in this approach. In fact, a ”master” reactive controller takes care of the evacuation of the vehicles from the intersection and the switching of the lights ”slaves”. These latter are represented by TSPN modules. The proposed control approach is based on the technique of Cyber-Physical systems where the digital model of the urban intersection (physical entity) is modeled and simulated using SUMO simulator. Thanks to the developed formal and simulation models, some interesting network’s properties are analysed and checked. The proposed solution allows for a smoother traffic flow in the studied intersection, reducing energy consumption and environmental impact.

Keywords: Control applications, Linear and nonlinear systems, Modeling and simulation
Abstract: This paper studies the tracking control design problem of a quadrotor based on a discrete-time controller, a new robust super twisting (RST) terminal sliding mode control (RST-TSMC) for a quadrotor with disturbances in discrete-time was developed. The discrete-time sliding mode manifolds have been developed for both attitude and position. From the theoretical analysis, it can be seen that the discrete-time robust super twisting terminal sliding mode control can provide better output tracking accuracy than the traditional method. Furthermore, the mathematical equations for system dynamics are discretized using forward Euler approximation and the control approach has been employed using the Lyapunov theory, which ensures the stability of the quadrotor system. Finally, extensive simulations are performed to demonstrate the effectiveness of the proposed approach and show the advantages of designed RST-TSMC in a discrete-time approach through comparative with DSMC at the end of the article, which clearly demonstrates the achievement of the suggested control method

Keywords: Robotics, Modeling and simulation, Control applications
Abstract: This paper investigates a new discrete-time fast terminal sliding mode control (DTFTSMC) for attitude/position subsystems of a quadrotor UAV. Firstly, the Newton-Euler formulation is used to complete mathematical model of this vehicle with external disturbances. The proposed method based Forward Euler technique for transforming the continuous-time system into discrete-time system is proposed for a disturbed quadrotor. The discrete control method ensures fast convergence and offers robustness against external disturbances. The stability analysis of the translational and rotational controller is guaranteed by the Lyapunov theory. The effectiveness of the proposed control approach is validated through numerical simulations under MATLAB software. Numerical simulation results show that the DTFTSMC is superior and faster to traditional discrete-time sliding mode control (DTSMC) in two various scenarios.

Keywords: Guidance and control theory, Autonomous Ssystems, Multivariable control
Abstract: In the face of parametric uncertainties and external disturbances, a recursive nonsingular fast terminal sliding mode controller (RNFTSMC) based on adaptive laws is presented for the attitude and altitude of a quadrotor. The first step is to implement recursive sliding mode control, which includes a two-layer sliding surface, an integral sliding manifold, and a fast nonsingular terminal sliding manifold. In turn, both sliding manifolds converge to zero in finite time without any singularity in the structure of the proposed controller. The initial value of the integral sliding manifold is set to eliminate the reaching phase. The upper bound of the unknown disturbances is addressed by estimating it using the adaptive adjustment technique. It is shown that the altitude/attitude control system converges in finite-time and that the tracking errors converge to zero. Finally, a numerical simulation is carried out for a quadrotor in the presence of disturbances. The simulation results illustrate the control performance that is predicted.

Keywords: Optimal control, Modeling and simulation, Renewable Energy
Abstract: 为了加速交通领域的脱碳进程，燃料电池电动汽车（FCEV）因其高效、零排放的特点，被广泛认为是解决全球能源危机和空气污染问题的理想方案。能源管理策略（EMS）可以最佳地协调不同电源的输出，从而提高系统效率并降低运营成本。然而，驾驶环境的不确定性将极大地影响EMS的性能。根据实际情况，速度规划生成FCEV的最佳速度曲线，可以减少复杂驾驶工况的不利影响。基于速度规划的EMS不仅可以降低全球成本，还可以提高车辆的性能。因此，为速度规划和能源管理策略开发先进的协同优化方法至关重要。本文

Keywords: Optimal control, Modeling and simulation, Renewable Energy
Abstract: The overall performance of fuel cell hybrid electric vehicles is largely dependent on the powertrain sizing configuration and energy management strategies (EMS). Due to their strong coupling relationship, it is thus instrumental to maximize vehicle’s economic potential by coordinating both aspects simultaneously. This paper presents a comprehensive review on the existing co-optimization methods of EMS and sizing. Firstly, the necessity of co-optimization is illustrated. Secondly, approaches for EMS, sizing, and especially co-optimization are reviewed and classified. Thirdly, the advantages and disadvantages of different co-optimization approaches are further summarized. In general, this work presents not only a comprehensive literature review of existing co-optimization approaches for sizing and EMS, but, more importantly, the relevant analyses could act as a baseline guideline for prospective designers in the field of control and optimization for fuel cell electric vehicles (FCEV) powertrain.

Keywords: Modeling and simulation, Estimations and identification, Optimal control
Abstract: Subjects with type 2 diabetes (T2D) require multiple daily injections (MDI) of insulin analogues to cover basal and prandial insulin needs for optimal blood glucose (BG) control. Intentionally or non-intentionally failing in treatment compliance has proved to degrade BG control in type 1 diabetes, while the effect of poor adherence to insulin therapy in T2D is understudied. Here, we aim at in silico quantifying the detrimental effects on BG control of delaying or skipping insulin bolus in T2D subjects. We employed the recently developed Padova T2D Simulator (T2DS), an accurate nonlinear computer simulator of early-stage T2D and, thanks to a newly developed cloning method, we extended it to advanced-stage insulin-dependent T2D subjects. One hundred in silico advanced-stage T2D were generated and models of basal-bolus insulins were incorporated into the T2DS to enable MDI therapy. MDI therapy parameters, i.e., basal and bolus insulin doses and injection times, were optimized for each subject by applying titration algorithms that iteratively update basal/bolus insulin amount based on BG deviation from prefixed target ranges. Finally, we assessed the impact of sub-optimal adherence to insulin therapy by running two 6-month in silico trials, with subjects receiving 3 meal/day under MDI. In the first trial, optimal basal and prandial insulin bolus at each meal were administered to each subject; in the other case, subjects received optimal basal insulin and randomly delayed or skipped the prandial insulin in 3 lunches during workingdays and 1 dinner during weekends. Results showed that, even in T2D, sub-optimal adherence to MDI therapy worsened postprandial BG control, leading to a significant increase of hyperglycemia, while apparently not increasing the risk of hypoglycemia.

Keywords: Signal processing, Fuzzy and neural systems
Abstract: Characterization of glycemic patterns in individuals with type 1 diabetes is addressed in this work. Unlike other methodologies, no insulin or meal data will be considered available. This makes the method presented suitable for all CGM users, independently of the insulin delivery device used. As well, no manual input is required from the patient potentially increasing usability and adherence. Data of 44 type 1 diabetic patients, from 26-week study were used in this work. An unsupervised clustering algorithm based on Fuzzy C-Means was applied to classify event-to-event segments of CGM data. Events defining data partitioning were automatically generated based on: 1) an automatic meal detection algorithm (for day periods) and 2) time of day (for night periods). After pre-filtering the dataset, 985 meal segments were detected and 180 periods were labelled as night per patient on average. The optimal number of clusters was determined by optimising clusters’ compactness and separation metrics, as given by the Fukuyama-Sugeno index. An average of 8 clusters for postprandial segments and 5 for nights was obtained, although, depending on patients’ habits and the amount of training data, these numbers may vary between patients. For the sake of comparison, the method was also applied to CGM data partitioned based on the mealtime manually reported by the patient. The use of a meal detection algorithm instead proved superior performance in terms of reduced within-cluster variability and interpretation of the resulting prototypes, besides freeing from patient intervention. Clusters described CGM data segments with differentiated glycemic control metrics, such as TIR, with average values across all patients of 45.2 ± 15% for detected meals and 49.9 ± 13.6% for announced meals data.

Keywords: Optimal control, Control applications, Control algorithms implementation
Abstract: In the context of closed-loop glycemic control, MPC has shown the skillfulness to improve glucose regulation in patients with type 1 diabetes mellitus (T1DM). To reduce its complexity, many of the proposed control strategies have been designed based on linear time-invariant (LTI) models, without accounting for intraday parametric fluctuations. In this work, a pulsatile Zone Model Predictive Control (pZMPC) is examined under a realistic patterns of intraday insulin sensitivity (SI ), according to the recent updates of the FDA-approved UVA/Padova simulator. Nominal updates of the postprandial insulin sensitivity are explicitly taken into account in the control-oriented model to improve the glucose predictions. The resulting controller is tested ’in-silico’ with the FDA-approved UVA/Padova simulator, while its behavior is analyzed by comparing the usual statistical metrics with the corresponding time-invariant configuration. As expected, results show significant improvements, which justifies the (reasonable) increment in the controller complexity

Keywords: Estimations and identification, Control applications, Optimal control
Abstract: It is well-known that tailored solutions are necessary to achieve tight glycemic control in diabetes care. In this work, we analyze the performance impact of model personalization on our clinically validated, fully Automated Insulin Delivery (AID) system, the so-called RocketAP. In this framework, personalization is focused on the glucose-insulin model used by its Kalman filter and Model Predictive Control (MPC) algorithm. To this end, identifiability analysis is conducted to obtain a suitable set of model parameters that are then estimated on a daily basis. Performance of RocketAP using a population-based or a personalized model is evaluated considering the 100 adult cohort of the Food and Drug Administration (FDA)-accepted UVA/Padova Type 1 Diabetes (T1D) Simulator. Comparing with the population-based model, results with the proposed personalization approach led to an increase in the percentage of time spent between 70-140 mg/dL (40.9% to 50.5%: +9.6%) and 70-180 mg/dL (70.5% to 75.0%: +4.5%), with an associated slight increase in the percentage of time spent below 70 mg/dL (0.6% to 1.6%: +1.0%). We conclude that model personalization has potential to improve glucose control overall in our fully AID system, RocketAP. However, further studies are needed to confirm the feasibility of this approach.

Keywords: Control algorithms implementation, Control applications, Modeling and simulation
Abstract: This work presents a set of proposed innovations to modify the original control algorithm composed by a set of rules to choose between two alternatives: Adaptive Predictive part and a Robust Filter (APCwRF). The main objective is to provide improvements to the Artificial Pancreas (AP) technology for patients with Type 1 Diabetes Mellitus (T1DM). The new version, called enhanced (E) APCwRF, has two alternative models the Finite Impulse Response (FIR) and the nonlinear Wiener-type block-oriented. In both cases the model parameters are updated by performing recursive identification using a Kalman Filter (KF). Hence, the control algorithm checks the quality of the prediction of the two options (FIR and Wiener) and decides which of them will be adopted. The robust filter part is able to choose between the two models to be implemented. To test the EAPCwRF we use a previously developed global data-driven model (GM) for defining the final tuning (commissioning). The GM uses the KF to improve the predictions for the next hour only by estimating two weight parameters. This technique allows achieving a good representation of the true glycemia dynamic behavior. The closed loop glycemic responses of the original and EAPCwRF together with real data of the patient without control are compared. The Control Variability Grid Analysis (CVGA) is usefull to warn about which techniques drive to maximum or minimum values outside the recommended ranges. Meanwhile, the percentage of time with dangerous excursions of the glycemic concentrations inside the risky zones are considered too as a tool to ponderate the control performances. Finally, we present the conclusions and discuss some future works.