Keywords: Nonlinear control
Abstract: Many problems in robust and nonlinear control can be formulated using polynomial positivity conditions: the simplest example is the search of polynomial Lyapunov functions for stability analysis of equilibria of dynamical systems with polynomial vector fields. The discovery that semidefinite programming can be used to test polynomial non-negativity, using sum of squares, opens up new directions in nonlinear systems analysis and design. In this talk I will first present how ideas from dynamical systems, positive polynomials and convex optimization can be used to analyse the stability, robust stability, performance and robust performance of systems described by nonlinear ODEs.

Although entirely algorithmic, this approach does not scale well to large system instances, but Chordal Sparsity methods offer a way to address this challenge. I will motivate and use this decomposition method on the problem of understanding the properties of Neural Networks and Neural Feedback Loops. Indeed, it is becoming clear that providing robust guarantees on systems that use neural networks is very important, especially in safety-critical applications given that a trained neural network’s sensitivity to adversarial attacks is one of its greatest shortcomings. To provide robust guarantees, one popular method is to describe and bound the activation functions in the neural network using equality and inequality constraints. However, there are numerous ways to form these bounds, providing a trade-off between conservativeness and complexity. I will first show that Sum of Squares methods can tightened bounds significantly, whilst the computational time remains reasonable, using Chrodal Sparsity methods and then consider the problem of analysing neural feedback loops using structured Lyapunov functions and sum of squares, demonstrating that this method can improve estimates on the region of attraction of an equilibrium.

Keywords: Classical and optimal control methods, System identification and modelling, Transportation and vehicle systems
Abstract: Adoption of energy-efficient automobiles has grown in importance as society grapples with the issues posed by climate change, as well as a desire to minimize reliance on fossil fuels. Vehicles of the future are predicted to be equipped with increased automation and electrified powertrains as technology progresses, making them faster, safer, and more energy efficient. A potential approach to address energy consumption issues in automated vehicles is to adopt an eco-driving approach, which involves adopting driving behaviours that result in reduced emissions and energy consumption. This research work addresses the development of an energy efficient control of electric vehicle, while incorporating driver preferences. An optimal control model is developed and implemented in OpenOCL that can mimic typical car-following behaviour and (for optimisation in future work) can accurately calculate energy losses while driving, as validated against a detailed Simulink model of an electric vehicle.

Keywords: Emerging applications, Transportation and vehicle systems, Future cities
Abstract: Air pollution is a global health challenge and one of the leading causes of mortality with people from low- and middle-income countries being disproportionately affected. Traffic is one of the key contributors to urban air pollution and the ability to accurately model it is of primary importance to understanding its health implications. This paper presents the comparative studies of three AI-based predictive models such as Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM) network and a Gated Recurrent Unit (GRU) network to correctly identify the levels of air pollutants using traffic and environmental data. Eighteen months of weather, air quality and traffic data were used and the models were then tested on data without access to previous particulate matter (PM) 2.5 µm levels. The GRU provided the best balance of low training overheads with good performance. An autocorrelation analysis revealed that PM2.5 levels are highly autocorrelated, hence access to previous levels of PM2.5 is needed. The models created demonstrated that there is indeed a relationship between the variables.

Keywords: Health monitoring, Transportation and vehicle systems, Systems engineering
Abstract: In this research work, two monitoring sensor systems have been defined and deployed inclusive RFID subsystem, data communication subsystem and database subsystem. The goal of the complete system is to synchronise the conditioning data of the railway track asset (crossing nose), recorded by two monitoring systems, one on the track and the second on the vehicle. The system also matches all recorded data with the crossing-nose position accurately by scanning the asset ID using a radio frequency identification technology (RFID) installed on the train and the track. Thus, Network Rail databases, which include the maintenance history of the Switch and Crossing system, will be harmonized based on the recorded conditioning monitoring data and the location of the track asset.

Keywords: Multi-objective methods and optimisation, Transportation and vehicle systems, Future cities
Abstract: The research on optimising the speed profile of public transportation holds significant potential for enhancing operational efficiency. Nevertheless, there is currently limited literature that accounts for the impact of traffic lights and other traffic participants on the speed profile. This paper proposes a method for online generation of the optimal speed profile based on dynamic programming and state machine. Based on dynamic programming, the speed profile that adhere to traffic lights is generated. Considering the interactions of ego vehicle with other participants during operation, the speed profile is optimised online based on state machine. The effectiveness of the proposed method is verified by simulation based on Simulink and TruckMaker.

Keywords: System identification and modelling, Transportation and vehicle systems
Abstract: For a complex system like a multi-articulated all-axle steering vehicle, an accurate and physically meaningful dynamic model is crucial for analyzing vehicle characteristics and designing controllers. This paper proposes a dynamic modelling method for multi-articulated vehicles based on the principles of Lagrangian dynamics. This method effectively balances the complexity and precision of the model. Firstly, a set of clear symbol representations is constructed based on the actual physical meanings, standardising the modelling process. Secondly, nonlinear dynamic equations are constructed using Lagrange’s equations, the principle of virtual work, and corresponding actuator models. Finally, through a series of transformations and simplifications, the vehicle dynamic model is obtained in matrix form. The model is validated by comparison with the model built under TruckMaker and collaborative simulation with controller.

Keywords: Robotics and autonomous systems, System identification and modelling, Autonomous systems
Abstract: Two methods for replicating the motion of full-scale surface vessels by small-scale vessels are presented. One method investigates the direct replication or mimicking of ship motion. The other investigates dynamically-similar mimicking of ship motion. Both methods use feedback laws to achieve the desired mimicking and do not require changes to the mass or moment of inertia of the smaller vessel. Numerical simulations are presented to demonstrate the efficacy of the proposed methods. The simulated vessel models utilize experimentally-identified parameters.

Keywords: Classical and optimal control methods, Nonlinear control, Stochastic systems
Abstract: Abstract— We consider the problem of optimal investment in a market with borrowing, unbounded random coefficients, and the power utility from terminal wealth with a random time horizon. The resulting optimization problem, due to the higher interest rate for borrowing than for lending, is an optimal stochastic control problem with a nonlinear system dynamics and unbounded random coefficients. A piece-wise completion of squares method and a linear backward stochastic differential equation are used to find an explicit closed-form solution as a linear state-feedback control.

Keywords: Fault detection and diagnosis, Aerospace and space systems, Health monitoring
Abstract: Generally, the area under the receiver operating characteristic curve (AUC) is considered to be a reliable performance measure in developing models where a class imbalance exists in the dataset. For such models, performance is adjudged on how much the AUC departs from a chance threshold of 0.5. However, the reliability of such threshold in class imbalanced problems is a growing concern. This paper investigates the severity of obtaining a high performance purely on chance by manipulating minority sample size, feature dimension, validation approach and classifier type.

Keywords: Linear control design, Classical and optimal control methods, Medical and biological systems
Abstract: A control theory approach to the management of blood clotting speed using the anticoagulant warfarin is investigated. Proportional Integral (PI) and Proportional-Integral-Plus (PIP) controllers are developed for models identified from patient data. These are used to estimate treatment decisions subject to stochastic disturbances, model uncertainty and missed observations, the latter representing missed clinic appointments. The focus is on the relative performance of various integral-of-error (IOE) forms, which are used to track the target International Normalised Ratio (INR) at steady state. These are adapted in novel ways to handle the missed observations. Preliminary Monte Carlo simulations suggest that forward difference, mean and trapezoidal IOE forms with modified pole assignment, could lead to more desirable outcomes than the standard case, but the differences are relatively small and more research is required into scenarios leading to set point deviations.

Keywords: Multi-agent methods and distributed control, Estimation and filtering, Human-machine systems
Abstract: A search and rescue localization algorithm is proposed using an unscented Kalman filter (UKF). The UKF provides superior performance to other filtering options such as the extended Kalman filter or the particle filter and is computationally less expensive than neural network localization methods. Each search agent obtains asynchronous measurements of its range and/or bearing relative to the victim. It is assumed that the victim’s pose (position and orientation) and speed estimates and the associated covariance matrices are available to all agents simultaneously. Each agent maintains its own UKF to update these estimates and its pose estimate when a new measurement is received. Simulation results demonstrate that the agents can track the victim’s location and orientation with minimal steady-state error despite significant measurement noise and large initiate estimation error.

Keywords: Process control systems, Linear control design, Classical and optimal control methods
Abstract: Selective Laser Melting (SLM), an additive manufacturing process, has attracted significant attention from academia and industry over the past two decades. SLM can efficiently produce complex industrial tools and parts with fewer steps, saving resources compared to subtractive manufacturing. However, the current industry-scale platforms for manufacturing metal parts via SLM do not sufficiently exploit online feedback control strategies. There is still significant potential for advanced process control which can enhance the overall performance of the system, as well as enable sophisticated manufacture, for example, via active control of microstructure to enhance part performance in geometrically complex parts.This paper presents the investigation of using a control system to enhance the system performance and reduce the effect of heat accumulation during the process of building a multi-layer object. The controller changes the laser input in the track and considers the temperature residuals for the completed layers. The simulation results showed a significant reduction in the error and better heat regulation.

Keywords: Transportation and vehicle systems, Multi-agent methods and distributed control, Distributed and decentralised control
Abstract: The control of platoons consisting of vehicles with varying characteristics is an area of significant research interest. Among existing platoon architectures, numerous strategies have been explored to leverage inter-vehicle communication for the creation of Cooperative Adaptive Cruise Control (CACC) systems. For instance, applications of the internal model principle to reach synchronization of heterogeneous linear multi-agent systems, that are coupled by diffusive links, has proven to yield high performance results. Yet, for realworld application, one major issue is taking into account input and state constraints while assuring safety requirements. In this paper, a feedback-distributed controller that guarantees synchronization of a heterogeneous vehicle platoon described by linear dynamics is presented. To maintain desired inter-vehicle spacing, a predecessor-follower scheme is utilized. To consider the physical limitations of the vehicles and prevent collisions, safety measures are implemented by applying control barrier functions. Conditions for vehicle stability are provided using a Lyapunov approach. Moreover, string stability properties of the platoon are analyzed. Via simulation, we demonstrate that the proposed control design enables the adoption of a velocitydependent gap-spacing policy for inter-vehicle distance, for any nonnegative headway. In conclusion, the controller’s efficiency is verified through a simulation study.

Keywords: Hybrid systems, Autonomous systems
Abstract: Real-time automata are a widely-used class of real-time systems. In this paper, we formulate a notion of concurrent composition of a labeled real-time automaton (LRTA) in which every pair of an observable faulty path and an observable nonfaulty path that can produce the same timed labeled sequence are synchronized and unobservable transitions interleave. We prove that a concurrent composition can be computed in time nondeterministically polynomial in the size of the LRTA. We also formulate a notion of diagnosability of an LRTA using infinite runs and derive a necessary and sufficient condition for the negation of the diagnosability using concurrent composition. Finally, we prove that the diagnosability verification problem is coNP-complete. It is well known that the diagnosability verification problem for general labeled timed automata is PSPACE-complete. We find more efficient algorithms for verifying diagnosability for the subclass LRTAs.

Keywords: Nonlinear control, Aerospace and space systems
Abstract: A finite-horizon optimal control problem for a non-linear unicycle with constant linear velocity is considered. The cost functional consists of the squared norm of a final position and the integral penalty term for the control effort, i.e., both the miss distance and the control are soft-constrained. A finite horizon formulation arises, for instance, in coordinated guidance attack against a stationary target, in which all interceptors have to arrive at the target at the same time. The soft constraint on terminal position allows for trade-off between the miss distance and control effort. Semi-analytical solution is derived by representing the squared norm as a maximum of a quadratic form and by changing the order of maximization and minimization. The inner minimization problem becomes a problem of calculus of variations, which Euler-Lagrange equation writes as a non-linear pendulum equation. Based on the solution of this equation, a numerical scheme for constructing the suboptimal control is developed. As a by-product of the approach, the posterior control bounds are obtained.

Keywords: Nonlinear control, Classical and optimal control methods
Abstract: An approach to design robust tracking controllers for non-linear systems is proposed. The method involves solving a non-linear open-loop optimal control problem that establishes the nominal tracking behaviour, followed by the design of a feedback controller that robustly stabilises the system around the optimal state trajectory. The effectiveness of the proposed approach is shown on a non-linear quadruple-tank system model subject to parametric uncertainties.

Keywords: Predictive control, Nonlinear control, Cyber-physical systems
Abstract: In this paper, we study the stability of a discrete-time nonlinear networked system controlled by model predictive control without explicit terminal constraints. The system is subject to input constraints and random packet losses on the actuation communication channel between the controller and the plant. We consider that a buffer, to store transmitted control sequences and provide some robustness to the packet losses, may or may not be present. We analyse the stability of the closed-loop system without resorting to the typical assumption that the terminal cost is a global control Lyapunov function (CLF), employing the much more realistic assumption that the latter is merely a local CLF. The developed conditions characterise an upper bound on the number of consecutive packet losses in order that stability is maintained.

Keywords: Multi-agent methods and distributed control, Robotics and autonomous systems, Distributed and decentralised control
Abstract: This paper introduces a bipartite consensus controller to address the challenge of achieving consensus among nonlinear agents, particularly when actuator faults are present, leading to significant obstacles. To tackle this issue, the controller is developed by adapting the Distributed Nonlinear Dynamic Inversion (DNDI) technique, thereby accommodating the impact of actuator faults. The randomness of the actuator the fault is taken into account to reflect real-world conditions. The the paper also furnishes comprehensive mathematical insights into the convergence of the fault-tolerant controller, establishing a robust theoretical foundation. An extensive array of simulation studies demonstrate that the proposed controller effectively manages actuator faults, leading to the successful attainment of bipartite consensus.

Keywords: Classical and optimal control methods, Nonlinear control

Keywords: Aerospace and space systems, Robotics and autonomous systems, Autonomous systems
Abstract: Monitoring moving ground vehicles using vision sensors mounted on Unmanned Aerial Vehicles (UAVs) in a densely populated area with high-rise buildings is a min-max problem. The cost function minimized or maximized by a pursuer or an evader is the integral of the distance between two vehicles over a finite time interval. One of the common approaches to the optimal tracking problem for UAVs is to minimize the cost function in the worst case caused by the evader. Extending the algorithm for one UAV to an algorithm for multiple UAVs requires collision avoidance capability. The cost function degradation to achieve collision avoidance must be minimal. We present an optimal collision avoidance target tracking algorithm combining the tracking command and the collision avoidance command. Finding the optimal combination becomes a line search optimization problem that can be solved with little computation. The resulting algorithm provides acceleration commands that can be directly used in the low-level controller of UAVs. The performance of the algorithm is demonstrated by multiple computer simulations.

Keywords: Aerospace and space systems, Transportation and vehicle systems, Nonlinear control
Abstract: This paper describes the application of input-output Nonlinear Dynamic Inversion (NDI) to flight control of a tilt-rotor actuated Vertical Short Take Off and Landing (VSTOL) platform. The NDI formulation is performed in the inertial reference frame resulting in a decoupled and linearised set of integrator virtual plants controlled using Linear Quadratic Integral (LQI) control. The NDI controller is continuously enabled along with a conventional fixed wing controller with the latter scheduled in and out of control authority as a function of the wing tilt/vector angle control input generated by the NDI controller.

Keywords: Classical and optimal control methods, Nonlinear control, Aerospace and space systems
Abstract: A novel full-envelope controller for an over-actuated fixed-wing vectored thrust eVTOL aircraft is presented. It proposes a generic control architecture applicable to piloted, semiautomatic and fully-automated flight consisting of an aircraft-level controller (high-level controller) and a control allocation scheme. The aircraft-level controller consists of a main inner-loop non-linear dynamic inversion controller and an outer-loop proportional-integral linear controller. The inner-loop classical non-linear dynamic inversion controller is used for forward cruise flight while the outer-loop proportional-integral linear controller is used for hover/low speed control and position control. The control allocation scheme uses a novel architecture which transfers the non-linearity in the vectored thrust effector model formulation to the computation of the actuator limits by converting the effector model from polar to rectangular form thus allowing the use of a linear optimisation technique. The linear optimisation technique is an Active Set Linear Quadratic Programming constrained optimisation algorithm with a weighted least squares formulation. The control allocation allocates the overall control demand (virtual controls) to individual redundant effectors while performing control error minimisation, control channel prioritization and control effort minimization. Simulation results shows forward transition from hover to cruise and clearly demonstrates that the controller can handle saturation (position or rate). The proposed controller can also handle actuator failures.

Keywords: Nonlinear control, Aerospace and space systems, Robotics and autonomous systems
Abstract: In this paper, an anti-windup compensation scheme is proposed for the manual mode of a rigid body attitude control system to make the angular velocity dynamics globally asymptotically stable despite actuator saturation. The addressed anti-windup design problem is challenging since the nominal control law includes a nonlinear dynamic inversion element to cancel the nonlinearity in the angular velocity dynamics. The stability of the compensated closed-loop system is proved via the Lyapunov stability criterion appropriately. Moreover, the superiority of the compensated system versus the uncompensated one is demonstrated by simulation.

Keywords: Nonlinear control, Predictive control, Multi-objective methods and optimisation
Abstract: In this paper, a Nonlinear Model Predictive Control is proposed to make a Quadrotor UAV track an energy-efficient trajectory generated off-line. The dynamically constrained, open-loop control problem is solved once and provides an energy-efficient trajectory that will have to be tracked by the quadrotor. The preliminary results demonstrate a noteworthy reduction in energy consumption when compared with the use of a standard MPC feedback controller. A 37% of energy saving was achieved in some cases

Keywords: Nonlinear control, Robotics and autonomous systems, Aerospace and space systems
Abstract: A long standing ambition in the aerospace industry is to flight test aircraft in wind tunnels. We propose a robotic manipulator system that can be operated with an aircraft wind tunnel model that replicates the longitudinal dynamics of the aircraft in free flight. A nonlinear aircraft-manipulator dynamics model developed with the Euler-Lagrange method is combined with the inverse kinematics to produce the relative joint angles for the robot manipulator to reproduce free flight trajectories in the wind tunnel working section. Simple PI control is used for the manipulator joint control to replicate the translational degrees of freedom, whilst the aircraft pitch is controlled via the aircraft elevator. The proposed scheme is tested in simulation and the results demonstrate the effectiveness of the proposed scheme.