Adaptive ℋ∞-control for nonlinear systems: a dissipation theoretical approach

The adaptive ℋ∞-control problem for parameter-dependent nonlinear systems with full information feedback is considered. The techniques from dissipation theory as well as the vector and parameter projection methods are used to derive the adaptive ℋ∞-control laws. Both of the projection techniques are rigorously treated. The adaptive robust stabilization for nonlinear systems with ℒ2-gain hounded uncertainties is investigated

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We consider a design problem of a variable gain robust output feedback controller with guaranteed ℒ2 gain performance for a class of Lipschitz uncertain nonlinear systems. The proposed variable gain robust output feedback controller achieves not only robust stability but also a specified ℒ2 gain performance. In this paper, we show that sufficient conditions for the existence of the proposed variable gain robust output feedback controller with guaranteed ℒ2 gain performance are given in terms of linear matrix inequalities (LMIs). Finally, a simple numerical example is included

Performance Guarantee of a Class of Continuous LPV System with Restricted-Model-Based Control

This paper considers the problem of the robust stabilisation of a class of continuous Linear Parameter Varying (LPV) systems under specifications. In order to guarantee the stabilisation of the plant with very large parameter uncertainties or variations, an output derivative estimation controller is considered. The design of such controller that guarantee desired  induced gain performance is examined. Furthermore, a simple procedure for achieving the  norm performance is proved for any all-poles single-input/single-output second order plant. The proof of stability is based on the polytopic representation of the closed loop under Lyapunov conditions and system transformations. Finally, the effectiveness of the proposed method is verified via a numerical example

Global Saturated Regulator with Variable Gains for Robot Manipulators

In this paper, we propose a set of saturated controllers with variable gains to solve the regulation problem for robot manipulators in joint space. These control schemes deliver torques inside the prescribed limits of servomotors. The gamma of variable gains is formed by continuous, smooth, and differentiable functions of the joint position error and velocity of the manipulator. A strict Lyapunov function is proposed to demonstrate globally asymptotic stability of the closed-loop equilibrium point. Finally, the functionality and performance of the proposal are illustrated via simulation results and comparative analysis against Proportional-Derivative (PD) control scheme on a two-degrees-freedom direct-drive robot manipulator

Control of power electronic interfaces in distributed generation.

Renewable energy has gained popularity as an alternative resource for electric power generation. As such, Distributed Generation (DG) is expected to open new horizons to electric power generation. Most renewable energy sources cannot be connected to the load directly. Integration of the renewable energy sources with the load has brought new challenges in terms of the system’s stability, voltage regulation and power quality issues. For example, the output power, voltage and frequency of an example wind turbine depend on the wind speed, which fluctuate over time and cannot be forecasted accurately. At the same time, the nonlinearity of residential electrical load is steadily increasing with the growing use of devices with rectifiers at their front end. This nonlinearity of the load deviates both current and voltage waveforms in the distribution feeder from their sinusoidal shape, hence increasing the Total Harmonics Distortions (THD) and polluting the grid. Advances in Power Electronic Interfaces (PEI) have increased the viability of DG systems and enhanced controllability and power transfer capability. Power electronic converter as an interface between energy sources and the grid/load has a higher degree of controllability compared to electrical machine used as the generator. This controllability can be used to not only overcome the aforementioned shortfalls of integration of renewable energy with the grid/load but also to reduce THD and improve the power quality. As a consequence, design of a sophisticated controller that can take advantage of this controllability provided by PEIs to facilitate the integration of DG with the load and generate high quality power has become of great interest. In this study a set of nonlinear controllers and observers are proposed for the control of PEIs with different DG technologies. Lyapunov stability analysis, simulation and experimental results are used to validate the effectiveness of the proposed control solution in terms of tracking objective and meeting the THD requirements of IEEE 519 and EN 50160 standards for US and European power systems, respectively

Advanced Discrete-Time Control Methods for Industrial Applications

This thesis focuses on developing advanced control methods for two industrial systems in discrete-time aiming to enhance their performance in delivering the control objectives as well as considering the practical aspects. The first part addresses wind power dispatch into the electricity network using a battery energy storage system (BESS). To manage the amount of energy sold to the electricity market, a novel control scheme is developed based on discrete-time model predictive control (MPC) to ensure the optimal operation of the BESS in the presence of practical constraints. The control scheme follows a decision policy to sell more energy at peak demand times and store it at off-peaks in compliance with the Australian National Electricity Market rules. The performance of the control system is assessed under different scenarios using actual wind farm and electricity price data in simulation environment. The second part considers the control of overhead crane systems for automatic operation. To achieve high-speed load transportation with high-precision and minimum load swings, a new modeling approach is developed based on independent joint control strategy which considers actuators as the main plant. The nonlinearities of overhead crane dynamics are treated as disturbances acting on each actuator. The resulting model enables us to estimate the unknown parameters of the system including coulomb friction constants. A novel load swing control is also designed based on passivity-based control to suppress load swings. Two discrete-time controllers are then developed based on MPC and state feedback control to track reference trajectories along with a feedforward control to compensate for disturbances using computed torque control and a novel disturbance observer. The practical results on an experimental overhead crane setup demonstrate the high performance of the designed control systems.Comment: PhD Thesis, 230 page

Research on Information Flow Topology for Connected Autonomous Vehicles

Information flow topology plays a crucial role in connected autonomous vehicles (CAVs). It describes how CAVs communicate and exchange information with each other. It predominantly affects the platoon\u27s performance, including the convergence time, robustness, stability, and scalability. It also dramatically affects the controller design of CAVs. Therefore, studying information flow topology is necessary to ensure the platoon\u27s stability and improve its performance. Advanced sliding mode controllers and optimisation strategies for information flow topology are investigated in this project. Firstly, the impact of information flow topology on the platoon is studied regarding tracking ability, fuel economy and driving comfort. A Pareto optimal information flow topology offline searching approach is proposed using a non-dominated sorting genetic algorithm (NSGA-II) to improve the platoon\u27s overall performance while ensuring stability. Secondly, the concept of asymmetric control is introduced in the topological matrix. For a linear CAVs model with time delay, a sliding mode controller is designed to target the platoon\u27s tracking performance. Moreover, the Lyapunov analysis is used via Riccati inequality to guarantee the platoon\u27s internal stability and input-to-output string stability. Then NSGA-II is used to find the homogeneous Pareto optimal asymmetric degree to improve the platoon\u27s performance. A similar approach is designed for a nonlinear CAVs model to find the Pareto heterogeneous asymmetric degree and improve the platoon\u27s performance. Thirdly, switching topology is studied to better deal with the platoon\u27s communication problems. A two-step switching topology framework is introduced. In the first step, an offline Pareto optimal topology search with imperfect communication scenarios is applied. The platoon\u27s performance is optimised using a multi-objective evolutionary algorithm based on decomposition (MOEA/D). In the second step, the optimal topology is switched and selected from among the previously obtained Pareto optimal topology candidates in real-time to minimise the control cost. For a continuous nonlinear heterogeneous platoon with actuator faults, a sliding mode controller with an adaptive mechanism is developed. Then, the Lyapunov approach is applied to the platoon\u27s tracking error dynamics, ensuring the systems uniformly ultimately bounded stability and string stability. For a discrete nonlinear heterogeneous platoon with packet loss, a discrete sliding mode controller with a double power reaching law is designed, and a modified MOEA/D with two opposing adaptive mechanisms is applied in the two-step framework. Simulations verify all the proposed controllers and frameworks, and experiments also test some. The results show the proposed strategy\u27s effectiveness and superiority in optimising the platoon\u27s performance with multiple objectives

Model-based control methods to improve the power qualify of grid-connected single-phase inverters.

Power electronic converters are commonly used for interfacing distributing generation sources (DGs) to the electrical power system networks. This is necessary because these DGs usually have different output characteristics and cannot be connected directly to the local load and/or the grid. The power electronic front-end converter is an inverter whose dc link is fed by an ac/dc converter or by a dc/dc converter, according to the DG source type. The commercial front-end inverters are designed to operate either in grid-connected (GC) mode or in stand-alone (SA) mode. In the SA mode, the inverter is connected to local load, but in the GC mode the inverter must be connected to the utility grid and a local load could be connected to this system as well. Based on this, any designed or proposed controller for such systems should work well in both operation modes. The control objective in SA mode is to improve the quality of the local load voltage, and the control objective in GC mode is to inject clean current to the grid with low total harmonic distortion (THD). Most of the control schemes in the literature have been designed to work in one of these operation modes and ensure low THD either for the local load voltage or for the injected grid current. However, some of the existing control schemes in the literature proposed different control architectures for each operation mode. Moreover, there are a few researches have been reported in the literature based on the cascaded control theory to obtain low THD for both the local load voltage simultaneously with the injected current to the grid in the grid-connected mode. Due to the growing penetration of the DG sources in the residential applications, single-phase grid-connected inverters have gained much attention. For this reason, the single-phase grid-connected inverter systems have been chosen in our study. Since such systems have nonlinearity in its behavior, different nonlinear model-based control schemes have been designed in order to improve the quality of the local load voltage while injecting clean current to the grid for single-phase grid-connected inverter systems by using single structure control scheme. Furthermore, the proposed control schemes ensure the seamless transfer between GC and SA operation modes without adjusting the controller structure and with self-synchronization ability

Second-Order Fault Tolerant Extended Kalman Filter for Discrete Time Nonlinear Systems

As missing sensor data may severely degrade the overall system performance and stability, reliable state estimation is of great importance in modern data-intensive control, computing, and power systems applications. Aiming at providing a more robust and resilient state estimation technique, this paper presents a novel second-order fault-tolerant extended Kalman filter estimation framework for discrete-time stochastic nonlinear systems under sensor failures, bounded observer-gain perturbation, extraneous noise, and external disturbances condition. The failure mechanism of multiple sensors is assumed to be independent of each other with various malfunction rates. The proposed approach is a locally unbiased, minimum estimation error covariance based nonlinear observer designed for dynamic state estimation under these conditions. It has been successfully applied to a benchmark target-trajectory tracking application. Computer simulation studies have demonstrated that the proposed second-order fault-tolerant extended Kalman filter provides more accurate estimation results, in comparison with traditional first- and second-order extended Kalman filter. Experimental results have demonstrated that the proposed second-order fault-tolerant extended Kalman filter can serve as a powerful alternative to the existing nonlinear estimation approaches