On the nonlinear output regulation for systems described by Takagi-Sugeno fuzzy descriptor models with a steady-state mapping as an LMI optimization problem

This paper is devoted to provide a numerical solution the nonlinear output regulation problem for descriptor systems. The control law under design is a nonlinear one, it consists on a nonlinear stabilizer combined with linear steady-state mapping as well as nonlinear steady-state input mapping; all of them are computed via linear matrix inequalities. A numerical example as well as a mechanical system as well are used to illustrate the viability of the proposed approach.

Optimal H∞ Control for Lateral Dynamics of Autonomous Vehicles

This paper presents the design and validation of a model-based H∞ vehicle lateral controller for autonomous vehicles in a simulation environment. The controller was designed so that the position and orientation tracking errors are minimized and so that the vehicle is able to follow a trajectory computed in real-time by exploiting proper video-processing and lane-detection algorithms. From a computational point of view, the controller is obtained by solving a suitable LMI optimization problem and ensures that the closed-loop system is robust with respect to variations in the vehicle’s longitudinal speed. In order to show the effectiveness of the proposed control strategy, simulations have been undertaken by taking advantage of a co-simulation environment jointly developed in Matlab/Simulink © and Carsim 8 ©. The simulation activity shows that the proposed control approach allows for good control performance to be achieved.

Global Attitude Stabilization of a Rigid Body on SO(3) via Observer-based Hybrid Feedback Under Constraints

This paper studies the global stabilization of a rigid body attitude, a task that is subject to topological obstacles. Theseobstructions preclude the existence of a globally stable equilibrium point. Consequently, the rigid body attitude cannotbe globally stabilized by continuous feedback control laws. In order to resolve this challenge, this paper presents anobserver-based hybrid feedback control law. Thereafter, in order to derive the proposed feedback law, a new kind ofsynergistic potential functions is presented which induces a gradient vector eld to globally stabilize a given set. Moreover, the gradient of the proposed synergistic potential functions is utilized to derive a hybrid angular velocityobserver. The outputs of the proposed observer are employed to produce the necessary damping from the noisy measurements of the attitude. Furthermore, this paper considers two types of constraints: angular velocity constraints, and input torque constraints. Afterward, these constraints are formulated in terms of the Linear Matrix Inequalities (LMI) optimization problem to perform constraints satisfaction at all times. Moreover, this paper introduces a novel hybrid quantizer to deal with the problem of the low-price wireless network. This paper analyzes the global asymptotic stability of the reference set via the Lyapunov's method. Finally, a comparative study in simulations is provided to assess the performance of the proposed control technique.

Lyapunov-based Methods for Maximizing the Domain of Attraction

This paper investigates Lyapunov approaches to expand the domain of attraction (DA) of nonlinear autonomous models. These techniques had been examined for creating generic numerical procedures centred on the search of rational and quadratic Lyapunov functions. The outcomes are derived from all investigated methods: the method of estimation via Threshold Accepted Algorithm (TAA), the method of estimation via a Zubov technique and the method of estimation via a linear matrix inequality (LMI) optimization and genetic algorithms (GA). These methods are effective for a large group of nonlinear models, they have a significant ability of improvement of the attraction domain area and they are distinguished by an apparent propriety of direct application for compact and nonlinear models of high degree. The validity and the effectiveness of the examined techniques are established based on a simulation case analysis. The effectiveness of the presented methods is evaluated and discussed through the study of the renowned Van der Pol model.

Experimental Study of Sensor Fault-Tolerant Control for an Electro-Hydraulic Actuator Based on a Robust Nonlinear Observer

Electro-hydraulic actuators (EHAs) have been widely used in modern industries. However, sensor faults and actuator faults in EHA systems can arise due to aging during operation, making the system unstable and unsafe. To solve these issues, fault-tolerant control (FTC) techniques for EHA systems have been studied intensively. In this paper, an FTC is proposed and developed for the mini motion package (MMP) EHA system. First, a mathematical model of the MMP system is formulated and improved to provide position tracking control using a well-known proportional-integral-derivative (PID) controller. Second, an unknown input observer (UIO) reconstruction is performed to estimate the states, disturbances, and sensor faults so that an asymptotically stable control error can be obtained by a linear matrix inequality (LMI) optimization algorithm through Lyapunov’s stability condition. Third, the FTC designed for the nonlinear discrete-time system is formed from fault compensation based on a residual logic signal to implement the fault compensation process and ensure stability and tracking performance with respect to minimizing impacts of disturbances and sensor faults. Here, residual is defined by the difference between state response and state estimation. Finally, numerical simulations and experiments of the MMP system are presented to illustrate the efficiency of the proposed FTC technique.

A comparative study of nonlinear circle criterion based observer and H∞ observer for induction motor drive

<span lang="EN-US">This paper deals with a comparative study of circle criterion based nonlinear observer<em> </em>and <em>H_∞</em> observer for induction motor (IM) drive. The advantage of the circle criterion approach for nonlinear observer design is that it directly handles the nonlinearities of the system with less restriction conditions in contrast of the other methods which attempt to eliminate them. However the <em>H_∞</em> observer guaranteed the stability taking into account disturbance and noise attenuation. Linear matrix inequality (LMI) optimization approach is used to compute the gains matrices for the two observers. The simulation results show the superiority of <em>H_∞</em> observer in the sense that it can achieve convergence to the true state, despite the nonlinearity of model and the presence of disturbance.</span>