M. Oudghiri

Robust observer-based fault-tolerant control for vehicle lateral dynamics

This paper presents online sensor Fault Detection and Isolation (FDI) and the associated Fault-Tolerant Control (FTC) algorithm for a vehicle lateral dynamics represented by the uncertain Takagi-Sugeno (T-S) fuzzy model. The fault-detection scheme is based on a bank of observers method. Using the LMI formulation, the T-S fuzzy model of the vehicle non-linear dynamics is used to design an observer-based output feedback controller. To demonstrate the effectiveness of the proposed strategy, simulation results are given.

Observer-based robust fuzzy control for vehicle lateral dynamics

In this paper, the robust fuzzy control for four wheels steering (4WS) vehicle dynamics is studied via a Takagi-Sugeno (T-S) uncertain fuzzy model when the road adhesion conditions change and the sideslip angle is unavailable for measurement. After giving the nonlinear model of the vehicle, its representation by a T-S uncertain fuzzy model is discussed. Next, based on the uncertain fuzzy model of the 4WS Vehicle a fuzzy controller and a fuzzy observer are developed. The closed loop stability conditions of a vehicle with the fuzzy controller and the observer are parameterized in terms of linear matrix inequality (LMI) problem which can be solved very efficiently using the convex optimization techniques. The numerical simulation of the vehicle handling with and without the use of the developed observer and controller has been carried out. The simulation results obtained indicate that considerable improvements in the vehicle handling can be achieved whenever the vehicle is governed by the proposed fuzzy observer and fuzzy controller

One-Step procedure for robust output h8 fuzzy control

This paper addresses robust observer based Hinfin control problem for Takagi-Sugeno fuzzy systems with time-varying norm bounded uncertainties. Sufficient relaxed conditions for synthesis of a fuzzy observer and a fuzzy controller for T-S fuzzy systems are derived in terms of a set of linear matrix inequalities (LMIs). In comparison with the existing techniques in literature, the proposed approach considerably simplifies the design procedure and gives in only one step the controller and the observer gains. The observer and controller designed are capable to reject the disturbance assumed known but norm bounded. In order to highlight the performance of the proposed control algorithm, numerical simulations are performed.

Lateral vehicle velocity estimation using fuzzy sliding mode observer

This paper presents a robust method for estimation the lateral velocity of vehicle. The proposed observer describes a simple structure that contains a sliding mode term which turns out to be robust against output noises and parameters variations as well as sustained disturbances The given nonlinear model of the vehicle is then represented by an uncertain Takagi-Sugeno fuzzy model when the road adhesion conditions change and the sideslip angle is unavailable for measurement. After giving the nonlinear model of the vehicle, its representation by a T-S uncertain fuzzy model is discussed. Stability conditions of such observers are expressed in terms of linear matrix inequalities (LMI). To illustrate the effectiveness of the proposed design observer, a numerical simulation is given.

Robust output fuzzy control for vehicle lateral dynamic stability improvement

This paper deals with the robust control for Four Wheels Steering (4WS) vehicle dynamics when the road adhesion conditions change and the sideslip angle is unavailable for measurement. The non-linear model of the vehicle is first represented by an uncertain Takagi-Sugeno model. Next, the robust output stabilisation of the vehicle is considered. The controller and the observer are designed in terms of Bilinear Matrix Inequalities (BMI) problem. A method is then proposed to get the LMI formulation resolved sequentially. The obtained simulation results indicate that considerable improvements in the vehicle handling can be achieved when the vehicle is governed by the proposed fuzzy observer-based controller.

Control and Sensor Fault-Tolerance of Vehicle Lateral Dynamics

In this paper, fault tolerant control (FTC) system is developed for lateral vehicle dynamics by combining static output feedback control and sliding mode observers for improving vehicle handling and stability under sensors faults. The system consists of three blocks: fault detection and isolation (FDI) block, a static output feedback controller block and a switcher block. The nonlinear two degrees of freedom vehicle motion (bicycle model) is described by a Takagi-Sugeno (T-S) fuzzy model. The strategy of the FDI method is based on a bank of observers, each one is constructed using sliding mode design techniques to estimate the system state vector. Thus the diagnostic signal-residuals are generated by the comparison of measured and estimated outputs and the faulty sensor is isolated. Simulations demonstrate that the vehicle maintains acceptable performance after either set of yaw rate sensor and lateral velocity sensor has failed.

A fuzzy approach for sensor fault-tolerant control of vehicle lateral dynamics

This paper presents fault-tolerant control (FTC) architecture for vehicle lateral dynamics described by Takagi-Sugeno (TS) fuzzy model with parametric uncertainties and sensor faults. Using the LMI formulation, the T-S uncertain fuzzy model of vehicle dynamics is used to design an output feedback observer-based controller, a method based on observer bank is then investigated for detection, isolation and accommodation of sensor faults. Simulations show that the sensor faults are detected immediately after their occurrences and illustrate the proposed FTC strategy.

Vehicle yaw control using a robust H ∞ observer-based fuzzy controller design

A vehicle dynamics control system has been developed in this study for improving vehicle yaw rate dynamics under critical motions. The system consists of a fuzzy robust Hinfin estimated state feedback controller. The variation of the road adhesion conditions is considered and represented by additive parametric uncertainties in the vehicle Takagi-Sugeno fuzzy model. The vehicle lateral velocity is unavailable for measurement and it is estimated by a fuzzy observer. The gains of the fuzzy controller and fuzzy observer are determined in terms of linear matrix inequality (LMI). Simulations have been conducted to evaluate the performance of the closed loop system under various driving conditions and results are presented in this paper.

Robust Output H∞ Fuzzy Control for Active Fault Tolerant Vehicle Stability

Abstract This paper presents an active Fault Tolerant Control (FTC) strategy for vehicle lateral dynamics. A bicycle vehicle model using small angle approximations is used to represent vehicle behavior. Firstly, the nonlinear lateral vehicle dynamics is approximated by a Takagi-Sugeno fuzzy model with parametric uncertainties and sensor faults. Secondly a robust H ∞ output controller is used. A method based on a bank of observers is used for detection and isolation of sensor faults. The effectiveness of the proposed strategy have been illustrated in simulation.