scholarly journals Relaxed State and Fault Estimation for Vehicle Lateral Dynamics Represented by T–S Fuzzy Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
N. El Youssfi ◽  
R. El Bachtiri ◽  
T. Zoulagh ◽  
H. El Aiss
Keyword(s):  
Fuzzy Systems ◽  
Sufficient Conditions ◽  
State Equation ◽  
Observer Design ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Vehicle Model ◽  
Lateral Dynamics ◽  
Takagi Sugeno ◽  
Vehicle Lateral Dynamics

This paper deals with the problem of observer design of the vehicle model which is represented by Takagi–Sugeno (T–S) fuzzy systems with the presence of uncertainties. A relaxed observer design is presented to estimate the unmeasurable states and the faults of the vehicle lateral dynamics model, simultaneously. The vehicle model is transformed into a system with unknown inputs. Then, it is rebuilt by adding the default to the system state equation. Based on the Lyapunov function approach and the introduction of some slack variables, sufficient conditions of unknown input observer design are formulated as Linear Matrix Inequalities (LMIs). Finally, the simulation section clearly shows the importance and effectiveness of the proposed strategy.

Fault Estimation and Fault-Tolerant Control Via a Novel Proportional–Integral Observer in Singular Takagi-Sugeno Fuzzy Systems

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Min Li ◽  
Ming Liu ◽  
Yingchun Zhang ◽  
Zhuo Chen
Keyword(s):  
Fuzzy Systems ◽  
Controller Design ◽  
Fault Tolerant ◽  
Sufficient Conditions ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Closed Loop System ◽  
Proportional Integral ◽  
System States ◽  
Takagi Sugeno

This paper deals with the fault observer and fault-tolerant controller design for singular Takagi–Sugeno (T–S) fuzzy systems subject to actuator faults. First, a novel proportional-integral observer is constructed to estimate the system states and faults. Sufficient conditions for the existence of the proposed observer are given in linear matrix inequality (LMI) terms. Furthermore, based on the state and fault estimation (FE), a fault-tolerant controller (FTC) is designed to effectively accommodate the influence of fault upon state and ensure that the closed-loop system is stable. Finally, a numerical example is given to show the effectiveness of the presented method.

New Nonlinear Takagi–Sugeno Vehicle Model for State and Road Curvature Estimation via a Nonlinear PMI Observer

2014 ◽  
Vol 23 (2) ◽  
pp. 155-170
Author(s):  
Zedjiga Yacine ◽  
Dalil Ichalal ◽  
Naima Ait Oufroukh ◽  
Said Mammar ◽  
Said Djennoune
Keyword(s):  
Estimation Error ◽  
Longitudinal Velocity ◽  
Multiple Integral ◽  
Lyapunov Theory ◽  
Observer Design ◽  
Force Model ◽  
Vehicle Model ◽  
Lateral Dynamics ◽  
Bounded Error ◽  
Takagi Sugeno

AbstractThe present article deals with an observer design for nonlinear vehicle lateral dynamics. The contributions of the article concern the nonconsideration of any force model and the consideration that the longitudinal velocity is time varying, which is more realistic than the assumption that it is constant. The vehicle model is then represented by an exact Takagi–Sugeno (TS) model via the sector nonlinearity transformation. A proportional multiple integral (PMI) observer based on the TS model is designed to estimate simultaneously the state vector and the unknown input (lateral forces and road curvature). The convergence conditions of the estimation error are expressed under LMI formulation using the Lyapunov theory, which guaranties a bounded error. Simulations are carried out for comparison between the conventional PI observer, the enhanced PI observer, and the PMI observer. Finally, experimental results are provided to illustrate the performances of the proposed PMI observer.

Finite Time Passive Reliable Filtering for Fuzzy Systems With Missing Measurements

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
S. Vimal Kumar ◽  
R. Sakthivel ◽  
M. Sathishkumar ◽  
S. Marshal Anthoni
Keyword(s):  
Finite Time ◽  
Fuzzy Systems ◽  
Filter Design ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Missing Measurements ◽  
Randomly Occurring Uncertainties ◽  
Error System ◽  
Takagi Sugeno ◽  
Reliable Filtering

This paper investigates the problem of robust finite time extended passive reliable filtering for Takagi–Sugeno (T–S) fuzzy systems with randomly occurring uncertainties, missing measurements, and time-varying delays. Moreover, two stochastic variables satisfying the Bernoulli random distribution are introduced to characterize the phenomenon of the randomly occurring uncertainties and missing measurements. By skillfully choosing a proper Lyapunov–Krasovskii functional (LKF), a new set of sufficient conditions in terms of linear matrix inequalities (LMI) is derived to ensure that the filtering error system is robustly stochastically finite time bounded (SFTB) with a desired extended passive performance index. Based on the obtained sufficient conditions, an explicit expression for the desired filter can be computed. Finally, two numerical examples are provided to show the effectiveness of the proposed filter design technique.

Vehicle lateral motion control via robust delay-dependent Takagi-Sugeno strategy

2021 ◽  
pp. 014233122097994
Author(s):  
Serdar Coskun ◽  
Lin Li
Keyword(s):  
Motion Control ◽  
Communication Delay ◽  
Linear Matrix ◽  
Lateral Motion ◽  
Dynamics Model ◽  
Lateral Dynamics ◽  
And Performance ◽  
Delay Dependent ◽  
Takagi Sugeno ◽  
Vehicle Lateral Dynamics

Presented in this research paper is an integrated direct yaw moment control (DYC) and active front steering (AFS) for an uncertain vehicle lateral dynamics model considering network-induced communication delay, which is a time-varying continuous function with a known upper bound. Firstly, we consider tire cornering stiffness as a non-linear norm-bounded uncertain system that is modeled by fuzzy membership functions, and then vehicle lateral dynamics model is expressed by a set of linear Takagi-Sugeno (T-S) uncertain fuzzy models. Secondly, since the network-induced communication delay in vehicle control system is an inherent reason for stability and performance degradation, we derive a robust delay-dependent [Formula: see text] control methodology via the Lyapunov-Krasovskii functional for stability and performance conditions of the closed-loop system. For the synthesis, the robust control method is employed within the T-S fuzzy-model-based analysis framework and formulations are performed based on the solution of delay-dependent linear matrix inequalities (LMIs). The simulation study is presented using MATLAB/Simulink to show the achieved improvements in tracking variables via the designed robust fuzzy [Formula: see text] state-feedback controller. The proposed fuzzy robust delay-dependent controller is compared with a linear robust delay-dependent controller to clearly show the tracking improvements for different road conditions. Moreover, a performance-based analysis is carried out to demonstrate the advantage of the design with respect to different delay values. It is confirmed from the analysis results that the proposed fuzzy controller can successfully stabilize and possess improved tracking performance for vehicle lateral motion control.

scholarly journals Adaptive Proportional Integral Observer Design for Interval Type 2 Takagi–Sugeno Fuzzy Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Atef Khedher ◽  
Ilyes Elleuch ◽  
Kamal BenOthman
Keyword(s):  
Fuzzy Systems ◽  
Observer Design ◽  
Adaptive Observer ◽  
Fault Estimation ◽  
Sensor Faults ◽  
Proportional Integral ◽  
Augmented State ◽  
Interval Type ◽  
Takagi Sugeno

In this paper, the problem of fault estimation in systems described by Takagi–Sugeno fuzzy systems is studied. A proportional integral observer is conceived in order to reconstruct state and faults which can affect the studied system. Proportional integral observer can easily estimate actuator faults which are assimilated to be as unknown inputs. In order to estimate actuator and sensor faults, a mathematical transformation is used to conceive an augmented system, in which the initial sensor fault appears as an unknown input. Considering the augmented state, it is possible to conceive an adaptive observer which is able to estimate the whole state and faults. The noise effect on the state and fault estimation is also minimized in this study, which provides some robustness properties to the proposed observer. The proportional integral observer is conceived for nonlinear systems described by Takagi–Sugeno fuzzy models.

New Sufficient Conditions on H∞ Filter Design for Nonlinear T-S Fuzzy Systems with Time Delays

2012 ◽  
Vol 263-266 ◽  
pp. 162-166
Author(s):  
Su Huan Yi ◽  
Sheng Juan Huang
Keyword(s):  
Fuzzy Systems ◽  
Time Delays ◽  
Filter Design ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Time Varying Delay ◽  
Weighting Matrix ◽  
Decoupling Approach ◽  
Takagi Sugeno ◽  
Varying Delay

This paper focuses on the problem of H∞ filter design for continuous Takagi-Sugeno (T-S) fuzzy systems with an interval time-varying delay in the state. Based on the free weighting matrix method combined with a matrix decoupling approach, some new sufficient results are proposed in forms of linear matrix inequalities (LMIs), which can achieve much less conservative feasibility conditions. Finally, the effectiveness of the proposed method is demonstrated ba an example.

scholarly journals Observer-based fault-tolerant control against sensor failures for fuzzy systems with time delays

2011 ◽  
Vol 21 (4) ◽  
pp. 617-627 ◽  
Author(s):  
Shaocheng Tong ◽  
Gengjiao Yang ◽  
Wei Zhang
Keyword(s):  
Fuzzy Systems ◽  
Time Delays ◽  
Fault Tolerant ◽  
Sufficient Conditions ◽  
Fault Tolerant Control ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Sensor Failures ◽  
On Line ◽  
Augmented State

Observer-based fault-tolerant control against sensor failures for fuzzy systems with time delaysThis paper addresses the problems of robust fault estimation and fault-tolerant control for Takagi-Sugeno (T-S) fuzzy systems with time delays and unknown sensor faults. A fuzzy augmented state and fault observer is designed to achieve the system state and sensor fault estimates simultaneously. Furthermore, based on the information of on-line fault estimates, an observer-based dynamic output feedback fault-tolerant controller is developed to compensate for the effect of faults by stabilizing the resulting closed-loop system. Sufficient conditions for the existence of both a state observer and a fault-tolerant controller are given in terms of linear matrix inequalities. A simulation example is given to illustrate the effectiveness of the proposed approach.

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