Fuzzy Fault-Tolerant H∞ Control Approach for Nonlinear Active Suspension Systems with Actuator Failure

Mrazgua, Jamal; Tisssir, El Houssaine; Ouahi, Mohamed

doi:10.1016/j.procs.2019.01.059

Cited by 24 publications

(7 citation statements)

References 21 publications

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“…By choosing Q = I and solving Equation (10), the symmetric positive matrix P is obtained as Select the optimal virtual controllers α1 , α2 and the optimal control law u as…”

Section: Case 1 (With Bump Road Displacement)mentioning

confidence: 99%

Neuro‐adaptive output‐feedback optimized stochastic control for the active suspension systems with state constraints

Zhang

2021

Adaptive Control & Signal

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This article investigates an adaptive neural network (NN) output-feedback optimal control design problem for active suspension systems (ASSs) with stochastic disturbance. The ASSs under consideration contain the characteristics of spring nonlinear dynamics, unmeasured states, and state constraints. The NNs are developed to approximate the unknown nonlinear functions. Meanwhile, observer-based output feedback control design method is proposed based on the adaptive backstepping technique. Furthermore, the stability of the closed-loop system is demonstrated by constructing the barrier Lyapunov function, thus ensuring that the full-state constraints are not exceeded. In particular, the simulation validations are given for the cases of bump, C-class, and D-class road displacements inputs.Finally, the simulation results verify the effectiveness of the studied control strategy.

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“…By choosing Q = I and solving Equation (10), the symmetric positive matrix P is obtained as Select the optimal virtual controllers α1 , α2 and the optimal control law u as…”

Section: Case 1 (With Bump Road Displacement)mentioning

confidence: 99%

Neuro‐adaptive output‐feedback optimized stochastic control for the active suspension systems with state constraints

Zhang

2021

Adaptive Control & Signal

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“…A test illustrating a critical driving situation is performed under MATLAB software, to show the efficiency of the static output-feedback based H ∞ control for vehicle lateral dynamics model (1) represented by T-S fuzzy system (9). The parameters of the vehicle are shown in Table 1.…”

Section: Numerical Illustrationmentioning

confidence: 99%

“…The control based on the estimated state feedback is widely studied in recent years as in [7,8], The authors have proposed an approach to stabilize the system of vehicle dynamics in the presence of disturbances. In [6,8,9], the authors discuss a control method that tolerates sensor and actuator faults for vehicle dynamics. The H ∞ Control For Vehicle Active Suspension Systems In Finite Frequency Domain is studied in [11].…”

Section: Introductionmentioning

confidence: 99%

Static output-feedback $$H_\infty$$ control for T–S fuzzy vehicle lateral dynamics

et al. 2019

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This paper deals with static output-feedback H ∞ control for a system of the vehicle lateral dynamics, represented by Takagi-Sugeno (T-S) fuzzy models. Sufficient conditions of the existence of H ∞ control based on the static output-feedback are presented. The bilinear matrix inequalities are converted to a set of linear matrix inequalities, with the aid of some special derivations. Simulation results demonstrate the effectiveness of the proposed method.

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“…An actuator fault compensation scheme is proposed, which can achieve arbitrarily small tracking errors in the presence of nonlinear actuators with random faults [5]. And there are more and more control strategies for active suspension, such as H∞ control [4,[8][9][10][11], optimal control [12][13][14][15], neural network control [16][17][18][19], LQG control [20,21], predictive control [22], and sliding mode control [14,23].…”

Section: Introductionmentioning

confidence: 99%

Optimization of the New Index Reaching Law of the Active Suspension Sliding Mode Controller Based on the Cuckoo Search Algorithm

Wei

2021

Complexity

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To facilitate the performance of the active suspension system, the optimization of a new reaching law of the active suspension sliding mode controller based on cuckoo algorithm is addressed in this paper. Firstly, a linear model of the active suspension system is built. Then, according to the features of the new exponential reaching law, an active sliding mode control scheme based on the new sliding mode reaching law is designed. Finally, the simulation results are separated into two stages to verify the suitability and superiority of the proposed control scenario.

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Fuzzy Fault-Tolerant H∞ Control Approach for Nonlinear Active Suspension Systems with Actuator Failure

Cited by 24 publications

References 21 publications

Neuro‐adaptive output‐feedback optimized stochastic control for the active suspension systems with state constraints

Neuro‐adaptive output‐feedback optimized stochastic control for the active suspension systems with state constraints

Static output-feedback $$H_\infty$$ control for T–S fuzzy vehicle lateral dynamics

Optimization of the New Index Reaching Law of the Active Suspension Sliding Mode Controller Based on the Cuckoo Search Algorithm

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