Fuzzy logic systems‐based integral sliding mode fault‐tolerant control for a class of uncertain non‐linear systems

Hao, Li‐Ying; Park, Ju H.; Ye, Dan

doi:10.1049/iet-cta.2015.0716

Cited by 54 publications

(40 citation statements)

References 46 publications

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“…At present, there are many methods to control the active suspension system, including linear quadratic optimal control [7], [8], PID control [9], [10], adaptive control [11]- [16], neural network control [17]- [20], [29], and sliding mode variable structure control [21]- [23]. These suspension control methods can improve the ride comfort and ride stability of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fault Tolerant Control of Active Suspension Systems With Time-Varying Displacement and Velocity Constraints

Zhang

Liu

2020

IEEE Access

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In this paper, active suspension system is selected as the research object. Back-stepping method is adopted, and virtual fault tolerant controller, main fault tolerant controller and adaptive law are designed by constructing Time-varying Barrier Lyapunov Function (TVBLF), to ensure that the displacement and speed of the vehicle do not violate the constraint boundary and achieve the goal of fast fault tolerance. For the unknown continuous function caused by the uncertain body mass and other factors in the system, Radial Basis Function Neural Network (RBFNN) is used for approximation. At the same time, the suspension space limitation and tire dynamic load are analyzed. Finally, the effectiveness of the proposed fault-tolerant control method is verified by simulation of deviation fault and partial failure fault. INDEX TERMS Fault-tolerant control, semi-vehicle active suspension system, time-varying displacement, velocity constraints.

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Section: Introductionmentioning

confidence: 99%

Adaptive Fault Tolerant Control of Active Suspension Systems With Time-Varying Displacement and Velocity Constraints

Zhang

Liu

2020

IEEE Access

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“…The advantage of sliding mode controller is that it has strong robustness to disturbances and unmodeled dynamics, so it has also been widely applied. [12][13][14][15] However, all the above methods require that the system meets an important condition, that is, the unknown nonlinearity and the control input appear in the same equation of the state space model, which is usually regarded as the matching condition. In the actual system, there is a large class of nonlinear systems that do not meet the matching condition, such as the system of the mechanical hand which is driven by the motor.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy backstepping control for uncertain nonlinear systems with tracking error constraints

Wan

Liu

2019

Advances in Mechanical Engineering

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This article deals with the design of adaptive fuzzy backstepping control for uncertain nonlinear systems in strictfeedback form with tracking error constraints. In this article, a fuzzy system is used to approximate the unknown nonlinear functions and the differential of virtual control law of each subsystem. In order to satisfy the limitation of tracking error constraints, the barrier Lyapunov function is introduced. Moreover, by applying the minimal learning parameters technique, the number of online parameters update for each subsystem is reduced to only 1. The control scheme not only ensures the tracking error is not to transgress the constraint bounds but also solves the problem of ''explosion of complexity'' and greatly reduces the initial control input and the number of the adaptive parameters; this provides the conditions for the practical application. The simulation results show the effectiveness of the proposed method.

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“…To conquer the vulnerability of single SMC method and guarantee the system stability, the combination of SMC and FLC could be useful [17]. Many publications have reported effective schemes to apply fuzzy sliding mode control (FSMC) method for the controller design of several high-order nonlinear systems [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Sliding Mode Control for the Vehicle Height and Leveling Adjustment System of an Electronic Air Suspension

Sun

Cai

Yuan

et al. 2018

Chin. J. Mech. Eng.

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The accurate control for the vehicle height and leveling adjustment system of an electronic air suspension (EAS) still is a challenging problem that has not been effectively solved in prior researches. This paper proposes a new adaptive controller to control the vehicle height and to adjust the roll and pitch angles of the vehicle body (leveling control) during the vehicle height adjustment procedures by an EAS system. A nonlinear mechanism model of the full-car vehicle height adjustment system is established to reflect the system dynamic behaviors and to derive the system optimal control law. To deal with the nonlinear characters in the vehicle height and leveling adjustment processes, the nonlinear system model is globally linearized through the state feedback method. On this basis, a fuzzy sliding mode controller (FSMC) is designed to improve the control accuracy of the vehicle height adjustment and to reduce the peak values of the roll and pitch angles of the vehicle body. To verify the effectiveness of the proposed control method more accurately, the full-car EAS system model programmed using AMESim is also given. Then, the co-simulation study of the FSMC performance can be conducted. Finally, actual vehicle tests are performed with a city bus, and the test results illustrate that the vehicle height adjustment performance is effectively guaranteed by the FSMC, and the peak values of the roll and pitch angles of the vehicle body during the vehicle height adjustment procedures are also reduced significantly. This research proposes an effective control methodology for the vehicle height and leveling adjustment system of an EAS, which provides a favorable control performance for the system.

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Fuzzy logic systems‐based integral sliding mode fault‐tolerant control for a class of uncertain non‐linear systems

Cited by 54 publications

References 46 publications

Adaptive Fault Tolerant Control of Active Suspension Systems With Time-Varying Displacement and Velocity Constraints

Adaptive Fault Tolerant Control of Active Suspension Systems With Time-Varying Displacement and Velocity Constraints

Adaptive fuzzy backstepping control for uncertain nonlinear systems with tracking error constraints

Fuzzy Sliding Mode Control for the Vehicle Height and Leveling Adjustment System of an Electronic Air Suspension

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