$${L_\infty }$$ Fault Estimation and Fault-Tolerant Control for Nonlinear Systems by T–S Fuzzy Model Method with Local Nonlinear Models

Yang, Wang; Li, Tieshan; Wu, Yue; Yang, Ximing; Chen, C. L. Philip; Long, Yue; Yang, Zhi-Xin; Ning, Jun

doi:10.1007/s40815-021-01061-6

Cited by 16 publications

(7 citation statements)

References 58 publications

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“…To tackle the trajectory tracking control issue of DP vessels amidst modeling uncertainties, environmental disturbances, and unpredictable velocities, ref. [23] combined performance control techniques with adaptive fuzzy backstepping control methods to design a novel adaptive fuzzy controller. In [24], a control strategy with high gain was given by combining the adaptive fuzzy method with the auxiliary dynamic system, considering the unknown parameters, unmeasured state, and saturated input of the ship dynamic model.…”

Section: Introductionmentioning

confidence: 99%

Integral Sliding Mode Output Feedback Control for Unmanned Marine Vehicles Using T–S Fuzzy Model with Unknown Premise Variables and Actuator Faults

Wang,

Yang,

Hao

et al. 2024

JMSE

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This paper addresses integral sliding mode output feedback fault-tolerant control (FTC) of unmanned marine vessels (UMVs) with unknown premise variables and actuator faults. Due to the complexity of the marine environment, the presence of uncertainties in the yaw angle renders the premise variables in the Takagi–Sugeno (T–S) fuzzy model of UMVs unknown. Consequently, traditional integral sliding mode techniques become infeasible. To address this issue, a control strategy combining integral sliding mode based on output feedback with a compensator utilizing switching mechanisms is proposed. First, a radial basis function neural network is used to approximate the nonlinear terms in the UMV T–S fuzzy model. In addition, an integral sliding mode surface is constructed based on fault estimation information and membership function estimation. On this basis, an FTC scheme based on integral sliding mode output feedback is developed to ensure that the UMV system is asymptotically stable and satisfies the prescribed H∞ performance index. Finally, simulation results are provided to demonstrate the effectiveness of the presented control strategy.

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Section: Introductionmentioning

confidence: 99%

Integral Sliding Mode Output Feedback Control for Unmanned Marine Vehicles Using T–S Fuzzy Model with Unknown Premise Variables and Actuator Faults

Wang,

Yang,

Hao

et al. 2024

JMSE

Self Cite

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“…[1][2][3][4][5] Recently, the problem of fault estimation for externally perturbed nonlinear systems based on unknown input observers is investigated by means of the T-S fuzzy modeling approach with local nonlinear models. 6 The designed proportional multiple integral observer enables simultaneous estimation of T-S fuzzy system states as well as actuator and sensor faults. 7 Moreover, fault-tolerant control (FTC) is an integral part of the system, and the system can effectively adapt to changes in the system by reconstructing the control accordingly to real-time fault signals.…”

Section: Introductionmentioning

confidence: 99%

“…For this research area, fruitful results have been reported in the literatures 1‐5 . Recently, the problem of fault estimation for externally perturbed nonlinear systems based on unknown input observers is investigated by means of the T‐S fuzzy modeling approach with local nonlinear models 6 . The designed proportional multiple integral observer enables simultaneous estimation of T‐S fuzzy system states as well as actuator and sensor faults 7 .…”

Section: Introductionmentioning

confidence: 99%

Robust fault estimation for T‐S fuzzy systems with intermittently sampled data based on finite information learning observer

Su,

Sun,

Huang

et al. 2023

Adaptive Control & Signal

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SummaryIn this article, we study the problem of robust fault estimation for a class of T‐S fuzzy systems with time delays and external disturbances based on the finite information learning observer. The learning observer with intermittent sampling is constructed and the change rate of output estimation error is introduced to estimate the system fault effectively. At the same time, by introducing a generalized inverse matrix to the designed observer, a sufficient condition for the stability of the error estimation system is given by using fuzzy Lyapunov function, which not only solves the problem of system fault and external disturbance estimation, but also reduces the conservatism of the obtained conclusion. Finally, the results described by LMI are solved numerically and simulated to demonstrate the effectiveness of the proposed method.

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“…During the past few decades, the felds of fault estimation (FE) technique and fault tolerant control (FTC) have been the result drawing an intensive research interests due to the increasing demands for system's performance, safety, and reliability. Active FTC and FE to a category of nonlinear systems particularly T-S fuzzy models [1][2][3] have a signifcant position in recent control implementation, as well as in supervision and reliability of actuators. In recent decades, a variety of methods have been developed, using adaptive observer [4][5][6] or SMO [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Multiplicative and Additive Actuator Faults Estimation‐Based Sliding Mode FTC for a Class of Uncertain Nonlinear System

Mabrouk

Brahim

Hmida

2023

Mathematical Problems in Engineering

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In this article, an adaptive sliding mode fault tolerant control (FTC) is improved in the case of uncertain nonlinear system which is affected by both multiplicative and additive faults in actuator. Especially, when the nonlinear system is modeled by Takagi–Sugeno (T-S) fuzzy system with local nonlinear model. The main contribution of this paper is developing a model of multiplicative faults, which offers a more realistic dynamic evolution of the actuator degradation. The degradation process is modeled by Wiener process and estimated by the maximum likelihood estimation (MLE). Sliding mode observer (SMO) is conceived to realize the additive actuator faults using convex multiobjective optimization. On these bases, the estimated multiplicative and additive actuator faults are used to design the adaptive sliding mode controller (SMC). Finally, the proposed fault-tolerant control scheme is demonstrated by the results of inverted pendulum system simulation.

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$${L_\infty }$$ Fault Estimation and Fault-Tolerant Control for Nonlinear Systems by T–S Fuzzy Model Method with Local Nonlinear Models

Cited by 16 publications

References 58 publications

Integral Sliding Mode Output Feedback Control for Unmanned Marine Vehicles Using T–S Fuzzy Model with Unknown Premise Variables and Actuator Faults

Integral Sliding Mode Output Feedback Control for Unmanned Marine Vehicles Using T–S Fuzzy Model with Unknown Premise Variables and Actuator Faults

Robust fault estimation for T‐S fuzzy systems with intermittently sampled data based on finite information learning observer

Simultaneous Multiplicative and Additive Actuator Faults Estimation‐Based Sliding Mode FTC for a Class of Uncertain Nonlinear System

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