Adaptive robust fault tolerant control design for a class of nonlinear uncertain MIMO systems with quantization

Ao, Wei; Yong-dong, Song; Chen, Wen

doi:10.1016/j.isatra.2017.03.016

Cited by 22 publications

(6 citation statements)

References 17 publications

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“…where e x = x − x ^ , and the gains K p and T i , are chosen to be low to reduce noise amplification and to guarantee the stability of the error dynamics simultaneously (Ao et al, 2017). Further, the rate of change of the fault can also be identified with the proposed observer scheme.…”

Section: The Proposed Adaptive Neuro-fuzzy Pi Tolerant Controllermentioning

confidence: 99%

“…In practical applications, disturbances, modelling errors and unmeasured uncertainties are such factors that should be decoupled from the symptoms to obtain precise fault information. Many approaches have been developed to deal with the impact of disturbances on fault diagnosis (Ao et al, 2017; Castillo et al, 2012; Sallem et al, 2014; Shi and Patton, 2015; Xie and Yang, 2017).…”

Section: Introductionmentioning

confidence: 99%

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An adaptive fault tolerant neuro-fuzzy based proportional-integral controller for a nonlinear system

Zhou

2018

Transactions of the Institute of Measurement and Control

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In this paper, an adaptive proportional-integral controller based on a fuzzy relational model is developed for the purpose of fault tolerant control in a nonlinear, information-poor system. First, the methods of fault tolerant control are briefly introduced. An air-cooling subsystem in a heating, ventilating and air-conditioning system is used as an example to describe the fuzzy relational modelling procedure. Then a proportional-integral (PI) observer is established for fault identification and a PI-based adaptive controller is designed for fault tolerance with varied parameter adjusting. By introducing the fault estimation, an adaptive mechanism is adopted to update the parameter selection in the control scheme. Sensor noise is also considered in the method and simulation experiments are performed to verify the effectiveness of the proposed scheme.

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Section: The Proposed Adaptive Neuro-fuzzy Pi Tolerant Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An adaptive fault tolerant neuro-fuzzy based proportional-integral controller for a nonlinear system

Zhou

2018

Transactions of the Institute of Measurement and Control

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“…Furthermore, FTC problem for the discrete-time dynamic systems has been addressed by the estimation of fault and state. In Ao et al [22], an adaptive robust FTC has been proposed for the nonlinear uncertain MIMO systems. Fault estimation and FTC scheme have been designed simultaneously for systems with generalized sector input non-linearity in Hashemi and Tan [23].…”

Section: Introductionmentioning

confidence: 99%

Fault estimation and fault tolerant control for linear stochastic uncertain systems

Ding

Zhang

2022

Asian Journal of Control

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This article investigates the fault estimation and fault tolerant control (FTC) problems for linear stochastic uncertain systems. By introducing the fictitious noise, the fault is augmented as part of the systems state, and then a robust estimator is proposed to simultaneously obtain the state and fault estimation. Based on the estimated information, the active FTC is presented to eliminate the impact of the fault. Finally, a simulation example is conducted to demonstrate the effectiveness of our main method.

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“…The so-called feedback linearized system refers to a kind of nonlinear system linearized by appropriate nonlinear feedback control [22]. Based on the feedback linearization, the control objectives such as models match, pole assignment, and tracking can be further realized.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fault Compensation and Disturbance Suppression Design for Nonlinear Systems with an Aircraft Control Application

Yao

Yang

2020

International Journal of Aerospace Engineering

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A comprehensive adaptive compensation control strategy based on feedback linearization design is proposed for multivariable nonlinear systems with uncertain actuator fault and unknown mismatched disturbances. Firstly, the linear dynamic system is obtained through nonlinear feedback linearization, and the dynamic model of the mismatched disturbances as well as its relevance to the nonlinear system is given. The effect of disturbances on the system output is suppressed with the basic controller of the linearized system. Then, a direct adaptive controller is developed for the multiple uncertain actuator faults. Finally, an integrated algorithm based on adaptive weighted fusion could provide an effective compensation for the effect of multiple uncertain faults and mismatched disturbances. Thus, the stability and asymptotic tracking performance of the closed-loop system are ensured. The feasibility and performance of the proposed control strategy are validated by the numerical simulation results.

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Adaptive robust fault tolerant control design for a class of nonlinear uncertain MIMO systems with quantization

Cited by 22 publications

References 17 publications

An adaptive fault tolerant neuro-fuzzy based proportional-integral controller for a nonlinear system

An adaptive fault tolerant neuro-fuzzy based proportional-integral controller for a nonlinear system

Fault estimation and fault tolerant control for linear stochastic uncertain systems

Adaptive Fault Compensation and Disturbance Suppression Design for Nonlinear Systems with an Aircraft Control Application

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