Adaptive neural network fault-tolerant control for MIMO systems with dead zone inputs

Zhou, Qi; Lin, Guohuai; Ma, Hui; Lu, Renquan

doi:10.1360/ssi-2019-0198

Cited by 2 publications

(2 citation statements)

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“…Since then, with the help of intelligent control technologies such as neural networks and fuzzy logic systems, the constraint conditions required by the adaptive backstepping design has been removed. And an increasing number of related results have been proposed in References 11,[25][26][27][28] Note that the tuning functions are proposed by Krstic, Kanellakopoulos and Kokotovic like Reference 29. In higher-order systems, the tuning functions are complicated, and the structure becomes more verbose with each step, which is caused by the property of backstepping method itself.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive fault‐tolerant control of nonlinear systems based on tuning functions

Chen

2023

Intl J Robust & Nonlinear

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This article investigates the tracking control problem of adaptive fault‐tolerant control (AFTC) for a class of strict‐feedback nonlinear systems with actuator/sensor faults and unmatched disturbances. The sensor/actuator faults include bias, drift, loss of accuracy, and loss of effectiveness. Our main control objective is to investigate an adaptive fault‐tolerant control algorithm with the help of tuning functions, adaptive control technology, fuzzy logic systems (FLSs) and so on. For unknown nonlinear functions and fault items, FLSs and adaptive control technology are utilized to approximate them. Furthermore, over‐parameterization problem existed in the backstepping‐based controller design is solved by introducing the tuning functions. Theoretical analysis proves that our proposed AFTC scheme can ensure that all the signals in the closed‐loop system are bounded and the tracking error remains within a small range of zero even if a series of faults mentioned above occur. In the end, the simulation results show that the presented AFTC strategy is feasible and effective.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%