Adaptive Fixed-Time Tracking Control for Nonlinear Systems Based on Finite-Time Command-Filtered Backstepping

Chen, Ming; Ying-sen, LI; Wang, Huanqing; Peng, Kaixiang; Wu, Li‐Bing

doi:10.1109/tfuzz.2022.3206507

Cited by 25 publications

(9 citation statements)

References 43 publications

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“…Lemma 2 (28,32). For the system (5), if there is a positive definite function V(x) with the initial value V(x 0 ), and some real numbers a > 0, b > 0, 0 < p < 1, q > 1, and…”

Section: Rbfnns and Preliminariesmentioning

confidence: 99%

“…Remark In References 32 and 33 the signum functions were used construct compensation mechanism, but they will cause the chattering, which may excite unmodeled high‐frequency dynamics and even degrade control performance. In this article, the proposed compensation mechanisms are constructed without using signum function, which can avoid chattering problem and achieve the fixed‐time convergence of the compensation signals

{\xi}_i

i \in 𝕀 [1, n]

.…”

Section: Control Law Design and Stability Analysismentioning

confidence: 99%

“…Many fixed‐time control laws have been developed for various nonlinear systems during the past few years 29–31 . Recently, a distinctive adaptive fixed‐time tracking control law was proposed via CFB for strict‐feedback nonlinear systems in Reference 32. It should be mentioned that the command filters utilized in Reference 32 are first‐order Levant differentiators, which can guarantee only the finite‐time estimation performance.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, a distinctive adaptive fixed‐time tracking control law was proposed via CFB for strict‐feedback nonlinear systems in Reference 32. It should be mentioned that the command filters utilized in Reference 32 are first‐order Levant differentiators, which can guarantee only the finite‐time estimation performance. Therefore, the author in Reference 32 has pointed out that the proposed control scheme could not guarantee that all the variables of the closed‐loop are practically fixed‐time stable.…”

Section: Introductionmentioning

confidence: 99%

“…It should be mentioned that the command filters utilized in Reference 32 are first‐order Levant differentiators, which can guarantee only the finite‐time estimation performance. Therefore, the author in Reference 32 has pointed out that the proposed control scheme could not guarantee that all the variables of the closed‐loop are practically fixed‐time stable. To the best of our knowledge, there is few literature about fixed‐time command filtered fixed‐time control until now.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Fixed‐time adaptive fault‐tolerant tracking control for uncertain strict‐feedback nonlinear systems via command filtered backstepping

Qi,

2024

Intl J Robust & Nonlinear

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In this article, the fault‐tolerant tracking control is addressed for uncertain strict‐feedback nonlinear systems with actuator faults. Neural networks are utilized to identify unknown dynamics in strict‐feedback nonlinear systems, and the adaptive technique is employed to estimate the parameter of actuator effectiveness. More importantly, a command filtered backstepping control method is improved by introducing a fixed‐time command filter and modifying virtual control laws with compensation mechanisms. By incorporating the adaptive neural networks into the command filtered backstepping design framework, a novel adaptive fault‐tolerant control law is constructed. Under the presented control law, the negative influence of the actuator fault and unknown dynamics is effectively compensated simultaneously. Besides, the “explosion of complexity” and “singularity” problems of backstepping is avoided. Moreover, the practical fixed‐time stability is guaranteed for the resulted closed‐loop system.

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“…Lemma 2 (28,32). For the system (5), if there is a positive definite function V(x) with the initial value V(x 0 ), and some real numbers a > 0, b > 0, 0 < p < 1, q > 1, and…”

Section: Rbfnns and Preliminariesmentioning

confidence: 99%