Adaptive decentralized prescribed performance control for a class of large-scale nonlinear systems subject to nonsymmetric input saturations
This paper investigates an adaptive decentralized predefined performance control problem for a class of large-scale nonlinear systems with nonsymmetric input saturation by using multi-dimensional taylor network (MTN) approach. Firstly, the input saturation model is approximated by a smooth function...
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| Published in | Neural computing & applications Vol. 34; no. 13; pp. 11123 - 11140 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
London
Springer London
01.07.2022
Springer Nature B.V |
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| Abstract | This paper investigates an adaptive decentralized predefined performance control problem for a class of large-scale nonlinear systems with nonsymmetric input saturation by using multi-dimensional taylor network (MTN) approach. Firstly, the input saturation model is approximated by a smooth function with a bounded approximation error and unknown nonlinear functions are estimated by MTNs. Secondly, a decentralized tracking control algorithm is established by integrating the idea of prescribed performance control into backstepping recursive technique. Thirdly, by using the designed MTN-based adaptive decentralized controller, all the closed-loop signals are bounded and all the tracking errors satisfy the predefined transient and steady-state performance, respectively. Finally, the presented control method is effective by introducing three examples, and the simulation results verify that the correctness and reasonableness of the proposed control algorithm. |
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| AbstractList | This paper investigates an adaptive decentralized predefined performance control problem for a class of large-scale nonlinear systems with nonsymmetric input saturation by using multi-dimensional taylor network (MTN) approach. Firstly, the input saturation model is approximated by a smooth function with a bounded approximation error and unknown nonlinear functions are estimated by MTNs. Secondly, a decentralized tracking control algorithm is established by integrating the idea of prescribed performance control into backstepping recursive technique. Thirdly, by using the designed MTN-based adaptive decentralized controller, all the closed-loop signals are bounded and all the tracking errors satisfy the predefined transient and steady-state performance, respectively. Finally, the presented control method is effective by introducing three examples, and the simulation results verify that the correctness and reasonableness of the proposed control algorithm. |
| Author | Han, Yu-Qun Zhu, Shan-Liang |
| Author_xml | – sequence: 1 givenname: Shan-Liang surname: Zhu fullname: Zhu, Shan-Liang organization: School of Mathematics and Physics, Qingdao University of Science and Technology – sequence: 2 givenname: Yu-Qun orcidid: 0000-0002-9055-2954 surname: Han fullname: Han, Yu-Qun email: yuqunhan@qust.edu.cn organization: School of Mathematics and Physics, Qingdao University of Science and Technology |
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| Keywords | Multi-dimensional Taylor network Input saturation Prescribed performance Adaptive control Large-scale nonlinear systems |
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| SubjectTerms | Adaptive control Algorithms Approximation Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Control algorithms Control methods Control theory Controllers Data Mining and Knowledge Discovery Design Image Processing and Computer Vision Nonlinear systems Original Article Probability and Statistics in Computer Science Recursive methods Saturation Tracking control Tracking errors |
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| Title | Adaptive decentralized prescribed performance control for a class of large-scale nonlinear systems subject to nonsymmetric input saturations |
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