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Adaptive command filtered control for a class of nonlinear time delay systems with extreme learning machine
Abstract
In this paper, an extreme learning machine (ELM)‐based adaptive command filtered control method is investigated for a class of strict feedback nonlinear systems with unknown external disturbances and time delay. To begin with, the original system state equation is transformed into a new form on account of coordinate transformation. Subsequently, an ELM is adopted to approximate unknown functions which exist in the whole system states, without any prior knowledges of the ideal weight vectors and approximation errors. Secondly, a command filter is developed for the system under consideration, which can avoid the probem of “explosion of complexity” caused by repeated derivation of virtual control signals in traditional backstepping control. Meanwhile, error compensation signals are designed to conquer the shortcoming of a dynamic surface control (DSC) method. The combination of ELM and command filter technique has been used to construct corresponding controllers and adaptive laws. Effective handling of the impact of time delay terms is ensured through designing a novel Lyapunov–Krasovskii functional. The proposed strategy guarantees boundedness of all signals in the closed‐loop system and the tracking error asymptotically converges to a compact set around the origin. In the end, two continuous stirred tank reactors (CSTRs) are taken as example to further verify the efficiency of the put forward control method.
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Cites
Higher-order sliding modes, differentiation and output-feedback control
Levant, A. (2003) · International Journal of Control · doi:10.1080/0020717031000099029 · Cited by 3,975
Dynamic surface control for a class of nonlinear systems
Swaroop, D., Hedrick, J. K., Yip, P. P., & Gerdes, J. C. (2000) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2000.880994 · Cited by 2,454
Optimization method based extreme learning machine for classification
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Command Filtered Adaptive Backstepping
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Adaptive neural network control of nonlinear systems with unknown time delays
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Cited by
Dutta, D., Biswas, P. K., Debnath, S., & Ahmad, F. (2024) · IEEE Access · doi:10.1109/access.2024.3523205 · Cited by 46
Metadata
- Authors
- Zhu, J., & Li, S.
- Affiliations
- Beijing University of Posts and Telecommunications (CN)
- Corresponding author
- Li, Shurong
- Venue
- Asian Journal of Control
- Publisher
- Wiley
- Published
- 2024-05-16
- Volume
- 27
- Issue
- 1
- Pages
- 215-229
- ISSN
- 1561-8625 (ISSN-L)
- 1934-6093
- OpenAlex
- W4396962305
- Cited by
- 1
- References
- 50
- Citations by year
- 2024: 1
- FWCI
- 0.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Asian Journal of Control (publishedVersion)
- Funders
- National Natural Science Foundation of China (61973043)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
- Keywords
- extreme learning machine, nonlinear time-delay systems, strict-feedback systems, unknown external disturbances, explosion of complexity, backstepping control, dynamic surface control, Lyapunov-Krasovskii functional, coordinate transformation, continuous stirred tank reactor, tracking error convergence
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