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Sliding-Mode Control With Soft Computing: A Survey
Abstract
Sliding-mode control (SMC) has been studied extensively for over 50 years and widely used in practical applications due to its simplicity and robustness against parameter variations and disturbances. Despite the extensive research activities carried out, the key technical problems associated with SMC remain as challenging research questions due to demands for new industrial applications and technological advances. In this respect, soft computing (SC) is a rather recent development in intelligent systems which has provided alternative means for adaptive learning and control to overcome the key SMC technical problems. Substantial efforts in integration of SMC with SC have been placed in recent years with various successes. In this paper, we provide the state of the art of recent developments in SMC systems with SC, examining key technical research issues and future perspectives.
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No free lunch theorems for optimization
Wolpert, D. H., & Macready, W. G. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585893 · Cited by 14,237
Cited by
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Kim, H., Son, J., & Lee, J. (2011) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2010.2098357 · Cited by 733
The 2017 IEEE International Conference on Fuzzy Systems
(2016) · IEEE Computational Intelligence Magazine · doi:10.1109/mci.2016.2545826 · Cited by 308
Wai, R.-J., & Muthusamy, R. (2013) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2012.2228230 · Cited by 188
Zou, Q. (2022) · Asian Journal of Control · doi:10.1002/asjc.2638 · Cited by 21
Metadata
- Authors
- Yu, X., & Kaynak, O.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2009-09
- Volume
- 56
- Issue
- 9
- Pages
- 3275-3285
- ISSN
- 0278-0046 (ISSN-L)
- OpenAlex
- W2099489172
- Cited by
- 531
- References
- 1
- FWCI
- 52.94
- Type
- journal article
- Language
- en
- Open access
- closed
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