Invariance Principle and the Asymptotic Behavior of T-S Fuzzy Systems
DOI:
https://doi.org/10.5540/03.2023.010.01.0063Palabras clave:
T-S Fuzzy systems, Extended LaSalle Principle, Linear Matrix InequalityResumen
In this paper, the asymptotic behavior of nonlinear systems is studied by means of a T-S fuzzy system, which exactly represents the nonlinear system in question, and the extended Invariance Principle. An important feature of the proposed approach is the exhibition of conditions to estimate the attracting invariant set in terms of LMIs.
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Luís Fernando Costa Alberto. “O Princípio de Invariância de LaSalle estendido aplicado ao estudo de coerência de geradores e à análise de estabilidade transitória multi-’swing’.” PhD thesis. São Carlos: Universidade de São Paulo, Apr. 2000. doi: 10.11606/T.18.2000.tde- 01102001-175455.
Anna V. Blumel, Antonios Tsourdos, and Brian A. White. “Flight Control Design For A STT Missile: A Fuzzy LPV Approach”. In: IFAC Proceedings Volumes 34.15 (Sept.2001), pp. 455–460. issn: 14746670. doi: 10.1016/S1474-6670(17)40769-5.
Flávio A. Faria, Geraldo N. Silva, and Vilma A. Oliveira. “Reducing the conservatism of LMI-based stabilisation conditions for TS fuzzy systems using fuzzy Lyapunov functions”. In: International Journal of Systems Science 44.10 (2013), pp. 1956–1969. issn: 00207721. doi: 10.1080/00207721.2012.670307.
Flávio A. Faria, Michele C. Valentino, and Vilma A. Oliveira. “A fuzzy Lyapunov function approach for stabilization and H control of switched TS fuzzy systems”. In: Applied Mathematical Modelling 38.19-20 (2014), pp. 4817–4834. issn: 0307904X. doi: 10.1016/j.apm.2014.03.034.
Xiaorong Huang et al. “A survey on the application of fuzzy systems for underactuated systems”. In: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 233.3 (Mar. 2019), pp. 217–244. issn: 0959-6518. doi: 10.1177/0959651818791027.
Javad Mohammadpour and Carsten W. Schrer. Control of Linear Parameter Varying Systems with Applications. Ed. by Javad Mohammadpour and Carsten W. Scherer. Boston, MA: Springer US, 2012. isbn: 978-1-4614-1832-0. doi: 10.1007/978-1-4614-1833-7.
Damiano Rotondo et al. “Automated generation and comparison of Takagi-Sugeno and polytopic quasi-LPV models”. In: Fuzzy Sets and Systems 277 (2015), pp. 44–64. issn: 01650114. doi: 10.1016/j.fss.2015.02.002.
Kazuo Tanaka and Hua O. Wang. Fuzzy Control Systems Design and Analysis. 2001. isbn: 0471323241. doi: 10.1002/0471224596.
Tadanari Taniguchi et al. “Model construction, rule reduction, and robust compensation for generalized form of Takagi-Sugeno fuzzy systems”. In: IEEE Transactions on Fuzzy Systems 9.4 (2001), pp. 525–538. issn: 10636706. doi: 10.1109/91.940966.
Shun-Hung Tsai and Yu-Wen Chen. “A novel identification method for Takagi–Sugeno fuzzy model”. In: Fuzzy Sets and Systems 338 (May 2018), pp. 117–135. issn: 01650114. doi: 10.1016/j.fss.2017.10.012.
A. Tsourdos et al. “Control design for a mobile robot: a fuzzy LPV approach”. In: Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003. IEEE, 2003, pp. 552–557. isbn: 0-7803-7729-X. doi: 10.1109/CCA.2003.1223496.
Michele C. Valentino et al. “Ultimate boundedness sufficient conditions for nonlinear systems using TS fuzzy modelling”. In: Fuzzy Sets and Systems 361 (2019), pp. 88–100. issn: 01650114. doi: 10.1016/j.fss.2018.03.010.
