Tong, Shaocheng; Tang, Jiantao; Wang, Tao Fuzzy adaptive control of multivariable nonlinear systems. (English) Zbl 0976.93049 Fuzzy Sets Syst. 111, No. 2, 153-167 (2000). The authors develop a robust fuzzy adaptive control scheme for a class of unknown nonlinear MIMO systems. The uncertainties are divided into two parts: A first type can be viewed as matched uncertainties, which are modeled by fuzzy systems and the design of fuzzy equivalence control. The second type can be treated as the unmatched uncertainties including modeling errors (fuzzy system approximation errors) and disturbances, etc., which cannot be modeled by fuzzy systems. Since the unmatched uncertainties may act as combined disturbance, it can lead to unstability of the closed-loop system, so a robust compensator is designed by the \(H^\infty\) control technique to reject this kind of uncertainties. The whole adaptive control scheme not only guarantees uniform ultimate boundedness, but also makes the worst case effect on the tracking error due to the unmatched uncertainties to be less than or equal to a desired attenuation level.Extensive simulations on the tracking control of a two-link rigid robotics manipulator verify the effectiveness of the proposed algorithms. Reviewer: George S.Stavrakakis (Chania) Cited in 33 Documents MSC: 93C42 Fuzzy control/observation systems 93C40 Adaptive control/observation systems 93B36 \(H^\infty\)-control 93C73 Perturbations in control/observation systems Keywords:robust fuzzy adaptive control; nonlinear MIMO systems; \(H^\infty\) control; uniform ultimate boundedness; tracking; unmatched uncertainties PDF BibTeX XML Cite \textit{S. Tong} et al., Fuzzy Sets Syst. 111, No. 2, 153--167 (2000; Zbl 0976.93049) Full Text: DOI OpenURL References: [1] Chen, B.S.; Lee, T.S.; Feng, J.h., A nonlinear \(H\^{}\{∞\}\) control design in robotics systems under parameter perturbation and external disturbance, Int. J. control, 59, 439-461, (1994) · Zbl 0807.93018 [2] Isodori, A., Nonlinear control systems, (1989), Springer New York [3] Kanellakopoulos, I.; Kokotovic, P.V.; Maritio, R., An extended direct scheme for robust adaptive nonlinear control, Automatica, 27, 247-255, (1991) · Zbl 0729.93046 [4] Kanellakopoulos, I.; Kokotovic, P.V.; Morse, A.S., Systematic design of adaptive controllers for feedback linearization systems, IEEE Trans. Automat. Control, 1991, (36) [5] Lee, C.C., Fuzzy logic in control systems: fuzzy logic controller – part 1.2, IEEE Trans. Systems Man Cybernet, 1990, (20) [6] R. Marino, P. Tomei, Global adaptive output feedback control of nonlinear systems, part 1: nonlinear parameterization, IEEE Trans. Automat. Control 38 (1993) 17-32. · Zbl 0783.93032 [7] R. Marino, P. Tomei, Global adaptive output feedback control of nonlinear systems, part 2: nonlinear parameterization, IEEE Trans. Automat. Control 38 (1993) 33-48. · Zbl 0799.93023 [8] Polycarpou, M.M.; Ioannou, P.A., A robust adaptive nonlinear control design, Automatica, 32, 423-427, (1996) · Zbl 0847.93031 [9] Sastry, S.; Isodri, A., Adaptive control of linearizable systems, IEEE trans. automat. control, 34, 1123-1131, (1989) · Zbl 0693.93046 [10] T.T. Spooner, K.M. Passino, Stable indirect adaptive control using fuzzy systems and neural networks, Proc. 34th Conf. on CDC, 1996, pp. 243-248. [11] Sue, C.Y.; Stepanenko, Y., Adaptive control for a class of nonlinear systems with fuzzy logic, Trans. fuzzy systems, 29, 285-294, (1994) [12] Taylor, D.G.; Kokotovik, P.V.; Marino, R.; Kanellakopoulos, I., Adaptive regulation of nonlinear systems with unmodeled dynamics, IEEE trans. automat. control, 34, 405-412, (1989) · Zbl 0671.93033 [13] Wang Li-Xin, Fuzzy systems are universal approximations, Proc. IEEE Int. Conf. on Fuzzy Systems, San Diego, 1992, 1163-1170. [14] Li-Xin, Wang, Stable adaptive fuzzy control of nonlinear systems, IEEE trans. fuzzy systems, 1, 146-155, (1993) This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.