A new sliding-mode control with fuzzy boundary layer. (English) Zbl 0988.93045

Fuzzy rules, which reduce the number of fuzzy inputs, are introduced to regulate the design parameters and increase operating performance. A sliding-mode controller based on fuzzy variable boundary layer with a control gain and boundary layer thickness as design parameters is developed. The control gain is an important factor affecting the control performance of variable structure system (VSS). Sliding-mode controllers based on a variable boundary layer are superior to the fixed-layer method for tracking. In order to regulate the design parameters and increase operating efficiency, the proposed methodologies make use of fuzzy inference, which reduces the number of fuzzy inputs. By using fuzzy algorithms in choosing a control gain and boundary layer, methods with better tracking performance than the conventional method are proposed. Finally, the results of a simulation are given to demonstrate the validity of this algorithm.


93C42 Fuzzy control/observation systems
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[1] Burton, J.A.; Zinober, A.S.I., Continuous self-adaptive control using a smoothed variable structure controller, Int. J. systems sci., 19, 1515-1528, (1988) · Zbl 0663.93043
[2] Decarlo, R.A., Variable structure system with sliding modes, IEEE trans. automat. control, AC-22, 212-222, (1977)
[3] Decarlo, R.A.; Zak, S.H.; Matthews, G.P., Variable structure control of nonlinear multivariable systemsa tutorial, Proc. IEEE, 76, 212-232, (1988)
[4] Gao, W.; Hung, J.C., Variable structure control of nonlinear systemsa new approach, IEEE trans. ind. electron., 40, 45-55, (1993)
[5] M.B. Ghalia, A.T. Alouani, Sliding mode control synthesis using fuzzy logic, Proceedings of the American Control Conference, Seattle, Washington, 1995, pp. 1528-1532.
[6] Hung, J.Y.; Gao, W.; Gao, J.C., Variable structure control: a survey, IEEE trans. ind. electron., 40, 2-22, (1993)
[7] Hwang, Y.R.; Tomizuka, M., Fuzzy smoothing algorithms for variable structure systems, IEEE trans. fuzzy systems, 4, 277-285, (1994)
[8] Ishigame, A.; Furukawa, T.; Kawamoto, S., Sliding mode controller design based on fuzzy inference for nonlinear systems, IEEE trans. ind. electron., 40, 64-70, (1993)
[9] S. Kawaji, N. Matsunaga, Fuzzy control of VSS type and its robustness, Proceedings of the IFSA World Congress, Brussels, 1991, pp. 81-84. · Zbl 0844.93049
[10] Mamdani, E.H., Applications of fuzzy algorithms for control of simple dynamic plant, Proc. IEE, 121, 1585-1588, (1974)
[11] R. Palm, Sliding mode fuzzy control, Proceedings of the IEEE International Conference on Fuzzy Systems, San Diego, 1992, pp. 519-526.
[12] Slotine, J.J., The robust control of robot manipulators, Internat. J. robotics res., 4, 49-64, (1985)
[13] Slotine, J.J.; Li, W., Applied nonlinear control, (1991), Prentice-Hall Englewood Cliffs, NJ
[14] Su, W.C.; Drakunov, S.Y.; Ozguner, U., Constructing discontinuity surfaces for variable structure systemsa lyaupunov approach, Automatica, 32, 925-928, (1996) · Zbl 0854.93020
[15] Wang, J.D.; Lee, T.L.; Juang, Y.T., New methods to design an integral variable structure controller, IEEE trans. automat. control, 41, 140-143, (1996) · Zbl 0842.93012
[16] Zadeh, L.A., Fuzzy sets, Inform. control, 8, 338-353, (1965) · Zbl 0139.24606
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