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IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Fuzzy Systems
Non-fragile control of uncertain Markovian jumping linear systems subject to actuator saturation
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T-S fuzzy controllers for a class of nonlinear systems with uncertainties and input delay
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FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
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FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
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Robust fuzzy controller design for nonlinear multiple time-delay systems by dithers
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Automatica (Journal of IFAC)
Robust anti-windup controller design of time-delay fuzzy systems with actuator saturations
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Controller design for Markov jumping systems subject to actuator saturation
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Neurocomputing
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Takagi-Sugeno (TS) fuzzy models can provide an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear input-output submodels. In this paper, the TS fuzzy modeling approach is utilized to carry out the stability analysis and control design for nonlinear systems with actuator saturation. The TS fuzzy representation of a nonlinear system subject to actuator saturation is presented. In our TS fuzzy representation, the modeling error is also captured by norm-bounded uncertainties. A set invariance condition for the system in the TS fuzzy representation is first established. Based on this set invariance condition, the problem of estimating the domain of attraction of a TS fuzzy system under a constant state feedback law is formulated and solved as a linear matrix inequality (LMI) optimization problem. By viewing the state feedback gain as an extra free parameter in the LMI optimization problem, we arrive at a method for designing state feedback gain that maximizes the domain of attraction. A fuzzy scheduling control design method is also introduced to further enlarge the domain of attraction. An inverted pendulum is used to show the effectiveness of the proposed fuzzy controller.