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The T\u2010S fuzzy model represents the discrete\u2010time nonlinear system in the form of the discrete uncertain time\u2010varying delay state space, which is firstly constructed by a set of local linear models and the nonlinear membership functions. The novel improved state space model can be further obtained by extending the output tracking error to the constructed model. Then the fuzzy predictive fault\u2010tolerant control law based on this extended model is designed, which can increase more control degrees of freedom. Utilizing Lyapunov\u2010Krasovskill theory, less conservative delay\u2010range\u2010dependent stable conditions in terms of linear matrix inequality (LMI) constraints are given to ensure the asymptotically robust stability of closed\u2010loop system. Meanwhile, the optimized cost function and H\u2010infinity performance index are introduced to the stable conditions to guarantee the robust performance and antidisturbance capability. The simulation results on the temperature control of a strong nonlinear continuous stirred tank reactor (CSTR) show that the proposed control scheme is feasible and effective.<\/jats:p>","DOI":"10.1155\/2019\/2031312","type":"journal-article","created":{"date-parts":[[2019,8,25]],"date-time":"2019-08-25T23:30:37Z","timestamp":1566775837000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Fuzzy Predictive Fault\u2010Tolerant Control for Time\u2010Delay Nonlinear Systems with Partial Actuator 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