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• W2074834202 abstract "Adaptive nonlinear control is investigated for continuously stirred tank reactor (CSTR) systems using neural networks. The CSTR plant under study belongs to a class of nonaffine nonlinear systems, and contains an unknown parameter that enters the model nonlinearly. Using adaptive backstepping and neural network (NN) approximation techniques, an alternative adaptive NN controller is developed that achieves asymptotic output tracking control. A novel integral-type Lyapunov function, which includes both system states and control input as its arguments, is constructed to solve the difficulty associated with the nonaffine control problem. Numerical simulation is performed to show the feasibility of the proposed approach for chemical process control." @default.
• W2074834202 created "2016-06-24" @default.
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• W2074834202 date "2005-01-01" @default.
• W2074834202 modified "2023-09-30" @default.
• W2074834202 title "Adaptive control of uncertain continuously stirred tank reactors with unknown actuator nonlinearities" @default.
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• W2074834202 doi "https://doi.org/10.1016/s0019-0578(07)60045-7" @default.
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