Adaptive nonlinear control of continuously stirred tank reactor systems

Adaptive nonlinear control is investigated for a class of continuously stirred tank reactor (CSTR) system. The CSTR plant under study belongs to a class of general 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. Both stability and control performance analysis of the closed-loop adaptive system are based on Lyapunov's stability techniques.

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