An Adaptive Sliding Mode Control with I-term Using Recurrent Neural Identifier
نویسندگان
چکیده
The paper proposed a new adaptive control system containing a Recurrent Neural Network (RNN) identifier, a Sliding Mode Controller (SMC), and an I-term controller. The SMC is derived defining the sliding surface with respect to the output tracking error and using a nonlinear plant identification, and state estimation RNN, which gives all the necessary state and parameter information to resolve the SMC. Furthermore, the adaptive abilities of the RNN permit the SMC to maintain the sliding regime when the plant parameters changed. So to compensate constant process disturbances, an I-term controller is used. Comparative simulation results obtained with a fed-batch fermentation plant model confirmed the good quality of the proposed control scheme.
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