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Performance comparison between Adaptive Neuro-controller and Adaptive Parametric Black Box Controller

The performance comparison between two controllers, namely Adaptive Neuro-Controller (ANC), based on Multi Layered Perceptron (MLP) network and Adaptive Parametric Black Box Controller (APBBC) are presented in this paper. The comparison is based on the capability of the controlled output tracking the model reference output and the percentage of overshoot. Both controllers are based on a black box approach that offers simpler design approach. The Model Reference Adaptive System (MRAS) has been used to generate the desired output path and to ensure the output of the controlled system follows the output of the reference model. Recursive Least Square (WRLS) algorithm will be used to adjust the controller parameters to minimize the error between the plant output and the model reference output. The controllers have been tested using a linear plant and a nonlinear plant with several varying operating conditions. The simulation results show that output response of ANC have slightly better tracking performance compared to APBB controller for linear plant and have equivalent performance for nonlinear plant.