Remarks on Adaptive-Type Hypercomplex-Valued Neural Network-Based Feedforward Feedback Controller

Abstract

In this study, we investigate the control performance of an adaptive-type feedforward feedback controller using multilayer hypercomplex-valued neural network. The control system consists of a neural network and a feedback controller, whereby the control input of a plant is synthesised online by using the sum of the multilayer hypercomplex-valued neural network and the feedback controller to track the plant output to the desired output generated by a reference model. Computational experiments to control a multiple-input and multiple-output discrete-time nonlinear plant are conducted to evaluate the capability and characteristics of the hypercomplex-valued neural network-based feedforward feedback controller. Experimental results show the feasibility and effectiveness of the proposed controller.