An Improved Adaptive Neural Network Method for Control System

Classical methods for designing a controller depend on the accuracy of system model. However, plant´s models and other parts in a physical system can not accurately represent all possible dynamics. Thus the controller designed is usually not the optimal one. In this article, a new, simple adaptive control method, which combines the classical frequency domain method with the neural network theory, is proposed. Firstly, we can obtain a controller using classical method. Secondly we use the coefficients in digitized controller equation as the initial values of an Adaline network. Finally, LMS learning rules is used to adjust the weights adaptively. Experimental results show that this method is very effective in improving the performance of conventional controller