A multivariable on-line adaptive PID controller using auto-tuning neurons

In this paper, we present a new PID control technique based on auto-tuning neurons for multivariable systems. The main difference between an auto-tuning neuron and a general neuron is that there are adjustable parameters of the activation function used in an auto-tuning neuron. In this paper, a modified hyperbolic tangent function is used as the activation function of an auto-tuning neuron, which provides two adjustable parameters to flexibly determine the magnitude and the shape of function. We then use such auto-tuning neurons to find gains of the multivariable PID controller, which is tuned on-line according to certain adaptation laws. Finally, two illustrative examples will be used to compare the performance by using our proposed method and other methods. (C) 2003 Elsevier Science Ltd. All rights reserved.