Based On Incomplete Derivative Single Neuron Adaptive Pid Controller Research And Applications

As the most age-old and powerful control mode, PID control always has had a great effect on the automatic control of the production process. But with the development of science and technology, the controlled system has become more and more complicated, and the requirements of effect have increased and PID can't adapt to the changed requirements. Thus there are some conflicts between the complexity and accuracy. Intelligent adaptive control is an effective method to solve this problem. Neural net has perfect selfadaptive and self-learning ability, so it can be regarded as an effective intelligent way for application. But there is also a existed contradiction between the parallel of Neural net and serial conduct way of computer which is hard to ensure the real time control. Neuron control is easy to calculate and ensure the real time control,and it is also self-adaptive.This paper aims to combine advantages of PID control and Neuron, propose the neuron PID controller which is derived from an incomplete derivative PID algorithm and based on six learning rules in common use, viz. no surpervized Hebbian learning rule,perceptron learning rule,supervized learning rule,improved Hebbian learing rule,Delta learning rule and capability index which is based on second type, and these rules come into being six control arithmatic. Then simulate in object with lag. The simulation turned out that Neuron incomplete derivative PID controller not only has the...