The Research On Neural Networks PID Controller And Simulation

The techologic of PID control is very general, there is extensive application in many fields at present. The paper further investigates the neural network PID controller. Have introduced the theoretical foundation of the neural network and studying algorithm of the neural network, traditional routine PID controller briefly at first, is it analyse to traditional PID controller to complicated, dynamic and uncertain system control for a lot of weak points to it to go on, in order to achieve the goal of improving traditional PID controller, five kinds of improvement ways of systematic proposition in the article (fuzzy PID controller, expert PID controller, grey PID controller, hereditary algorithm PID controller and neural network PID controller).The text has discussed the neural network PID controller mainly. Because the neural network has strong nonlinearity to shine upon ability, study adaptive capacity, associative memory ability, the information processing way run side by side by oneself and fine fault-tolerant performance, there are better control result to the complicated system in industrial control, improveing the structure of system effective and change of the parameter result in controlling the unstability of the result. The paper further investigate the neuron PID controller based on neural network, neural network PID controller of BP algorithm, and algorithm while using easy to put some snack very much into to BP, but also has learnt the chronic purpose to even reach study and proposed using the fuzzy algorithm, the hereditary algorithm carries on the improved association and optimizes the neural network PID controller to BP network. Finally, carried on simulation to traditional PID controller and neural network PID controller, simulation result indicate, use neural network go on after improving raising stupid getting wonderful and dynamic characteristicking of system to routine PID controller, the effective systematic control result of improvement, has achieved the anticipated goal.