Research On The Design Of Neural Network PID Control System And Parameter Optimization With The Algorithm Of PSO

The technique of PID control is very general, and it is applied in many fields at present. In the paper, neural network theory foundation, studying algorithm of the neural network and traditional PID controller are introduced, and traditional PID controller weak point is analyzed in controlling the complicated, dynamic and uncertain system. In order to achieve the goal of improving traditional PID controller, five kind improvement ways are put forward in the paper——fuzzy PID controller, expert PID controller, grey PID controller, hereditary algorithm PID controller and neural network PID controller.Because of the strong nonlinearity to shine upon ability, study adaptive capacity, associative memory ability, processing method of proceed information and fine fault-tolerant performance, there are better control results to the complicated system in industrial control, and the unstable control results caused by the change of system structure or parameters have been improved after the PID controller improved by neural network. Single neural network PID controller and BP neural network PID controller have been study chiefly in the paper. Because there are some difficult in choosing the first power value of the BP neural network, PSO algorithm has been used to improve BP neural network controller in the paper. In the paper, PSO algorithm has been used to improve traditional PID controller.Lastly, the traditional PID controller was simulated, and I found that the system which parameters improved by PSO algorithm was better than the parameters improved by Z-N algorithm. I also found that the system of PSO BP-PID simulation result was better than the single neural adaptive system.