Abstract
A new type of PID control method based on improved back-propagation (BP) neural network is proposed to deal with the defects of steepest gradient descent in slowly converging and easily sticking into local minimum frequently. It has merits of both neural network and PID controller, and it is adjusted by Fletcher-Reeves conjugate gradient, which can make study speed of network faster and can eliminate the disadvantages of steepest gradient descent in BP algorithm. The parameters of neural network PID controller are adjusted on line by the improved conjugate gradient. The programming steps under MATLAB are finally described. Simulation results show that the controller is effective.
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