The PID Control Algorithm based on Whale Optimization Algorithm Optimized BP Neural Network

Aiming at the non-linear and time-varying problems existing in the traditional PID control system, a new PID control method based on the whale algorithm to optimize the BP neural network is proposed. The algorithm utilizes the characteristics of the whale optimization algorithm, such as simple operation, few parameters to adjust, and strong ability to jump out of local optimum, continuously adjusts and optimizes the weights of the BP neural network, and adjusts the parameters of the PID control algorithm in real time, avoiding the problem of easily falling into local minimum values during the learning process of the PID control algorithm of the BP neural network, and improving system performance. The simulation shows that compared with the control algorithm based on particle swarm BP neural network PID and other control algorithms, the algorithm in this paper has fast response speed, good stability, small overshoot, higher control precision and control stability.