Neural network PID decoupling control based on chaos particle swarm optimization

As a new kind of neural network model, Neural network PID (PIDNN) combines the advantages of PID and neural network. However, the error back propagation algorithm (BP) limits the performance of PIDNN. In order to realize effective control of nonlinear, large delay and strong coupling system, this paper proposes a neural network PID control method based on chaos particle swarm optimization. Using chaos particle swarm algorithm to replace the reverse pass algorithm of original PID neural network, adjusting the weights of PIDNN between each neuron, the algorithm achieved rapid decoupling control effect. The simulation results show that the proposed method in this paper, compared with the original BP algorithm, has more excellent dynamic and steady-state performance.