The Application of RBF-NN with Improvements in Clustering Algorithm Based on Ant Colony Optimization in PID Control

The PID control of RBF-NN is taken for the nonlinear system. Due to the low quality of clustering in the clustering algorithm of the traditional RBF-NN, the rate of convergence is directly influenced by the initial value. In this paper, the quality of the clustering has been raised and the initial value has been optimized through the improvements of the clustering algorithm by taking the K-means-algorithm and the Ant Colony Optimization (ACO). The simulation results show that the rate of convergence is precise and fast after the clustering algorithm is improved and the PID control is better than the one without taking the new method.