An Improved Single Neuron Adaptive PID Control Algorithm

An improved single neuron Adaptive PID Control algorithm is presented in the paper. In the improved algorithm, a new objective function is presented which is the weighted squared sum of output error and controlling increment before k time. The recursive equations of the adaptive PID control algorithm based on the new objective function is derived using Newton iterative algorithm. The improved algorithm modifies the weight iteratively, and reduces the adjustable parameters number from three learning rate to one Newton search step. An adaptive strategy of the gain K is given. Simulation results show that the performance of the improved algorithm is better than that of the classic single neuron adaptive PID algorithm.