Single Neuron PID Controller Based on Quadratic Optimization and its Application on pH Process Control

Aiming at strongly nonlinear process such as pH process, single neuron PID learning algorithm based on quadratic optimization is proposed. This algorithm does not need to conside the problem of subsection compartmentalization for common PID. The controller based on the algorithm mentioned above solves the problem of bad static state performance for common single neuron PID controller. Simulation control results of a strong nonlinear pH process show that this method has better adaptation and anti-disturbance ability than the general algorithm.