An improved single neuron self-adaptive PID control scheme of superheated steam temperature control system

Abstract

The control unit of superheated steam temperature of thermal power plants has poor quality, and easy over-temperature problem. In this paper, according to the single neuron adaptive controller with self-learning, strong adaptability, high robustness and fast response, an improved single neuron self-adaptive proportional-integral-derivative (PID) control scheme of superheated steam temperature control system has been presented. The proposed control scheme has two main characteristics: 1) Compared with the traditional PID control scheme, the three PID control parameters of proportional, integral, differential coefficients become a neuron adaptive control coefficient K; 2) This proposed control strategy has provided a new theoretical basis and research methods in the application of control system of superheated steam temperature. Simulation results show that the control scheme has improved the control performance of large time delay, multi-disturbance, and has reflected the strong robustness, high stability and good control quality.