A Parallel Nonlinear Control System of Improved Generalized Predictive Control and Single Neuron PID Based on U-model

For a class of smooth nonlinear plants, an improved generalized predictive control (JGPC) and single neuron PID (SNPID) parallel control framework based on U-model is proposed. In this framework, firstly, the nonlinear plant is transformed into a U-model, and then the control law of the U-model is designed by using JGPC. According to the current error, SNPID is used to compensate the control effect of JGPC to improve the dynamic performance of system. At the same time, tracking differentiator can reduce overshoot and improve the anti-interference ability of the system. A simulated case study is conducted to illustrate effectiveness of the control framework.