Nonlinear internal model control based on online support vector machine

To improve the robustness and anti-interference of traditional inverse control,the system process is modeled and an inverse model controller using support vector machine regression(OSVMR) is designed.First,the OSVMR principle is briefly introduced.Second,the OSVMR is applied to the internal model control(IMC) problem,and the OSVMR internal model is developed. Third,an OSVMR controller for internal model control problem is proposed under the inverse condition of control process.Finally,the control algorithm is applied to the reversible nonlinear system and greenhouse environment with unknown disturbance,and compared with neural networks IMC using simulation,and the results show that the OSVMR IMC has a simplified model and good control performance.