The Research Of LTR Control Method In Nonlinear System Based On Cubature Kalman Filter

Nonlinearity and noise are common phenomena in the actual chemical industrial process.Because of the complex nonlinear composition of the model and the presence of noise,the robustness and control performance of the system are affected seriously.Therefore,it has been a research hotspot in the field of control.LTR(Loop Transfer Recovery)is a control method that can be applied in both time domain and frequency domain.However,the existing studies on LTR control methods for nonlinear systems are relatively absent,especially the study of nonlinear systems with non-Gaussian noise.Therefore,it is of great theoretical value and practical significance to optimize the loop transfer recovery control method and apply LTR into more complex systems.A nonlinear two degree freedom LTR controller design method based on CKF and a corresponding control structure for nonlinear systems with complex non-Gaussian noise are presented in this paper.The traditional single degree freedom LTR controller based on output error can not satisfy the requirements of the control effect and robustness of the nonlinear system at the same time.Based on the research of the existing LQG/LTR control method,optimization of control structure of LQG/LTR is presented.First,the cubature kalman filter is used to replace the kalman filter in the traditional LTR controller structure,completing the design of the state observer through calculating the gain matrix of the cubature kalman filter,and make LTR controller can perform high-precision state observations in nonlinear systems.Secondly,LTR method is used to design two freedom degree controller systems on the basis of single degree freedom LQG/LTR control structure in this paper.The front control term is designed to expand the systems,which constructs the two freedom degree controller with state feedback controller together.Moreover,the controller and observer are designed by separation principle.The simulation results of the classical CSTR reactor model and the three water tank system show that the nonlinear LTR control method has satisfactory robust performance and good control performance.For nonlinear systems with non-Gaussian noise,the caubature Kalman filter is optimized by the principle of minimum entropy,so that the system can still work stably under non-Gaussian noise.At the same time,the state vector and the state space matrix are decomposed and augmented by LTR.The method is designed to be applied to a nonlinear control system with non-Gaussian noise and the probability density function is used to measure the performance of the system.Finally,simulation results show that the nonlinear LTR control method based on minimum entropy optimization has good disturbance recovery ability,strong output response capability,and excellent robustness.