Application Of Optimized Filter In Internal Model Control

Time-delay system is a problem in process control industrial, the internal model control (IMC) has been widely used in time-delay systems control because of its good robustness and control performance. In this paper, industrial process of time-delay system is used as the research object, the current IMC method is applied to the main control means, for the filter of IMC design, analyzes its effect on control system performance. Filter design is crucial for the improvement of the robustness of the system and closed-loop performance. Therefore, performance analysis of the system robustness and closed-loop performance analysis can be used to design the filter of the controller.This paper did in-depth research in the filter design of the IMC, analyzed the basic principles of the standard Butterworth filter, also the effect to the control properties of time and frequency domain characteristics, n the order,ωc the cut-off frequency, given improved Butterworth filter design methods which can improve control system performance, and from time domain. It also analyzed the control performance of the three adjustable parameters of improved Butterworth filter from frequency domain characteristics, which are:n the order,ωc cut-off frequency andθincluded-angle between radii of pole which next to the imaginary axis and the imaginary axis. For a 1st and 2nd order delay system, simulation experiment of the improved Butterworth filter control design was carried out.Secondly, we analyzed the impact of the control system of the filter adjustable parametersλ(as 1/ωc), and proposed a fuzzy self-tuning IMC using variable universe expansion factor of filter time constantλ. Offered a improve fuzzy control method of the variable universe expansion factor for the filter time constant, advanced the exponential expansion factor derived from the e index which can be useful for the works. In connection with the first order, second order delay process which is common in industrial process, when model matched, model mismatch and model uncertainty and disturbance cases, we did simulation experiments using, respectively, the standard fuzzy control, the improved variable universe fuzzy control and the power function variable universe expansion factor fuzzy control.Finally, the Kalman filter is introduced into the structure of IMC, when the model is uncertainty, remaining the system's random noise and measurement noise then build an IMC, the control system has strong robustness and fast, greatly improved the control system performance, it provides a method for the further optimization of the IMC design.