The Research Of Modified Algorithm About Predictive Function Control

As a new generation of Predictive Control algorithm, Predictive Function Control has received most wide concern and much more application in industry process control have applied. PFC has illustrated many advantages in process control, such as simple computing, strong rejection of disturbance, perfect asymptotic tracking and small control error, etc. As use the traditional PFC control algorithm, the dynamic response can not be tuned to track a predefined curve, additionally, use the PFC method to study the periodic process control, may receive good results and there also have some problems.This thesis has based on the above two points, does a deep research about the problems on both points, and have done some improvement to the PFC control algorithm, presents some renovation points after summarizing a lot of previous research reports in this field.The main contents and renovation points in this thesis are as follows:1. Reviewed the Predictive Function Control theory's development and summarized the status of this algorithm's research both at home and abroad. Have introduced its basic principle and the application in industry process control. And also developed the simulation of Predictive Function Control stick to its control performance in each control occasions.2. The exponential reference trajectory algorithm used in traditional predictive function control result in the fact that the dynamic response can not be tuned to track a predefined curve. A new reference trajectory self-tuning scheme for predictive function control is presented in this paper. The damp parameter of reference trajectory is on-line optimal tuned by comparing current reference trajectory with a predefined trajectory, which guaranteed the dynamic can reachthe setpoint at expectative time and follow the expectative response. The simulation shows that the proposed method can result favourable dynamic performances and good robustness.3. There has a big steady state error between the system's steady state response and expected value when use traditional Predictive Function Control method. To solve this problem, have introduced Repetitive Control into PFC method and did some modification to the PFC method. Result shows that it made a big improvement in response's quickness and rejection of disturbance, and achieves perfect asymptotic tracking/rejection in periodic process control. The simulation shows that the proposed method can result favourable performances and usefulness.4. In standard Repetitive Predictive Function Control (RPFC), there exist a potential instability of control system because of the period mismatch. Based on the analysis of the robustness of RPFC, have used Iterative Learning Method to deal with periodic process. Simulation examples were given to illustrate that the proposed method has good effectiveness and robustness.