Research On Model Reference Adaptive Internal Model Control With Control Input Limitation

Model reference adaptive control can deal with the control problem of the uncertain plant which parameters change slowly. Internal model control(IMC) is successful in controlling the plant with large time delay. It has good robust performance, simple structure, only a few tuning parameters and is easy to design and tune. Fuzzy control is a simple and practical control method that had been developed in recent years. It has some adaptive ability for process parameter changes, but its steady-state accuracy is unsatisfactory. In this paper, based on the idea of model reference adaptive control and combining the fuzzy control method with the IMC method, we proposed the method of model reference adaptive fuzzy IMC. In this paper, we design the IMC controller using zero-pole cancellation method, and tune the controller filter parameter a according to the error e and its first difference A e and acquire the best combination between robust performance and the response speed. The error e is the difference between the reference model output and system output. At the same time, this paper summarized the experience on solving the problem of amplitude limitation of the controller output and proposed a method to predict system output by use of the model prediction with feedback correction. The on-line intelligence switch of controller output between the limited amplitude and IMC controller output is determined according to the state whether the system output and the predictive output are within the given error range. Thispaper integrated the advantage of fuzzy control, IMC and adaptive control, so the performance of the system is improved. The simulation results for typical industrial process model show the effectiveness of this method.