| Predictive control is a kind of advanced control technologies that is based on the model of plants, so it is also called model predictive control. It is a novel computer control algorithm first appeared in industrial area in Europe and America in 1970s. French researcher-Richalet et al first proposed the conception, background, mechanism and performance of the model predictive heuristic control. Then the theory of model predictive control was further developed by Mehra, Culter and Clark et al. In 980s, model predictive control received extensive attention of the western researchers for its distinct merits and features and it has been deeply studied from different aspects with many mathematic methods, In the recent years, with the development of many kinds of the control theory, such as intelligent control, PID control, wavelet theory, robust control, and hybrid systems control etc., the theory of model predictive control has also obtained rapid development. Moreover, the theory researches and corresponding application reports of model predictive control also appeared in the field of the variable structure control, time-delay system control, hybrid system control, output feedback control and so on.Based on the study status of model predictive control and the new requirements from the practiceb industrial processes for the theory of model predictive control, some desiderated problems are studied and discussed in this article, also the corresponding results are given. The main contents are as follows:1. For a class of multivariable systems, the tuning of PID controller parameters is discussed in this paper. Based on the idea of GPC and the relation between y GPC and PID controllers, a new tuning algorithm of PID controller parameters for discrete multivariable systems is presented. Compared with the conventional PID control, the proposed predictive PID control not only has simple control structure as conventional PID, but also maintains performance of the advanced control algorithm such as generalized predictive control. Furthermore, when the matching conditions are satisfied, the proposed method can also be used for nonminimum-phase systems and time-delay systems.IV Abstract2. Considering the model predictive control algorithm based on the model of the plant, the accuracy of the model is closely connected with the control performance. As the actual plant is nonlinear, it is hard to obtain the accurate internal model. Furthermore, if the nonlinear model is considered for control design directly, it will reduce to nonlinear optimization, which can not satisfy the requirement of on-line control. In addition, the current research results on predictive PID control mainly focus on the linear systems and the results about the nonlinear predictive PID control. In this paper, a novel predictive PID control based on T-S fuzzy model is proposed, which can deal with a class of large-scale nonlinear systems. What's more, the stability of the closed-loop systems is also studied and some analytical conclusions are given.3. Based on the discussion and summarization for the merits and shortcomings of current predictive PID control theory, a new T-S fuzzy model predictive PID control is given based on the output-error predicted. A proper T-S fuzzy model is adopted to describe the complex nonlinear system. Based on the method of local linearization, the idea of generalized predictive control (GPC) and the definition of Finite Impulse Response are utilized to design the novel control strategy. The new method not only is different from the common predictive PID control, but also solves the problem that the system's order is restricted in the reported papers. So the presented method is fit for more common systems and PID tuning knobs on the industrial controller also can be used to adjust the performance of the closed-loop system. Furthermore, the compute burden is greatly reduced.4. Considering the fact that a class of la...
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