The Research Of The Intelligent Composite Control Policy For Lag System And Non-Minimum Phase System

With the development of modern science and technology, intelligent control theory is used more widely than ever before. It has become one of the indispensable tools in industry control field and much attention has been paid to it increasingly. For non-minimum phase system with time delay, the overshoot and undershoot phenomena often occur because of the right-half plane zeros and poles. It is a difficult task to cancel the characteristics by using traditional linear control techniques. How to bring advantages of different control strategy into full play and to improve the performance is focused in this paper. It is also the essence of the intelligent composite control. Based on the predecessor's researches on time lag system and non-minimum phase system, two systems are regarded as a whole system and studied as follows: ⑴ In this paper, the "Intelligent composite control" is defined after analyzing many intelligent control theories and systems. The paper also refers several fuzzy PID intelligent composite control algorithms that are applicable to non-minimum phase system with time delay. On one hand, fuzzy control is used to improve the dynamic characteristics. On the other hand, PID control is used to ensure the steady-state accuracy. ⑵ Smith estimator is a conventional method to solve large delay process, and its main disadvantage is too sensitive for parameter variation. A simplified method of non-minimum phase system with time delay is put forward. The relations between robustness of the controlled system and other performances are analyzed. theory can effectively improve the robustness. According to the unstable non-minimum phase system with time delay, a modified Smith estimator is introduced, and the experiential formulas are brought up to tune the control parameter. ⑶ The genetic algorithms are used to optimize design of non-minimum phase system with time delay, the intelligent composite control scheme can effectively eliminate the overshoot and undershoot phenomena. In order to guarantee the smooth conversion of the control modes, the fuzzy inference and optimization are imported. ⑷ According to the multivariable non-minimum phase system with time delay, the conditions of system decoupling and the points for attention are put forward. ⑸ All of the Intelligent control strategies developed in this paper have been simulated by many non-minimum phase system with time delay, such as helicopter pitching control, the process of chemical polymerization and the adjusting speed system of hydraulic. The results demonstrate that the control algorithms are clear and simple, and the control performance satisfies the requirement. All of the above fully show the advantages of these composite control strategies and their favorable foreground in practice.