Research On Intelligent Internal Model Control For Non-minimum Phase System With Time Delay

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. Based on some people's researches on time-delayed system and non-minimum phase system, two kinds of systems are considered as a whole and studied by the author. 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. 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 eliminate the phenomena 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. Firstly, the influences of the feedforward filter structure and its parameter are discussed in detail. Aiming to decrease overshoot, undershoot and settling time of non-minimum phase system with time delay, this paper proposes an intelligent IMC control system based on fuzzy inference. In this paper, we design the IMC controller using zero-pole cancellation method, and tune the feedforward filter parameter and the gain parameter K using fuzzy inference method. The simulation results show that both of methods oftuning and K are effective. They all can acquire the reasonable trade-offs between the response speed and decreasing overshoot and overshoot. At the same time, both of methods improve the robustness of control systems.