Based Fuzzy Control Of The Rotary Inverted Pendulum Control Algorithm Research

The inverted pendulum is a classical control problem of balancing stick vertically on a linear track cart. Inverted pendulum system is a typically rapid, multi-variable ,nonlinear absolutely insiability system ,and it is the favorite problem in the control theory and test the modern control theory ,and also it is control technique and idea is useful to average industrial process.The studies on the inverted pendulum have significant theory and practical values. They can show many abstract concepts, such as the stability, the controllability, the convergent speed and the ability of the anti-disturbance. Because inverted pendulum is a typical system, which is fleet, multi-variable, non-linear, and absolutely instable. It becomes the research object of many researchers. They continually excavate many new methods, and apply them to various high-tech fields, such as aviation and the robots. Because the characteristic of the inverted pendulum is similar to the characteristic of the rockets and the robots, the researches on it have theory and practical significance. Above all, the inverted pendulum has become the experimental system, on which we can learn and validate various control theories.Linear and fuzzy control theory is required to keep the system stable in the paper .After concisely introducing the development and current situation of inverte pendulum system research ,The analytic model of single inverted pendulum is derived .Subsequently .different control algorithms are designed based modern control theries, In this paper, we put the methods of the pole configuration and the optimal control to control the linear inverted pendulum, and have a deep research work on these two theories. We have the work on linearization of the dynamic equation of the inverted pendulum system near the working position, and achieve the linear equation. Good simulation results are got by MATLAB by using pole configuration and optimal control simulation, and we summarize some experience parameters. At last, we compare the results of these two control methods. As the controlled objects become more and more complex and the requirement of control...