The Study Of Double Inverted Pendulum Control Algorithm

Inverted pendulum system is a typical. fast, multi-variable, unstable, strongly coupled system. Its research in the field of spacecraft attitude control, robotics, missile defense system, which are of great significance. This paper has studied the swing stability control of single inverted pendulum and two inverted pendulum. The main works in this paper are the following:1．Detailed analysis of the principles of the inverted pendulum control system, has been inverted pendulum approximation model and double inverted pendulum system, and then separately for inverted pendulum system and double inverted pendulum system for qualitative analysis,the two inverted pendulum systems are open-loop unstable, but in the vicinity of the equilibrium point is controllable, substantial, and double inverted pendulum control more difficult.2．Introduces the principle of PID control, and then design a PID controller in the Matlab environment for the inverted pendulum system to build a Simulink simulation platform, drawn by parameter tuning ideal simulation curve. Since the Matlab environment can achieve real-time control to the next machine, so on the basis of the simulation control interface to build a GUI, the interface to build a good future, to prepare the PID control algorithm S function, by calling the S function to realize the inverted pendulum real-time control systems. Problems during the experiment verified the PID control algorithm drawbacks.3．This article is then inverted to settle in the primary real-time control of the audience were fuzzy algorithm, written in VC environment fuzzy algorithm, by comparing real-time effects once again proven PID control algorithm drawbacks.4．Fuzzy control theory is briefly introduced. How to create a major double inverted pendulum fuzzy controller, the first integration of functions designed to reduce the dimension of its variables, and then describes how fuzzy, fuzzy reasoning and clarity, well after the fuzzy controller design in Matlab environment for build a Simulink simulation, and finally the simulation results are analyzed. Finally, the experimental platform in VC first example for double inverted pendulum control fuzzy control algorithm. After a lot of fuzzy rules after modification and adjustments on the field, the effect of the double inverted pendulum control is still not very stable, but the next in-depth study of the foundation. 5．Finally, this article lists the problems encountered in the learning process, and how to solve, and summarizes the results and shortcomings of this paper, and proposed future research directions and priorities.