基于粒子群算法的LQR直線二級(jí)倒立擺的控制研究
[Abstract]:Inverted pendulum system is a typical representative of unstable underdriven system because of its nonlinear, high order, multivariable, strong coupling and so on. Inverted pendulum system can represent the basic model of control objects in various application fields abstractly, and can be used as an ideal multi-intelligent control theory to verify control application platform, so as to realize inverted pendulum system in the field of aerospace. The research on stability control of inverted pendulum is very important because of its wide application in the field of intelligent machine. In this paper, the control system of linear two-stage inverted pendulum is taken as the research object. Firstly, the physical mechanism of the straight-line two-stage inverted pendulum is analyzed and the mathematical model is established, and then the linear analysis of the mathematical model of the straight-line two-stage inverted pendulum is carried out. The linear state space expression of the system is obtained. Secondly, the control simulation experiment of PID controller and LQR controller to realize linear two-stage inverted pendulum is compared and analyzed. The results show that the number of controllers realized by PID is large and the control effect is poor. However, the accuracy of linear two-stage inverted pendulum control realized by LQR controller is better than that of PID control, but the parameter selection process of LQR controller is empirical, and the number of optimized parameters is small, resulting in low control accuracy. Finally, aiming at the parameter selection of LQR controller, particle swarm optimization algorithm is used to optimize the parameters of LQR controller, and a LQR control is used to realize the displacement of trolley, the speed of trolley, the angle and angular velocity of swinging rod 1. The parameters of swing rod 2 angle and angular velocity are optimized. It is verified on the experimental equipment platform that the LQR controller optimized by particle swarm optimization improves the stability and accuracy of the linear two-stage inverted pendulum control, realizes the self-recovery state of the swinging rod after deviating from equilibrium, and maintains it in a balanced and stable state. The experimental results show that the particle swarm optimization algorithm realizes the optimization of LQR linear two-stage inverted pendulum control system, which is of great theoretical significance to improve the stability of linear two-stage inverted pendulum control system. It lays a theoretical foundation for the practical application of inverted pendulum system and has certain application value.
【學(xué)位授予單位】:西安科技大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TH112
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