倒立摆系统控制研究  

Research of Control Inverted Pendulum System

作　　者：辛静[1] 赵高晖[1] 李天箭[1] 杨培培[1] 

机构地区：[1]上海理工大学机械工程学院,上海200093

出　　处：《电子科技》2016年第12期159-161,共3页Electronic Science and Technology

基　　金：国家自然科学基金资助项目(51405300)

摘　　要：基于复杂的二阶非线性倒立摆系统的不确定性问题,提出了一种自适应该系统的控制方案。通过倒立摆系统的动态方程,利用RBF神经网络对未知函数的逼近,并结合自适应滑模控制算法,建立RBF自适应滑模控制器,谋求解决非线性不确定的倒立摆系统,对该系统进行Matlab仿真验证,并分别对RBF自适应PID控制、普通RBF自适应滑模算法和文中RBF自适应滑模算法进行仿真比较,仿真比较结果验证了该方案不仅具有可行性和有效性,且在时间上具有快速响应性和稳定性。Uncertainty problem of basing on complex two order nonlinear inverted pendulum system, this paper put forward a kind of controlling scheme that adapt above system. By means of dynamic equation of the inverted pen- dulum system, using RBF neural network to approximate the unknown function, combining with the adaptive sliding mode control algorithm, this paper build adaptive sliding mode controller and seek a solution to solve the uncertain nonlinear inverted pendulum system, then the system is simulate and verify by Matlab simulation. In the end, this paper simulate and compare the RBF adaptive PID control, the common RBF adaptive sliding mode algorithm and the RBF adaptive sliding mode algorithm. The result of simulation and comparison show that the control scheme not only has the feasibility, effectiveness, but also it is fast response and stablization in time.

关 键 词：倒立摆 动态方程 RBF神经网络 自适应滑模控制 MATLAB仿真 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]