串级模糊控制在多变量单级倒立摆中的应用
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摘要
针对单级倒立摆非线性、多变量等问题,该文研究了串级T-S模糊控制系统控制单级倒立摆的控制策略。建立了单级倒立摆的数学模型,对其进行位移和角度的解耦,建立双闭环串级模糊控制模型,其中内环控制单级倒立摆角度,外环控制单级倒立摆的位移。运用并行分配补偿法和极点配置相结合的方法设计串级模糊控制器,并运用自适应遗传算法鲁棒优化串级模糊控制器,实现串级模糊控制器的自动设计。最后,运用Matlab对拟建模型进行了仿真,实验结果证明了该文设计的遗传算法优化串模糊控制模型在多变量控制系统中的有效性。
For single inverted pendulum nonlinear,multivariable and other issues,the control strategy of cascade T-S fuzzy control system is studied. The mathematical model of single inverted pendulum is established,the displacement and angle of the inverted pendulum are decoupled,and the double closed-loop cascade fuzzy control model is established,In which the inner loop controls the angle of the single inverted pendulum,and the outer loop controls the displacement of the single inverted pendulum. By using the parallel distribution compensation(PDC) methodand pole assignment method,the cascade fuzzy controller is designed,and the improved genetic algorithm is used to optimize the cascade fuzzy controller in order to realize the automatic design of cascade fuzzy controller. Finally,the proposed model is simulated by Matlab,and the experimental results show that the genetic algorithm designed in this paper that is effective in the multivariable control system.
For single inverted pendulum nonlinear,multivariable and other issues,the control strategy of cascade T-S fuzzy control system is studied. The mathematical model of single inverted pendulum is established,the displacement and angle of the inverted pendulum are decoupled,and the double closed-loop cascade fuzzy control model is established,In which the inner loop controls the angle of the single inverted pendulum,and the outer loop controls the displacement of the single inverted pendulum. By using the parallel distribution compensation(PDC) methodand pole assignment method,the cascade fuzzy controller is designed,and the improved genetic algorithm is used to optimize the cascade fuzzy controller in order to realize the automatic design of cascade fuzzy controller. Finally,the proposed model is simulated by Matlab,and the experimental results show that the genetic algorithm designed in this paper that is effective in the multivariable control system.
引文
[1]安新雨,张涛.一级直线倒立摆串联模糊控制方法研究[J].科技信息,2013(10):50-51.
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[3]陈国洋.一类T-S模糊控制系统的稳定性分析及设计[D].上海:上海交通大学,2009.
[4]胡桂红.基于遗传算法的倒立摆控制策略研究[D].西安:西安电子科技大学,2008.
[5]侯涛,董海鹰.基于T-S模型的倒立摆双闭环串级模糊控制设计与仿真[J].系统仿真学报,2007,19(11):2477-2478.
[6]吕志.基于分类解耦模糊PID控制的倒立摆系统[J].江南大学学报:自然科学版,2015,14(2):141-144.
[2]黄彦海,张镭,张朋朋,等.单级倒立摆模糊控制研究[J].制造业自动化,2015,37(1):1-4.
[3]陈国洋.一类T-S模糊控制系统的稳定性分析及设计[D].上海:上海交通大学,2009.
[4]胡桂红.基于遗传算法的倒立摆控制策略研究[D].西安:西安电子科技大学,2008.
[5]侯涛,董海鹰.基于T-S模型的倒立摆双闭环串级模糊控制设计与仿真[J].系统仿真学报,2007,19(11):2477-2478.
[6]吕志.基于分类解耦模糊PID控制的倒立摆系统[J].江南大学学报:自然科学版,2015,14(2):141-144.