基于自适应模糊滑模控制的机器人轨迹跟踪算法

发布时间：2018-05-18 07:15

本文选题：自适应滑模控制 + 移动机器人　；参考：《电子测量与仪器学报》2017年05期

【摘要】：针对控制参数的不确定性以及存在未知外部扰动情况下移动机器人的轨迹跟踪问题,提出一种基于光滑非线性饱和函数的自适应模糊滑模轨迹跟踪控制算法。通过建立不确定非线性移动机器人运动控制模型,利用自适应模糊逻辑系统构建自适应模糊滑模控制器。为了增强轨迹跟踪控制算法对随机不确定外部扰动适应能力的同时削弱滑模控制算法中的输入抖振现象,利用有界输入有界输出(BIBO)稳定的方法,通过带有自适应调节算法的模糊系统对滑模控制律中非线性函数项进行自适应逼近,并设计了模糊系统中可调参数的自适应控制律,保证了控制系统的稳定与收敛。实验结果表明,所设计的控制器对系统参数不确定性和外界扰动均具有较强的轨迹跟踪性能和鲁棒性。与传统的滑模控制算法相比,该算法不仅能有效减小输入抖振而且轨迹跟踪控制精度提高了18.89%。
[Abstract]:In view of the uncertainty of the control parameters and the trajectory tracking problem of the mobile robot in the presence of unknown external disturbances, an adaptive fuzzy sliding mode tracking control algorithm based on the smooth nonlinear saturation function is proposed. The adaptive fuzzy logic system is used to establish an uncertain nonlinear mobile robot movement control model. The adaptive fuzzy sliding mode controller is constructed. In order to enhance the adaptability of the trajectory tracking control algorithm to the random uncertain external disturbance, the input buffeting phenomenon in the sliding mode control algorithm is weakened while the bounded input bounded output (BIBO) stability method is used, and the sliding mode control law is used in the sliding mode control law by the fuzzy system with the adaptive adjustment algorithm. The nonlinear function term is adaptive approximation, and the adaptive control law of the adjustable parameters in the fuzzy system is designed to ensure the stability and convergence of the control system. The experimental results show that the designed controller has strong trajectory tracking performance and robustness for both the system parameter uncertainty and the external disturbance. Compared with the algorithm, the algorithm can not only effectively reduce the input chattering, but also improve the tracking accuracy by 18.89%.
【作者单位】：榆林学院现代设计与先进制造技术研究中心;
【基金】：国家自然科学基金(10872160) 榆林学院高层次人才科研启动基金(12GK43)资助项目
【分类号】：TP242;TP273

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