基于扰动观测器的机械臂自适应反演滑模控制
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摘要
机械臂的动力学模型通常包含一定的结构不确定性,并受到外界未知干扰的影响;针对现有模型的不确定性特点,提出了一种基于非线性扰动观测器的自适应反演滑模控制方法,解决机械臂的轨迹跟踪控制问题;对于外界干扰,利用非线性扰动观测器进行观测补偿,无需上界先验知识;对于结构不确定性,引入反演滑模控制,同时设计自适应律,保证闭环系统的稳定性并增强系统的动态适应性;仿真结果证明,所提出的方法可以有效克服系统不确定性,降低控制输入信号的抖振,最终实现期望轨迹的快速精确跟踪。
The dynamic model of the manipulator usually contains certain structural uncertainties and is always influenced by unknown disturbance.An adaptive backstepping sliding mode control method based on nonlinear disturbance observer is proposed to solve the problem of trajectory tracking control for the manipulator in this paper.The nonlinear disturbance observer is used to observe the external disturbance without the prior knowledge of the upper bound.For structural uncertainties,backstepping sliding mode control with the adaptive law is introduced to ensure the stability of the closed-loop system and enhance the system dynamic adaptability.The simulation results show that the proposed method can effectively overcome the uncertainty of the system,reduce the buffing of the input signal and finally realize the fast and accurate tracking of the desired trajectory.
The dynamic model of the manipulator usually contains certain structural uncertainties and is always influenced by unknown disturbance.An adaptive backstepping sliding mode control method based on nonlinear disturbance observer is proposed to solve the problem of trajectory tracking control for the manipulator in this paper.The nonlinear disturbance observer is used to observe the external disturbance without the prior knowledge of the upper bound.For structural uncertainties,backstepping sliding mode control with the adaptive law is introduced to ensure the stability of the closed-loop system and enhance the system dynamic adaptability.The simulation results show that the proposed method can effectively overcome the uncertainty of the system,reduce the buffing of the input signal and finally realize the fast and accurate tracking of the desired trajectory.
引文
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[10]邓伟,刘平,李贻斌,等.基于模型预测控制的排爆机器人轨迹跟踪算法研究[J].仪器仪表学报,2016(s1):1-6.
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[12]蔡自兴,谢斌.机器人学(第三版)[M].北京:清华大学出版社,2015.
[13]苏磊,姚宏,杜军,等.飞行器自适应反推Terminal滑模轨迹跟踪控制[J].系统工程与电子技术,2014(11):2249-2254.
[14]刘金锟.机器人控制系统的设计与MATLAB仿真[M].北京:清华大学出版社,2008.
[2]马如奇,董为,杜志江,等.主被动混合式微创手术机械臂机构设计及灵巧度优化[J].机器人,2013,35(1):81-89.
[3]刘志全,危清清,王耀兵.空间机械臂关节精细动力学模型的建立及关节力矩控制[J].宇航学报,2014,35(6):663-668.
[4]史先鹏,刘士荣.机械臂轨迹跟踪控制研究进展[J].控制工程,2011,18(1):116-122.
[5]吴玉香,张景,王聪.机械臂的自适应神经网络控制与学习[J].机械工程学报,2013,49(15):42-48.
[6]刘福才,梁利环,高娟娟,等.不同重力环境的空间机械臂自抗扰轨迹跟踪控制[J].控制理论与应用,2014,31(3):352-360.
[7]Benzaoui M,Chekireb H,Tadjine M,et al.Trajectory tracking with obstacle avoidance of redundant manipulator based on fuzzy inference systems[J].Neurocomputing,2016,196(C):23-30.
[8]Chu Z Y,Cui J,Sun F C.Fuzzy Adaptive disturbance-observer-based robust tracking control of electrically driven free-floating space manipulator[J].IEEE Systems Journal,2014,8(2):343-352.
[9]Yen V T,Wang Y N,Cuong P V,et al.Robust adaptive sliding mode control for industrial robot manipulator using fuzzy wavelet neural networks[J].International Journal of Control Automation&Systems,2017,15(6):2930-2941.
[10]邓伟,刘平,李贻斌,等.基于模型预测控制的排爆机器人轨迹跟踪算法研究[J].仪器仪表学报,2016(s1):1-6.
[11]Mondal S,Mahanta C.Adaptive second order terminal sliding mode controller for robotic manipulators[J].Journal of the Franklin Institute,2014,351(4):2356-2377.
[12]蔡自兴,谢斌.机器人学(第三版)[M].北京:清华大学出版社,2015.
[13]苏磊,姚宏,杜军,等.飞行器自适应反推Terminal滑模轨迹跟踪控制[J].系统工程与电子技术,2014(11):2249-2254.
[14]刘金锟.机器人控制系统的设计与MATLAB仿真[M].北京:清华大学出版社,2008.