基于干扰观测器的级联气动肌肉肘关节滑模控制
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摘要
肘关节的设计和控制是仿人手臂的研究重点。为了得到肘关节的模型,首先搭建测试平台对单根气动肌肉进行静态建模,再建立级联式肘关节的名义模型,采用最小二乘参数辨识得到模型的参数。基于Luenberger干扰观测器设计了滑模控制律。分别采用PID控制、滑模控制和基于干扰观测器的滑模控制对肘关节位置跟踪进行仿真和实验,在仿人手臂末端夹持半瓶矿泉水作为负载和外界不确定性干扰,测试3种控制算法的性能。仿真和实验结果表明,基于干扰观测器的滑模控制位置跟踪精度和鲁棒性均优于滑模控制和PID控制。
The design and control of elbow joint are the research priorities of humanoid arm. To obtain the elbow joint model,a test platform is constructed for static modeling of a single pneumatic muscle,and then a nominal model of cascade elbow joint is established. The least square parameter identification is used to obtain the parameters of model. A sliding mode control law is designed based on Luenberger disturbance observer. The elbow joint location tracking with proportion integration differentiation( PID) control,sliding mode control( SMC) and sliding mode control based on disturbance observer( SMCDO) are simulated. Three control algorithms are tested by taking half a bottle of mineral water held at the end of humanoid arm as a load and uncertain outside disturbance. The simulated and experimental results show that the location tracking accuracy and robustness of sliding mode control based on disturbance observer are better than those of sliding mode control and PID control.
The design and control of elbow joint are the research priorities of humanoid arm. To obtain the elbow joint model,a test platform is constructed for static modeling of a single pneumatic muscle,and then a nominal model of cascade elbow joint is established. The least square parameter identification is used to obtain the parameters of model. A sliding mode control law is designed based on Luenberger disturbance observer. The elbow joint location tracking with proportion integration differentiation( PID) control,sliding mode control( SMC) and sliding mode control based on disturbance observer( SMCDO) are simulated. Three control algorithms are tested by taking half a bottle of mineral water held at the end of humanoid arm as a load and uncertain outside disturbance. The simulated and experimental results show that the location tracking accuracy and robustness of sliding mode control based on disturbance observer are better than those of sliding mode control and PID control.
引文
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[4]Robinson R M,Kothera C S,Sanner R M,et al.Nonlinear control of robotic manipulators driven by pneumatic artificial muscles[J].IEEE/ASME Transactions on Mechatronics,2016,21(1):55-68.
[5]Lilly J H,Quesada P M.A two-input sliding-mode controller for a planar arm actuated by four pneumatic muscle groups[J].IEEE Transactions on Neural Systems and Rehabilitation Engineering,2004,12(3):349-359.
[6]Pujana-Arrese A,Mendizabal A,Arenas J,et al.Research on the position control of a 1-Do F set-up powered by pneumatic muscles[C]∥IEEE International Conference on Mechatronics.Malaga:IEEE,2009:1-6.
[7]Chang M K.Tracking control of a leg rehabilitation machine driven by pneumatic artificial muscles using composite fuzzy theory[J].Scientific World Journal,2014(1):464276.
[8]Rezoug A,Tondu B,Hamerlain M.Experimental study of nonsingular terminal sliding mode controller for robot arm actuated by pneumatic artificial muscles[J].IFAC Proceedings Volumes,2014,47(3):10113-10118.
[9]Zhao L,Ge L,Yang Y.Active disturbance rejection trajectory tracking control for two-joint driven by pneumatic artificial muscles[C]∥2015 International Conference on Fluid Power and Mechatronics.Harbin,Heilongjiang,China:IEEE,2015:972-977.
[10]Eker I·.Second-order sliding mode control with experimental application[J].ISA Transactions,2010,49(3):394-405.
[11]Xing K Y,Huang J,Wang Y,et al.Tracking control of pneumatic artificial muscle actuators based on sliding mode and nonlinear disturbance observer[J].IET Control Theory&Applications,2010,4(10):2058-2070.
[12]Chang M K,Liou J J,Chen M L.T-S fuzzy model-based tracking control of a one-dimensional manipulator actuated by pneumatic artificial muscles[J].Control Engineering Practice,2011,19(12):1442-1449.
[13]Chang M K.An adaptive self-organizing fuzzy sliding mode controller for a 2-DOF rehabilitation robot actuated by pneumatic muscle actuators[J].Control Engineering Practice,2010,18(1):13-22.
[14]于海涛,郭伟,谭宏伟,等.基于气动肌腱驱动的拮抗式仿生关节设计与控制[J].机械工程学报,2012,48(17):1-9.YU Hai-tao,GUO Wei,TAN Hong-wei,et al.Design and control on antagonistic bionic joint driven by pneumatic muscles actuators[J].Journal of Mechanical Engineering,2012,48(17):1-9.(in Chinese)
[15]Wu Q,Wang X,Du F,et al.Fuzzy sliding mode control of an upper limb exoskeleton for robot-assisted rehabilitation[C]∥2015 IEEE International Symposium on Medical Measurements and Applications(Me Me A).Torino,Italy:IEEE,2015:451-456.
[16]刘金琨.滑模变结构控制MATALB仿真:基本理论与设计方法[M]:北京:清华大学出版社,2015.LIU Jin-kun.The sliding mode variable structure control MATLAB simulation:basic theory and design method[M]:Beijing:Tsinghua University Press,2015.(in Chinese)