基于扩展状态观测器的伺服系统特征建模和自适应滑模控制
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摘要
为抑制伺服系统中的转矩扰动和惯量变化对动态性能和稳态精度的影响,该文提出了1种基于扩展状态观测器(ESO)的伺服系统特征建模和自适应离散终端滑模控制方法。将伺服系统动力学模型中的摩擦力矩、转矩扰动和其他不确定性扰动归入集总扰动,并看作新的系统状态,设计ESO对其进行观测和补偿。在补偿后的广义被控对象基础上,通过采样其输入输出数据和在线参数辨识,建立伺服系统特征模型,并设计自适应离散终端滑模控制器。通过Lyapunov稳定性理论分析观测误差的收敛性,并证明跟踪误差的有限时间有界性。仿真结果表明,该文方法对转矩扰动有较强的鲁棒性,且能够适应20倍以内的转动惯量。
A characteristic modeling method based on an extended state observer(ESO)and an adaptive discrete terminal sliding-mode controller is proposed to restrain the influence of torque disturbances and inertia variations on the dynamic performance and steady-state accuracy of servo systems. The friction moment,torque disturbances and other uncertainties in a dynamics model are encapsulated into lumped disturbances and regarded as a new system state,and an ESO is designed to observe and compensate it.A characteristic model is established for the generalized compensated servo system and an adaptive discrete terminal sliding-mode controller is designed based on the sampled input-output data and online parameter identification method. The convergence of observation error and the finite-time boundedness of tracking error are proved by Lyapunov stability theory. Simulation results show that the proposed method has strong robustness to torque disturbances and can adapt to inertia variations within 20 times.
A characteristic modeling method based on an extended state observer(ESO)and an adaptive discrete terminal sliding-mode controller is proposed to restrain the influence of torque disturbances and inertia variations on the dynamic performance and steady-state accuracy of servo systems. The friction moment,torque disturbances and other uncertainties in a dynamics model are encapsulated into lumped disturbances and regarded as a new system state,and an ESO is designed to observe and compensate it.A characteristic model is established for the generalized compensated servo system and an adaptive discrete terminal sliding-mode controller is designed based on the sampled input-output data and online parameter identification method. The convergence of observation error and the finite-time boundedness of tracking error are proved by Lyapunov stability theory. Simulation results show that the proposed method has strong robustness to torque disturbances and can adapt to inertia variations within 20 times.
引文
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[14] 郭健,季晶晶,杨帆,等.基于LuGre摩擦模型的伺服系统自适应鲁棒控制器[J].南京理工大学学报,2013,37(6):779-784.Guo Jian,Ji Jingjing,Yang Fan,et al.Adaptive robust controller for servo system based on LuGre model of friction[J].Journal of Nanjing University of Science and Technology,2013,37(6):779-784.
[15] Li Shihua,Du Haibo,Yu Xinghuo.Discrete-time terminal sliding mode control systems based on Euler’s discretization[J].IEEE Transactions on Automatic Control,2014,59(2):546-552.
[2] Yang Jun,Chen Wenhua,Li Shihua,et al.Disturbance/uncertainty estimation and attenuation techniques in PMSM drives—A survey[J].IEEE Transactions on Industrial Electronics,2017,64(4):3273-3285.
[3] Ha W,Back J.A disturbance observer-based robust tracking controller for uncertain robot manipulators[J].International Journal of Control Automation & Systems,2018,16(2):417-425.
[4] Wang Bo,Luo Cheng,Yu Yong,et al.Anti-disturbance speed control for induction machine drives using high-order fast terminal sliding-mode load torque observer[J].IEEE Transactions on Power Electronics,2017,33(9):7927-7937.
[5] 宋江鹏,周荻,孙广利.基于扩张观测器的反射镜平台自适应鲁棒控制[J].系统工程与电子技术,2017,39(4):876-882.Song Jiangpeng,Zhou Di,Sun Guangli.Adaptive robust control for mirror platform based on extended state observer[J].Systems Engineering & Electronics,2017,39(4):876-882.
[6] Li Zhijun,Liu Chengying,Meng Fanwei,et al.Precision motion control of permanent magnet linear synchronous motor servo system based on an integrated controller with inertia variation compensation[J].Proceedings of Institution of Mechanical Engineers,Part C:Journal of Mechanical Engineering Science,2013,227(7):1481-1494.
[7] Oh K S,Seo J H.Inertial parameter estimation of an excavator with adaptive updating rule using performance analysis of Kalman filter[J].International Journal of Control Automation & Systems,2018,16(3):1226-1238.
[8] Pan Y R,Shih Y T,Horng R H,et al.Advanced parameter identification for a linear-motor-driven motion system using disturbance observer[J].International Journal of Precision Engineering & Manufacturing,2009,10(4):35-47.
[9] Saghafinia A,Ping H W,Uddin M N.Fuzzy sliding mode control based on boundary layer theory for chattering-free and robust induction motor drive[J].International Journal of Advanced Manufacturing Technology,2014,71(1-4):57-68.
[10] Wang Chunming,Xia Yuanqing,Fu Mengyin,et al.Application of active disturbance rejection control in tank gun control system[J].Journal of the Franklin Institute,2014,351(4):2299-2314.
[11] Yi Guo,Mao Jianxu,Wang Yaonan,et al.Adaptive tracking control of nonholonomic mobile manipulators using recurrent neural networks[J].International Journal of Control Automation & Systems,2018(2-3):1-14.
[12] 吴宏鑫,胡军,解永春.基于特征模型的智能自适应控制[M].北京:中国科学技术出版社,2009.
[13] Wu Hongxin,Hu Jun,Xie Yongchun.Characteristic model-based all-coefficient adaptive control method and its applications[J].IEEE Transactions on Systems Man & Cybernetics Part C,2007,37(2):213-221.
[14] 郭健,季晶晶,杨帆,等.基于LuGre摩擦模型的伺服系统自适应鲁棒控制器[J].南京理工大学学报,2013,37(6):779-784.Guo Jian,Ji Jingjing,Yang Fan,et al.Adaptive robust controller for servo system based on LuGre model of friction[J].Journal of Nanjing University of Science and Technology,2013,37(6):779-784.
[15] Li Shihua,Du Haibo,Yu Xinghuo.Discrete-time terminal sliding mode control systems based on Euler’s discretization[J].IEEE Transactions on Automatic Control,2014,59(2):546-552.