电液伺服系统RBF神经网络滑模控制
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摘要
针对阀控液压缸位置伺服系统非线性导致模型参数确定困难及干扰问题,在分析三阶位置控制的电液控制系统原理及模型的基础上,引入神经网络的RBF径向基控制模型和自适应滑模算法,同时考虑了非1负反馈参数,建立了基于RBF神经网络滑模控制的电液伺服控制系统数学模型。通过选取合适的Lyapunov函数,分析了系统稳定性,解决了参数未定及挠动情况下的电液伺服系统控制器设计问题。仿真结果证明,所设计的控制器使系统的输出对给定信号的跟踪精度高,响应快,具有较强的鲁棒性。
Aiming at the problem of interference and difficulty of model parameter determination caused by nonlinearity of valve-controlled hydraulic cylinder position servo system,on the basis of analysis of electro-hydraulic control servo system principle and model of third-order position control,we introduce a neural network RBF model and an algorithm of adaptive sliding mode control,and non-one negative feedback parameters are considered at the same time. A mathematical model of electro-hydraulic servo control system based on RBF neural network sliding mode control is established. By choosing the appropriate Lyapunov function and analyzing system stability,the design problem of electro-hydraulic servo system controller under the condition of uncertain parameters and torsion is solved. The simulation results show that the designed controller has high tracking accuracy,fast response and strong robustness to a given signal.
Aiming at the problem of interference and difficulty of model parameter determination caused by nonlinearity of valve-controlled hydraulic cylinder position servo system,on the basis of analysis of electro-hydraulic control servo system principle and model of third-order position control,we introduce a neural network RBF model and an algorithm of adaptive sliding mode control,and non-one negative feedback parameters are considered at the same time. A mathematical model of electro-hydraulic servo control system based on RBF neural network sliding mode control is established. By choosing the appropriate Lyapunov function and analyzing system stability,the design problem of electro-hydraulic servo system controller under the condition of uncertain parameters and torsion is solved. The simulation results show that the designed controller has high tracking accuracy,fast response and strong robustness to a given signal.
引文
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[2]SAMER A,FETHI B.OUEZDOUA,et al.High Performance Integrated Electro-hydraulic Actuator for Robotics-Part I:Principle,Prototype Design and First Experiments[J].Sensors and Actuators A,2011,(169):115-123.
[3]AHMED ALISOFIANE.Sampled Data Observer Based Intersample Output Predictor for Electro-hraulic Actuators[J].ISA Transactions,2015,(58):421-433.
[4]NGUYEN M T,DOAN N C,HYUNG G,et al.Trajectory Control of an Electro Hydraulic Actuator Using an Iterative Backstepping Control Scheme[J].Mechatronics,2015,(29):96-102.
[5]吴宝举,李硕,王晓辉.自治水下机器人自适应滑模控制[J].机械设计与制造,2010,(7):142-144.WU Baoju,LI Shuo,WANG Xiaohui.Adaptive Sliding Mode Control of an Autonomous Underwater Vehicle[J].Machinery Design&Manufacture,2010,(7):142-144.
[6]何常玉,施光林,郭秦阳.负载挠动的电液比例位置系统鲁棒控制策略研究[J].机床与液压,2018,46(3):90-94.HE Changyu,SHI Guanglin,GUO Qinyang.Study in Robust Control Strategy for Electro-hydraulic Proportional position System with Load Disturbance[J].Machine Tool&Hydraulics,2018,46(3):90-94.
[7]WANG Shu,RICHARD B,SAEID H.Sliding Mode Controller and Filter Applied to an Electrohydraulic Actuator System[J].Journal of Dynamic Systems,Measurement,and Control,2011,133(2):024504-024510.
[8]KARPENKO M,SEPEHRI N.Robust Position Control of an Electro-hydraulic Actuator With a Faulty Actuator Piston Seal[J].Journal of Dynamic Systems,Measurement,and Control,2003,9(125):413-423.
[9]CLAUDE K,JEAN-PIERRE K,MAAROUF S.Indirect Adaptive Control of an Electrohydraulic Servo System Based on Nonlinear Backstepping[J].IEEE/ASME Transactions on Mechatronics,2011,6(16):1171-1177.
[10]张友旺.电液伺服系统的动态递归模糊神经网络辨识与鲁棒控制研究[D].长沙:中南大学,2006.ZHANG Youwang.Study on Identification by Dynamic Recurrent Fuzzy Neural Networks and Robust Control for Electro-hydraulic Servo System[D].Changsha:Central South University,2011.
[11]张慧凤.基于干扰观测器的几类非线性系统抗干扰控制[D].沈阳:东北大学,2016.ZHANG Huifeng.Several Kinds of Nonlinear System Antiinterference Control Based on Disturbance Observer[D].Shenyang:Northeastern University,2016.
[12]王雪丽.基于RBF神经网络电液恒功率调速自整定PID控制[J].机床与液压,2016,44(22):115-117.WANG Xueli.Self-tuning PID Control of Electric Hydraulic Constant Power Speed Regulation Based on RBFNeural Network[J].Machine Tool&Hydraulics,2016,44(22):115-117.
[13]王春行.液压控制系统[M].北京:机械工业出版社,1999.WANG Chunxing.Hydraulic Control System[M].Beijing:China Machine Press,1999.
[14]靳宝全,熊诗波,梁义维,等.考虑反馈机构动刚度的轧机伺服压下系统建模与仿真[J].中国机械工程,2008,19(11):1330-1335.JIN Baoquan,XIONG Shibo,LIANG Yiwei,et al.Modeling and Simulation for Rolling Mill Servo Screwdown System Involving Dynamic Stiffness of Displacement Feedback Apparatus[J].China Mechnical Engineering,2008,19(11):1330-1335.