摘要
针对泵控电液伺服系统中常见的参数不确定性和未知干扰问题,文章设计了一种结合RBF神经网络的预设性能滑模控制方法(RBFPPCBSMC)。首先,基于模型设计了一种干扰观测器(DOB)对未知扰动进行估计,并采用反步法设计改进趋近律的滑模控制律,通过双曲正切函数(tanh)构造滑模面切换函数,有效抑制滑模控制中的高频抖振现象。其次,设计径向基函数(RBF)神经网络对系统未建模动态进行自适应补偿。然后,引入规定性能约束(PPC),确保瞬态和稳态位置响应在要求的有界范围内,进一步降低系统的跟踪误差。通过Lyapunov稳定性理论,证明了采用该控制方法的闭环系统的稳定性。为了验证RBFPPCBSMC的有效性,文章进行了详细的仿真对比。仿真结果表明,该控制器能够实现泵控电液伺服系统的精准控制,并有效应对模型参数不确定性和外部扰动带来的挑战。
To address the common issues of parameter uncertainty and unknown disturbances in pump control electrohydraulic servo systems,this paper proposes a novel control strategy combining RBF neural networks with preset performance sliding mode control(RBFPPCBSMC).Initially,a disturbance ob-server(DOB)is designed based on the system model to estimate unknown disturbances.The sliding mode control law is then formulated using a backstepping approach.The sliding surface switching function is constructed via the hyperbolic tangent function(tanh),effectively mitigating the high-frequency chattering phenomenon inherent in sliding mode control.In parallel,a radial basis func-tion(RBF)neural network is synergistically designed to achieve adaptive compensation for the sys-tem’s unmodeled dynamics.To ensure that both transient and steady-state position responses re-main within desired bounds and to minimize tracking errors,a prescribed performance constraint(PPC)is incorporated.The stability of the closed-loop system under this control method is rigor-ously proven using the Lyapunov stability theory.Detailed simulation comparisons are conducted to validate the effectiveness of the RBFPPCBSMC.Simulation results demonstrate that the proposed controller achieves precise control of the electro-hydraulic servo system and effectively handles challenges posed by model uncertainties and external disturbances.
作者
郑益平
马琛俊
Yiping Zheng;Chenjun Ma(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai;Shanghai Electric Hydraulics and Pneumatics Co.,Ltd.,Shanghai)
出处
《建模与仿真》
2025年第5期703-714,共12页
Modeling and Simulation
关键词
电液伺服系统
RBF神经网络
规定性能约束
参数不确定
滑模控制
Electro-Hydraulic Servo System
RBF Neural Network
Prescribed Performance Constraint
Parameter Uncertainty
Sliding Mode Control
