基于改进混合遗传算法的二自由度PID控制器设计与应用

针对一般遗传算法存在的不足,提出一种改进的混合遗传算法,并将其应用于二自由度PID控制器参数寻优设计,仿真试验表明,所设计的二自由度PID控制器具有优良的鲁棒特性和抑制外界于扰特性,在仿真转台控制系统设计中获得了良好的控制效果,从而说明了该方法的有效性。     

基于二次稳定的仿真转台鲁棒控制器设计

针对摩擦力矩干扰,系统参数摄动等非线性扰动环节对仿真转台控制系统的影响,提出了基于二次稳定理论的仿真转台鲁棒控制器设计思想。分析了二次稳定理论的基本原理及设计方法,给出了某型飞行仿真转台基于二次稳定的状态反馈控制器和PID鲁棒控制器设计实例。仿真结果表明,基于二次稳定理论的控制器克服了摩擦力矩干扰以及转动惯量摄动对仿真转台的影响,实现了转台转角的精确控制,动态指标优越,满足了高精度飞行仿真转台系统的鲁棒控制要求。     

A nonlinear friction compensation method using adaptive control and its practical application to an in-parallel actuated 6-DOF manipulator

This paper presents a simple and effective nonlinear friction compensation method which is derived from an adaptive control strategy and its practical application to a linear actuator. The proposed adaptive friction compensation method is shown to be equivalent to the reversed integral controller that is easily applied to the conventional PID controller. The reversed integral controller reverses the sign of the integrator output as the sign of the velocity changes. It analyzes how the reversed control action can compensate for friction. The effectiveness of this approach is demonstrated by experiments on a 3-PRPS (Prismatic-Revolute-Prismatic-Spherical joints) in-parallel 6-DOF manipulator.     

Adaptive robust control of linear motors with dynamic friction compensation using modified LuGre model

LuGre model has been widely used in dynamic friction modeling and compensation. However, there are some practical difficulties when applying it to systems experiencing large range of motion speeds such as, the linear motor drive system studied in the article. This article first details the digital implementation problems of the LuGre model based dynamic friction compensation. A modified model is then presented to overcome those shortcomings. The proposed model is equivalent to LuGre model at low speed, and the static friction model at high speed, with a continuous transition between them. A discontinuous projection based adaptive robust controller (ARC) is then constructed, which explicitly incorporates the proposed modified dynamic friction model for a better friction compensation. Nonlinear observers are built to estimate the unmeasurable internal state of the dynamic friction model. On-line parameter adaptation is utilized to reduce the effect of various parametric uncertainties, while certain robust control laws are synthesized to effectively handle various modeling uncertainties for a guaranteed robust performance. The proposed controller is also implemented on a linear motor driven industrial gantry system, along with controllers with the traditional static friction compensation and LuGre model compensation. Extensive comparative experimental results have been obtained, revealing the instability when using the traditional LuGre model for dynamic friction compensation at high speed experiments and the improved tracking accuracy when using the proposed modified dynamic friction model. The results validate the effectiveness of the proposed approach in practical applications.     

Desired Compensation Adaptive Robust Control of Electrical-optical Gyro-stabilized Platform with Continuous Friction Compensation Using Modified LuGre Model

Continuous friction compensation along with other modeling uncertainties is concerned in this paper, to result in a continuous control input, which is more suitable for controller implementation. To accomplish this control task, a novel continuously differentiable nonlinear friction model is synthesized by modifying the traditional piecewise continuous LuGre model, then a desired compensation version of the adaptive robust controller is proposed for precise tracking control of electrical-optical gyro-stabilized platform systems. As a result, the adaptive compensation and the regressor in the proposed controller will depend on the desired trajectory and on-line parameter estimates only. Hence, the effect of measurement noise can be reduced and then high control performance can be expected. Furthermore, the proposed controller theoretically guarantees an asymptotic output tracking performance even in the presence of modeling uncertainties. Extensively comparative experimental results are obtained to verify the effectiveness of the proposed control strategy.

     

Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.     

基于运动学正解的三转动并联机构迭代补偿控制

首先建立三转动并联机构的运动学方程,研究该并联机构的运动学反解和运动学正解,然后建立该机 构的动力学方程并分析其动力学特性．基于该机构研制了能复现自行武器行进时的车体姿态变化过程的动态模拟器 试验台．该试验台利用运动学反解算法进行闭环控制,并采用基于运动学正解的开环迭代补偿控制算法修正姿态驱 动信号,使试验台的响应逐渐逼近期望的姿态指令．测试表明该系统时域波形复现精度优于95%,验证了迭代补偿 控制的有效性．     

循环球电动助力转向系统控制及补偿策略

考虑循环球式转向系统内多因素的影响,设计循环球式电动助力系统的控制及补偿策略,建立循环球式电动助力转向系统模型,设计电流助力曲线,采用模糊PID控制方法,实现电机的实时控制;为了获得更好的助力力矩,补偿系统内损失,基于LuGre摩擦模型,通过观测到的系统参数,建立摩擦状态观测器,得到摩擦补偿叠加电流。使用Matlab/Simulink与CarSim的联合仿真验证控制系统;通过对增加摩擦补偿策略前后的对比分析,可知所设计的电动助力转向电流控制系统能综合车辆行驶时的摩擦、车速和转向盘转角等信息,由助力执行电机产生适当的助力,更准确地实现驾驶员的驾驶意图,使得回正过程更加平稳。     

基于神经网络和PID算法的数控机床并行混合控制模型

针对数控机床低速运动时由于非线性摩擦造成的问题，提出了一种基于神经网络和PID算法的并行混合控制模型．当电机速度大于转换速度时使用PID控制，小于转换速度时使用神经网络控制器．神经网络为5个输入的单神经元，采用Hebb学习算法．分析表明，混合控制器使跟随误差的波动明显减小，机床运动变得平稳．利用可由用户编写伺服算法的多轴运动控制器(PMAC)进行了实验，验证了混合控制器的控制效果．     

滚珠丝杠式电动舵机系统非线性特性分析

针对速度反馈控制的滚珠丝杠式电动舵机系统,建立更加完整的系统模型,模型中充分考虑间隙和摩擦等非线性因素的影响,并通过数值仿真,观察分析不等间隙和摩擦对系统输出的影响规律。采用LuGre模型和死区模型分别描述电动舵机运行时的摩擦和间隙行为,然后根据传动链结构特点提出非线性研究方案,并根据此方案将非线性环节加入所建立的电动舵机二阶模型中,分别对间隙和摩擦的影响进行仿真分析。仿真结果表明,间隙和摩擦会使伺服系统产生跟踪误差,影响定位精度,甚至影响系统稳定。     

基于LuGre 摩擦模型的机械臂模糊神经网络控制

针对未知摩擦非线性会使机械臂控制精度难以提高的缺陷,建立基于动态LuGre摩擦的机械臂模型.在系统参数未知和机械臂负载变化的情况下,设计一种自适应模糊神经网络控制器,采用基函数中心和宽度均自适应变化的模糊神经网络补偿器,实现对系统中包括LuGre摩擦在内的非线性环节的逼近,并利用滑模控制项减小逼近误差.通过Lyapunov方法证明了闭环系统的稳定性,并通过仿真结果验证了所提出控制方法的有效性.     

基于神经网络补偿的转台伺服系统控制研究

针对飞行仿真转台伺服系统中存在的非线性摩擦干扰进行了研究,采用一种基于RBF神经网络进行误差补偿的在线自适应控制策略。在基于逆动力学的计算力矩控制方法的基础上,利用RBF神经网络的万能逼近特性在线辨识模型误差,从而对系统进行补偿,其权值自适应律根据Lyapunov稳定性理论推导,保证了系统跟踪误差的收敛及稳定,仿真结果表明该控制策略可使位置MAE指标从0.0087m提高到0.0016m,使位置MSE指标从1.0128e-4m提高到3.3002e-6m,具有较高的鲁棒性和稳态控制精度。最后分别从隐层节点数及节点中心学习算法的变化两方面提出两种改进方案,仿真结果表明隐层节点数的增加可以进一步减小位置误差,而采用K-means均值聚类算法解决了神经网络节点中心按经验选取或试凑的困难。     

基于新型补偿控制策略的柔性关节控制器设计

柔性关节机器人控制系统中存在不确定性扰动、摩擦力、参数变化以及建模误差等问题,而常规PID控制无法兼顾稳定性和控制精度的要求,为此设计了一种基于新型补偿控制策略的柔性关节鲁棒控制器.控制器设计中,将摩擦力分为线性和非线性两部分,扰动分为确定性和不确定性两部分:机器人自身结构相关量、确定性扰动以及摩擦力的线性部分可以通过...     

自适应模糊PID控制器在跟踪器瞄准线稳定系统中的应用

针对陀螺惯性平台上的跟踪器瞄准线稳定系统中非线性不确定因素对稳定精度的影响, 设计了一种自适应模糊PID复合控制策略. 提出了改进的自适应调整因子和学习算法进行控制参数和规则的在线修正; 采用PID控制克服模糊控制固有的精度盲区. 实验结果表明该方法在一定测量噪声和速度敏感范围内, 能有效地隔离载体扰动,保证跟踪器对目标的准确瞄准, 具有动态响应快、稳定精度高、自适应抗干扰鲁棒性强等特点.     

Trajectory Tracking Control of XY Table Using Sliding Mode Adaptive Control Based on Fast Double Power Reaching Law

Currently, high velocity and precision are the main developing directions of the XY table. However, the nonlinear effects of friction at low speed deteriorate the precision of the XY table servo system. As a result, it is very important to design a control method to carry out friction compensation and trajectory tracking. In this paper, dual sliding mode state observers are used to estimate these immeasurable parameters in the dynamic LuGre model, and the Lyapunov function is used to design the adaptive update law. In addition, fast double power reaching law has the advantage of improving the global asymptotic convergence rate and overcoming these disadvantages where traditional sliding mode control reaching law causes severe chattering. Simulation results that compare the proposed method with exponent sliding mode control and PID control, demonstrate that the fast double power sliding mode control guarantees position and speed signals, tracking the desired references asymptotically.     

基于感知模糊自适应蚁群算法的非线性PID控制

随着系统复杂度的提高和对象不确定性因素的增加,为克服线性PID动态性能和稳态性能差的缺陷,分析了非线性PID控制器各控制参数对误差的理想变化过程,构造非线性PID控制器。由于增益参数大量增加,传统参数优化方法不再适用,在分析蚁群算法的基础上,提出了基于感知自适应蚁群算法,并加入模糊自适应信息素更新机制,用于优化非线性PID控制器的设计方法。通过仿真实验将该控制器与基于蚁群算法的非线性PID控制器和基于蚁群算法、Z-N法的PID控制器进行对比,并对控制性能和收敛性能进行了分析,结果表明该算法有效克服了传统蚁群算法收敛速度较慢、容易陷入局部最优而停滞的缺陷,该控制器具有更好的动态性能和稳态性能。     

含有LuGre摩擦并联机械臂的自适应控制

本文研究了含有LuGre摩擦的并联机械臂自适应控制问题.首先,在并联机械臂动力学模型中引入LuGre摩擦模型来描述伺服关节内部的摩擦行为;其次,构造含有动态摩擦补偿的自适应控制算法,并使用Lyapunov方法证明控制算法的有效性;最后,通过平面3 RRR并联机械臂数值算例,验证所提出控制算法的效果以及LuGre摩擦补偿的必要性.     

高速AWID车辆车轮独立制动控制研究

全部车轮均独立驱动/制动(AWID)的车辆比非独立驱动/制动的车辆在高速工况下具有更优越的动力、机动和操纵性能,论文对车轮独立制动控制问题进行研究;首先建立车轮独立制动的数学模型,简单介绍轮胎LuGre动态模型;然后分析制动控制的目标,设计控制系统结构和自抗扰控制器;最后对动态期望滑移率下的车轮制动控制进行仿真;结果表明,所设计的自抗扰控制器可以实现强鲁棒和高精度的车轮独立制动控制。     

控制力矩陀螺框架伺服系统期望补偿自适应鲁棒控制

本文针对控制力矩陀螺框架伺服系统中存在的参数不确定性、摩擦非线性及外部干扰问题,提出了一种考虑LuGre摩擦的自适应鲁棒控制方法.针对陀螺框架伺服系统未知惯量和阻尼系数、LuGre摩擦参数不确定性及未知外部干扰上界,设计参数更新律对其进行估计.在此基础上,为提高系统对不确定参数及未知干扰的鲁棒性,设计带有期望补偿的自适应鲁棒控制器,可实现对LuGre摩擦非线性的精确补偿,同时减小测量信号噪声及外部干扰对系统的不利影响.应用Lyapunov稳定性理论分析了闭环系统的稳定性.对挠性航天器姿态机动控制的仿真结果,验证了所提方法的有效性.