滑模观测器在大惯量扫描镜系统中抗谐振的应用

针对扫描镜伺服控制系统中柔性连接所导致的机械谐振问题,本文提出一种结合电机加速度反馈以及负载速度反馈的滑模观测器控制方法.首先建立伺服系统柔性连接的数学模型并分析谐振对系统性能的影响;然后给出滑模观测器的设计过程;随后将观测出的电机加速度以及负载速度反馈到伺服系统中进行补偿;最后分析了位置传感器对伺服系统控制性能的影响,系统的鲁棒性,并与相似被控条件下的其他控制方法进行了比较.仿真结果表明:与未采用观测器时相比,本文所提出的方法有效地抑制了基于柔性连接的伺服系统中的机械谐振问题,提高了系统的控制性能,且具有较高的鲁棒性.     

基于滑模状态观测器的电液位置伺服系统控制

在电液伺服系统优化设计的研究中,针对电液位置伺服系统的高阶非线性特性、系统参数不确定性以及系统状态信号测量困难的情况,提出一种基于滑模状态观测器的反演控制策略.策略采用滑模方法设计状态观测器,只需要位置传感器,不需要速度传感器和加速度传感器.对采用状态观测器之后的系统,设计反演控制器,针对系统中的不确定性,在反演控制的最后一步采用滑模控制设计,基于Lyapunov方法证明了系统中所有信号是一致最终有界的,闭环系统是稳定的.仿真结果表明,上述策略为电液伺服系统优化设计提供了参考.     

三轴稳定卫星扫描镜伺服系统的谐振抑制

本文针对三轴稳定卫星中的扫描镜伺服系统在运行时产生的机械谐振现象,采用在反馈回路中加入加速度观测器的方法抑制此类机械谐振.首先针对大惯量扫描镜伺服系统的机械传动结构建立研究模型,通过数学推导和仿真分析谐振产生的原因及谐振对系统控制性能的影响;然后采用加速度观测器方法,将观测出的加速度反馈到伺服系统电流环的前端对谐振进行补偿,并分析了噪声对观测器性能的影响与限制;最后的仿真结果表明,相比于采用陷波滤波器抑制谐振的方法,采用加速度观测器能更为有效地抑制三轴稳定卫星中扫描镜伺服控制系统中的机械谐振,并提高系统的控制性能,且设计的观测器对噪声具有良好的鲁棒性.     

基于陷波器参数自调整的伺服系统谐振抑制

针对永磁交流伺服系统中的柔性传动环节,建立电机——负载二质量模型,通过对模型的Simulink仿真分析阐述系统机械谐振发生的机理。为抑制伺服系统的机械谐振,根据对伺服系统谐振的定量分析,结合对电机速度误差信号的快速傅里叶变换（FFT）分析,设计自动调整参数的陷波滤波器,并进行仿真实验与实际实验。实验结果证实理论分析的正确性和所设计陷波器的有效性,在传动环节的刚度、阻尼和负载惯量不尽准确的情况下,相关仿真结果验证所设计陷波器依旧有效。     

面向性能增强的双惯量伺服系统状态反馈控制

为避免使用函数逼近器(神经网络或模糊系统),并提高双惯量伺服系统的瞬态响应和稳态性能,针对含外部扰动的双惯量伺服系统,提出一种基于预设性能函数(Prescribed performance function, PPF)的类比例状态反馈控制策略.首先,提出一种改进的带有最大超调、收敛速率以及稳态误差的预设性能函数,并将该函数融入控制器设计使二惯量伺服的跟踪误差保持在预定的边界之内.其次,基于预设性能函数设计了类比例状态反馈控制器实现跟踪控制.与传统基于函数逼近控制方法相比较,该方法可降低控制系统计算复杂度同时消除反演控制中存在的复杂度爆炸问题.最后,利用双惯量伺服系统实验平台开展了对比实验,验证了所提出方法的有效性.     

未知死区输入非线性系统的双观测器动态面控制

针对一类含死区输入的严格反馈非线性系统,提出基于双观测器的自适应鲁棒控制算法.动态面的每一步设计中,第1观测器即跟踪信号观测器对指令信号进行观测,并得到指令信号的差分信号,消除传统动态面控制中计算复杂问题.第二观测器即扰动观测器在线估计高阶动态面控制系统中每一步的不确定模型,与跟踪信号观测器实现双反馈控制,提高控制效果...     

基于观测器的双吊具桥吊时变滑模同步控制

为针对双起升桥式吊车双吊具同步运行过程中普遍存在的无法精确建模、系统参数变化、外部扰动未知等问题,采用交叉耦合策略,提出了一种基于非线性扰动观测器的时变滑模同步控制方法。首先,采用时变滑模控制保证了控制器的全局鲁棒性;其次,利用非线性扰动观测器观测聚合扰动,对控制器进行扰动补偿;此外,提出一种可动态适应控制系统变化的变增益趋近律,有效抑制了控制输入抖振、缩短了趋近时间。最后,利用Lyapunov理论证明控制器的渐进稳定性,并通过仿真结果表明了所提出方法的有效性,控制器在未知扰动存在的情况下仍具有良好性能。     

基于观测器的伺服系统反馈线性化控制

基于重载且负载大范围变化的伺服系统提出高精度数学模型,建立扩展卡尔曼观测器对速度和模型中参数进行观测,使用基于模型的反馈线性化方法准确地将模型线性化,并使用线性控制方法设计高精度控制器。该策略的应用不但避免了传感器的测量时带来的误差,同时,在参数准确的条件下能够得到更高的控制精度。仿真实验结果表明:运用所设计的基于扩展卡尔曼观测器的反馈线性化控制策略不仅能够准确地对速度状态和参数进行观测,同时系统在跟踪性能方面也取得了较好的结果。     

基于固定时间扰动观测器的水面无人艇精确编队控制

在水面无人艇(USV)编队控制中,控制效果易受系统初始状态和内外部扰动的影响.为此,研究一类具有复杂干扰下的USV编队控制问题,结合固定时间扰动观测器提出一种领航-跟随编队控制方法.首先,提出一种基于固定时间滑模的跟踪控制(FTSM-TC)策略,在固定时间内保证领航艇快速跟踪期望轨迹;然后,为处理内外部未知干扰设计固定时间扰动观测器(FTDO),从而保证在固定时间内对编队系统中的未建模动态和外部复杂干扰进行精确辨识.所提出的基于FTDO的编队控制(FTDO-FC)策略,使编队控制系统在固定时间内收敛并保持稳定的期望队形,仿真结果表明,所设计控制方法能够有效解决存在复杂未知扰动情况下的USV编队控制问题,且收敛时间与系统初始状态无关.     

含执行机构未知动态的液压伺服系统输出反馈控制

针对含有未知动态(如:执行机构、负载等)液压伺服系统,提出一种基于未知系统动态估计器的输出反馈控制方法.该方法不依赖于函数逼近器和传统反步控制设计,且无需难以测量的系统内部状态.首先,为避免反步控制和系统全部状态,引入等价变换,将含液压执行机构的伺服系统高阶严格反馈模型转化为Brunovsky标准型,进而运用高阶滑模微分器观测转化后的系统未知状态.控制器设计中引入描述收敛速率、最大超调量和稳态误差的性能函数,保证预设控制系统稳态和瞬态控制性能.为补偿系统集总未知动态影响,设计一种仅含一个调节参数并保证指数收敛的未知系统动态估计器.该输出反馈控制器可以实现对系统输出的精确跟踪控制.最后,通过数值仿真结果表明了所提出算法的有效性.     

High order sliding mode observer for linear systems with unbounded unknown inputs

A global observer is designed for strongly detectable systems with unbounded unknown inputs. The design of the observer is based on three steps. First, the system is extended taking the unknown inputs (and possibly some of their derivatives) as a new state; then, using a global high-order sliding mode differentiator, a new output of the system is generated in order to fulfil, what we will call, the Hautus condition, which finally allows decomposing the system, in new coordinates, into two subsystems; the first one being unaffected directly by the unknown inputs, and the state vector of the second subsystem is obtained directly from the original system output. Such decomposition permits designing of a Luenberger observer for the first subsystem, which satisfies the Hautus condition, i.e. all the outputs have relative degree one w.r.t. the unknown inputs. This procedure enables one to estimate the state and the unknown inputs using the least number of differentiations possible. Simulations are given in order to show the effectiveness of the proposed observer.     

Observer‐based compensation control of servo systems with backlash

For compensating backlash phenomenon in servo systems, the authors propose an observer method in this paper to estimate both system states and vibration torque before controller design. First, a systematic scheme is given to obtain plant parameters, which is very important in observing system states. This is a parameter estimation principle that gives a crude estimation and computes the differences between the crude and true values. As a result, the precise value of the parameters is obtained by adding together the crude value and the difference. Then, based on the precise estimated parameters, an extended state observer (ESO) is designed to obtain feedback and feedforward signals. Consequently, robust compensation control is achieved by designing an output feedback controller, consisting of a feedback term and a feedforward term. Finally, in order to validate the proposed approach, extensive experiments are performed on a practical servo system with backlash nonlinearity.     

Multiple sliding mode observers and unknown input estimations for Lipschitz nonlinear systems

Multiple sliding mode observers for state and unknown input estimations of a class of MIMO nonlinear systems are systematically developed in this paper. A new nonlinear transformation is formulated to divide the original system into two interconnected subsystems. The unknown inputs are assumed to be bounded and not necessarily Lipschitz, and do not require any matching condition. Under structural assumptions for the unknown input distribution matrix, the sliding mode terms of the nonlinear observer are designed to track their respective unknown inputs. Also, the unknown inputs can be reconstructed from the multiple sliding mode structurally. The conditions for asymptotic stability of estimation error dynamics are derived. Finally, simulation results are given to demonstrate the effectiveness of the proposed method. Copyright © 2011 John Wiley & Sons, Ltd.     

大惯量扫描镜的滑模自抗扰控制

针对大惯量扫描镜伺服系统中因柔性连接所导致的机械谐振问题,本文提出一种非线性滑模自抗扰控制方法对机械谐振加以抑制.首先建立了伺服系统谐振数学模型,并分析了自抗扰控制抑制谐振的原理;然后建立了速度环滑模自抗扰控制器,并在计算机仿真软件中针对连续–离散混合模型进行仿真;最后在大惯量扫描镜机构上进行控制实验.仿真结果表明,采用滑模自抗扰控制后,机械谐振得到了抑制,系统的动态性能得到了提高,系统更接近于刚性连接系统.实验结果表明,扫描镜摆动过程中匀速段及反向加速段的机械谐振得到了有效抑制,位置跟踪精度得到了有效提高,达到了设计要求(<1′′).     

基于未知输入观测器的多智能体一致性控制

现有研究成果大多仅考虑随机噪声或未知输入干扰单一存在的情况,实际工程中两者往往同时存在.在此背景下,本文针对一类含有未知输入干扰和随机噪声的非线性多智能体系统,提出了一种一致性控制协议方法.首先,针对单个智能体系统设计未知输入观测器以消除干扰项对状态估计的影响.参考Kalman滤波器算法来求解状态反馈矩阵,使得输出残差信号的协方差最小,从而增强系统对随机噪声的鲁棒性.然后,基于观测器的状态估计信息,设计了鲁棒一致性控制协议,并将其转化为线性矩阵不等式求解问题.最后,通过一个数值仿真证明了所提方法的正确性和有效性.     

An adaptive sliding mode controller for electro-hydraulic servo systems combining offline training and online estimation

In order to improve the tracking accuracy of electro-hydraulic servo systems under nonlinear disturbance, an adaptive sliding mode controller (SMC) based on generalized regression neural network (GRNN) is proposed. The nonlinear factors and external disturbances of systems are considered in the controller, and an improved GRNN is used. In addition, the neural network achieves nonlinear approximation of the unknown part by online learning, determines the parameters of the SMC in real time by training the model offline, and reduces the impact of online estimation errors on the system to improve control accuracy. Finally, the effectiveness of the control method is verified by simulation.     

Robust actuator fault reconstruction for Takagi-Sugeno fuzzy systems with unknown input via a synthesized learning and sliding-mode observer

The issue of robust actuator fault reconstruction for a class of Takagi-Sugeno (T-S) fuzzy systems with actuator fault and unknown input via a novel Synthesized Learning and Sliding-Mode Observer (SLSMO) is investigated in this paper. Through a coordinate transformation technique, the considered T-S fuzzy system is decomposed into two separate subsystems: Subsystem 1 affected only by actuator fault and Subsystem 2 affected by unknown input and actuator fault. In the SLSMO methodology, for Subsystem 1, a new reduced-order Fuzzy Learning Observer (FLO) is explored to accurately reconstruct actuator fault, while a reduced-order Fuzzy Sliding Mode Observer (FSMO) is employed for Subsystem 2 such that it has strong robustness against actuator fault and unknown input. Stability and convergence of the fuzzy SLSMO are explicitly proved using Lyapunov's indirect method. The design issue of the reduced-order FLO and of the reduced-order FSMO can be uniformly formulated in terms of some Linear Matrix Inequalities (LMIs) that can be directly solved using LMI optimization technique. In addition, a new full-order FLO is suggested for actuator fault reconstruction in a class of T-S fuzzy system without unknown input. At the end, a numerical example is applied to verify the effectiveness and superiority of the proposed approaches.     

Exact state estimation for linear systems with unknown inputs based on hierarchical super‐twisting algorithm

A robust hierarchical observer is designed for linear time invariant systems with unknown bounded inputs under conditions of strong observability, providing exact state estimation. The main condition for designing the state estimator is the, so‐called, strong observability condition. The supertwisting (second‐order sliding mode) algorithm is used in each step of the hierarchy; the continuity of the supertwisting output injection allows to reconstruct a vector formed by some full column rank matrix premultiplied by the state vector, and that vector is obtained in a finite time and without any sort of filtration. For the case when the unknown inputs are considered as constant uncertain parameters, the continuous version of the least‐square method is developed. Two numerical examples illustrate the efficiency of the suggested technique. Copyright © 2007 John Wiley & Sons, Ltd.