带扰动补偿的无抖振离散重复控制器设计

针对周期离散系统的跟踪控制问题,提出一种有限时间单调收敛的无抖振吸引律,讨论扰动补偿措施并将其嵌入吸引律形成理想误差动态用于设计离散重复控制器.通过分析补偿误差上界说明扰动补偿措施能抑制重复控制未能消除的扰动,通过推导控制器稳态误差带说明吸引律的收敛性可使系统具有鲁棒稳定性.针对伺服电机系统的仿真与实验验证了设计工作的有效性.     

无抖振离散重复控制器的设计与实现

针对周期参考/干扰信号下的不确定离散时间系统,提出一种基于吸引律的重复控制方法,在吸引律中"嵌入"干扰抑制措施,构造理想误差动态,并基于此设计重复控制器.文中推导出单调减区域、绝对吸引层和稳态误差带边界的表达式,用于整定控制器参数和表征闭环系统的跟踪性能,并给出了跟踪误差在无干扰时收敛于原点及在干扰存在时收敛进入稳态误差带内所需最多步数的表达式.设计的重复控制器不仅能够完全抑制周期干扰信号,而且可以消除系统抖振.在电机实验装置上的应用结果表明了所提出控制方法的有效性.     

基于约束输入变速吸引律的离散重复控制器设计

针对离散时间线性系统的周期跟踪问题, 提出一种能够约束控制输入变化速度的变速吸引律, 结合干扰抑制措施构造了理想误差动态, 并由此导出离散重复控制器. 分析表明, 该变速吸引律能使跟踪误差在有限时间内单调收敛至零, 且误差收敛速度可控. 为刻画误差动态行为, 推导了有界扰动下的误差单调收敛域、绝对值收敛域和稳态误差带, 并给出了收敛步数. 针对伺服电机系统的仿真与实验结果验证了所提出控制方案的有效性.

     

采用干扰差分补偿的无切换吸引离散时间控制方法

提出一种基于无切换吸引律的离散控制器设计方法,将干扰差分补偿措施嵌入吸引律中构建理想误差动态,依据理想误差动态推导离散时间控制器.所提控制方案既回避了抖振,也能够有效抑制干扰.给出稳态误差带、绝对吸引层、单调减区间和跟踪误差首次进入稳态误差带的最多步数的具体表达式,用以刻画系统跟踪误差瞬态、稳态性能,并指导控制器参数整定.数值仿真与实验结果验证了所提出方法的有效性.     

离散时间系统重复控制的理想误差动态方法

针对周期参考信号下的离散时间系统, 引入吸引律构造理想误差动态特性, 并基于理想误差动态设计重复控制器. 重复控制能够实现周期性扰动的完全抑制, 从而提高控制能.为了消除颤振现象, 以饱和函数替换重复控制器中的符号函数. 分别推导了理想误差动态方程的单调减区域、吸引层和稳态误差带的边界, 用于刻画误差动态行为, 并给出了数值仿真结果. 在逆变器装置上完成的实验进一步表明了所提出的重复控制方法的有效性.

     

以幂次吸引的离散多周期重复控制

针对一类多周期干扰的抑制问题,提出一种基于幂次吸引律的离散多周期重复控制方法.多周期干扰由多个周期已知的周期干扰叠加而成.根据周期干扰的对称特性,构造出具有干扰抑制项的幂次吸引律,据此设计出子重复控制器,并以并联方式组合成多周期重复控制器,在消除多周期干扰的同时,有效地抑制慢时变非周期干扰带来的影响,改善控制品质;推导出幂次绝对吸引层和稳态误差带的具体表达式,用于刻画系统跟踪性能.仿真结果验证了所提控制方法的有效性.     

一种两相幂次吸引律离散时间控制方法

针对一类不确定离散时间系统,提出一种新型两相幂次吸引律.在吸引律设计中,通过将跟踪误差收敛过程划分为两个不同阶段,增加误差收敛幅度并提高误差收敛速度.构造离散形式的扩张状态观测器有效补偿系统干扰,基于观测值设计两相幂次形式的离散时间控制器,提高系统鲁棒性并减小稳态误差.此外,推导出跟踪误差绝对吸引层和稳态误差带的具体表...     

基于死区吸引律的离散重复控制

针对周期参考信号下的不确定离散时间系统,提出一种离散重复控制方法,利用死区函数设计新型的吸引律,将干扰补偿、抑制措施“嵌入”吸引律,构造理想误差动态,并基于此导出重复控制器。为了进行具体的控制器参数整定和表征闭环系统的误差动态行为,推导出了稳态误差带、单调减区域和绝对吸引层边界的表达式。所设计的离散重复控制器能够完全抑制周期对称干扰信号,控制器设计方法也适用于常值调节问题的定位控制。数值仿真及在电机伺服系统上的实验结果验证了所提出控制方法的有效性。     

重复学习控制及其在一类非线性系统中的应用

为跟踪或抑制仅周期已知的未知周期参考或扰动信号,提出一种新的重复学习控制方法,利用系统的稳态误差并通过迭代学习构造前馈补偿,实现了误差的渐近收敛,将所提出方法应用于一类常见的扰动信号和系统输出具有未知非线性关系的非线性系统,假设其满足连续里普希斯条件,利用重复学习控制器,系统的稳态误差可以减小到极低的程度,该方法控制精度高,实现简单,与传统的基于时延内模的重复控制方法相比,具有对非重复性干扰不敏感的优点,仿真结果验证了该方法的有效性。     

离散自适应重复控制: 收敛性分析与实现

针对周期已知情形下的离散周期时变系统, 提出一种自适应重复控制方法, 参数估计采用带死区修正的重复学习投影算法. 关键技术引理在分析离散自适应控制系统时起到了关键作用, 通过推广这一引理, 文中给出重复域关键技术引理, 用于证明离散自适应重复控制系统的稳定性和收敛性. 理论分析表明, 系统的输入和输出信号均有界; 且当周期数趋于足够大时, 跟踪误差收敛于一邻域中, 其半径为干扰的界. 在直线电机实验装置上的应用结果验证了 所提出重复控制方法的有效性.     

Separated design of robust model predictive control for LPV systems with periodic disturbance

To eliminate the steady-state error of systems with periodic disturbance, the repetitive control (RC) is a useful approach. For practical applications, the controller is designed to both steer system output to a given set-point (or track a given reference signal) and reject periodic disturbance. The learning procedure of RC and the control action to steer system output to a set-point may influence each other and prolong the convergence time RC. In order to reduce this interaction, this paper proposes a separated design approach. A linear parameter varying (LPV) system is considered. A repetitive predictive control (RPC) and a robust model predictive control (RMPC) are separately designed, respectively, corresponding to reject the periodic disturbance and steer system output to the set-point. The convergence of the proposed RPC sub-controller is derived. The numerical examples show that the proposed design is effective.     

Analysis and Estimation of Tracking Errors of Plug-in Type Repetitive Control Systems

Subject to stability constraints, tracking performance of a plug-in type repetitive control system with periodic inputs is explored in this note. An upper bound for the square integral of the tracking error over one time period of periodic input signals is derived based on Fourier analysis. The magnitude and the decay rate of the tracking error can be estimated using the harmonics of the input signal within the designed bandwidth. Both computer simulations and experimental results are presented to illustrate the effectiveness of the proposed method. It is also shown that the tracking error can decay significantly in the first two time periods in the proposed repetitive control system if the required bandwidth conditions are satisfied.     

融合迭代学习与干扰观测器的压电微动平台精密运动控制

针对运动系统中常见的重复参考轨迹,尽管迭代学习控制（iterative learning control,ILC）可以通过迭代有效消除重复误差,但其对于非重复性干扰十分敏感．为实现在非重复干扰环境下压电微动平台的精密运动,提出了融合ILC与干扰观测器（disturbance observer,DOB）的控制策略．为避免复杂的迟滞建模,将迟滞非线性视为迭代过程中的重复性输入干扰．为保证控制策略的稳定性,推导其收敛条件并分析对非重复性干扰的抑制作用从而降低收敛误差．最后在压电微动平台进行了对比实验,结果表明：所提控制策略可以在无迟滞模型的前提下有效补偿迟滞非线性．针对理想环境下的5Hz、10Hz、20Hz三角波跟踪,其跟踪误差的均方根在行程的0.4%以内;而在非重复干扰环境下,跟踪误差的均方根为10.24nm,与内置的控制器、单独的反馈控制器、ILC相比,分别降低了98.73%、98.67%与88.24%．而且在干扰环境下,所提控制策略加快了ILC的收敛速度．实验结果充分验证了所提控制策略的有效性,实现了压电微动平台的精密运动．     

姿态变化一致有界的姿态稳定控制器设计

针对航天器姿态稳定控制问题, 设计一种迭代学习姿态控制器. 将连续非周期运动的姿态跟踪过程分解为队列重复运动, 采用前一周期的姿态跟踪误差修正后一周期的控制输入, 分别对未知参数和干扰构建有界迭代学习律, 给出航天器姿态稳定控制器, 并从理论上分析了闭环系统的渐近稳定性和姿态跟踪误差的一致有界性. 通过在轨捕获非合作目标过程中航天器姿态跟踪控制问题的数值仿真, 验证了迭代学习控制器的鲁棒性和强抗干扰性.

     

Design of noise and period-time robust high-order repetitive control, with application to optical storage

Repetitive control is useful if periodic disturbances or setpoints act on a control system. Perfect (asymptotic) disturbance rejection is achieved if the period time is exactly known. The improved disturbance rejection at the periodic frequency and its harmonics is achieved at the expense of a degraded system sensitivity at intermediate frequencies. A convex optimization problem is defined for the design of high-order repetitive controllers, where a trade-off can be made between robustness for changes in the period time and for reduction of the error spectrum in-between the harmonic frequencies. The high-order repetitive control algorithms are successfully applied in experiments with the tracking control of a CD-player system.     

Desired Compensation Adaptive Repetitive Control of Electrical‐Optical Gyro‐Stabilized Platform with High‐Precision Disturbance Compensation

In this paper, the influences of unknown disturbances are first analyzed, and the structural properties of the disturbances are given. By appropriately applying Fourier series approximation, a novel continuously differentiable nonlinear friction model is synthesized by modifying the traditional piecewise continuous LuGre model, then a desired compensation version of the proposed adaptive repetitive controller is developed for precise tracking control of servo systems to compensate for spatial periodic disturbance and random disturbance. To further reduce noise sensitivity and improve tracking accuracy, the desired compensation robust control term is also constructed to effectively attenuate the effect of approximation errors, and thus a theoretically asymptotic tracking performance is achieved by the proposed controller, which is very important for the high accuracy tracking control of servo systems. Extensive comparative experimental results are obtained to verify the high‐performance nature of the proposed control strategies.     

Compensation for state‐dependent nonlinearity in a modified repetitive control system

This paper presents an estimation and compensation of state‐dependent nonlinearity for a modified repetitive control system. It is based on the equivalent‐input‐disturbance (EID) approach. The nonlinearity is estimated by an EID estimator and compensated by incorporation of the estimate into the repetitive control input. A two‐dimensional model of the EID‐based modified repetitive control system is established that enables the preferential adjustment of control and learning actions by means of 2 tuning parameters. The singular‐value‐decomposition technique and Lyapunov stability theory are used to derive a linear‐matrix‐inequality–based asymptotic stability condition. Exploiting the stability condition and an overall performance evaluation index, a design algorithm is developed. Simulation results for the tracking control of a chuck‐workpiece system show that the method not only compensates state‐dependent nonlinearity but also improves the tracking performance for the periodic reference input, thereby demonstrating the validity of the method.