共查询到20条相似文献,搜索用时 15 毫秒
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提出一种基于周期信号的迭代学习控制方法,并将其应用于电力逆变器,分析了跟踪误差沿迭代方向的收敛条件,给出了控制律的时域表达形式以及参数的确定方法.由于该方法理论上可实现跟踪误差收敛到零,因而使逆变器输出电压跟踪精度大幅提高.通过MATLAB/Simulink仿真,该方法的有效性得到验证;此外,与传统PID控制相比,仿真结果显示出该方法具有较好的负载适应能力以及优越的跟踪性能. 相似文献
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针对受非重复扰动作用的离散线性系统的输出跟踪控制问题,提出一种基于参考轨迹更新的点到点迭代学习控制算法.首先通过构建性能指标函数对控制器进行范数优化,并给出相应的收敛性条件,使得系统输出能够跟踪上更新后参考轨迹处的期望点.其次,当系统输出端受到某批次非重复扰动的影响时,进一步通过引入拉格朗日乘子算法构造多目标性能指标函数,以优化鲁棒迭代学习控制器,达到提高收敛速度和跟踪精度的目的.最后将该算法应用于电机驱动的单机械臂控制系统中,仿真结果验证了算法的合理性和有效性. 相似文献
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提出一种鲁棒迭代学习控制的设计方法.利用混合灵敏度设计方法,控制器满足一定鲁棒性条件时就可以直接获得收敛更新规则.此外,只要学习滤波函数满足一定条件,系统跟踪误差将显著降低.仿真结果表明该方法有效性较高. 相似文献
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针对P型迭代学习算法对初始偏差和输出误差扰动敏感,以及PD型迭代学习算法容易放大系统噪声,降低系统鲁棒性的问题,研究了具有任意有界扰动及期望输出的重复运行非线性时变系统的PD型迭代学习跟踪控制算法.利用迭代学习过程记忆的期望轨迹、期望控制以及跟踪误差,给出基于变批次遗忘因子的学习控制器设计,并借助λ范数理论和Bellman-Gronwall不等式,讨论保证闭环跟踪系统批次误差有界的学习增益存在的充分必要条件,及分析控制算法的一致收敛性.本算法改善了系统的鲁棒性和动态特性,单关节机械臂的跟踪控制仿真验证了方法的有效性. 相似文献
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针对一类严格反馈非线性系统, 本文提出误差跟踪学习控制算法, 旨在解决状态约束问题和系统的初值问
题. 文中构造了二次分式型对称障碍Lyapunov函数以及二次分式型非对称障碍Lyapunov函数, 并结合反推技术来分
别设计学习控制器. 两种控制方案里分别采用积分学习律和微分–差分学习律估计未知系数. 系统跟踪误差在控制
器作用下囿于预设的界内, 从而实现迭代过程中对状态的约束; 引入期望误差轨迹, 经迭代学习后, 两种控制方案均
能够实现状态误差在整个作业区间上对期望误差轨迹的完全跟踪, 并且实现系统输出在预指定作业区间上精确跟
踪参考信号. 数值仿真结果表明了控制方案的有效性. 相似文献
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Limin Wang Yiteng Shen Jingxian Yu Ping Li Furong Gao 《International journal of systems science》2018,49(2):324-343
In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini–Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy. 相似文献
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一类输出饱和系统的学习控制算法研究 总被引:1,自引:0,他引:1
传感器饱和是控制系统中较为常见的一种物理约束. 本文针对一类含饱和输出的受限系统, 提出了两种学习控制算法. 具体而言, 首先, 对于重复运行的被控系统, 设计了开环P型迭代学习控制器, 实现在有限时间区间内对期望轨迹的完全跟踪, 并在λ范数意义下分析了算法的收敛性, 给出了含饱和输出的迭代学习控制系统的收敛条件. 进而, 针对期望轨迹为周期信号的被控系统, 提出了闭环P型重复学习控制算法, 并分析了这类系统的收敛性条件. 最后, 通过一个仿真实例验证了本文所提算法的有效性. 相似文献
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惠小健 《计算机工程与应用》2021,57(3):261-265
对迭代初值为任意值的工业机器人轨迹跟踪控制系统,提出了一种基于滑模面的非线性迭代学习控制算法,使机器人轨迹能快速、精确跟踪上期望轨迹。基于有限时间收敛原理,构建了关于机器人轨迹跟踪误差的迭代滑模面,在滑模面内,机器人轨迹跟踪误差在预定时间内收敛到零。设计了基于滑模面的迭代学习控制算法,理论证明了随着迭代次数的增加,处于任意初态的轨迹将一致收敛到滑模面内,解决了迭代学习中的任意初值问题。数值仿真验证了该算法的有效性和抗干扰能力。 相似文献
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为进一步提高工业过程控制系统的跟踪能力, 实现稳、准、快等性能, 本文利用迭代学习算法产生的各类信息, 在控制器函数拟合的基础上, 设计了一种高精度跟踪的鲁棒控制器. 首先在频域对闭环迭代学习算法进行分析, 得出迭代学习控制器等同于级联控制器的结论, 进而采用一个低阶结构的控制器去拟合误差序列与控制序列,避免了难以物理实现的高阶控制器, 最后通过对一般的工业过程对象进行实验设计, 结果表明这种控制器在快速性、无超调及控制精度上具有很好的优势, 并且具有良好的抑制干扰能力. 相似文献
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殷春武 《计算机工程与应用》2019,55(3):266-270
对存在执行器故障的连续线性时变系统,给出了PID型迭代学习容错控制律的收敛条件。对连续时变故障系统设计了一种PID迭代学习容错控制律,在[λ]范数意义下给出了故障系统PID型迭代容错控制器收敛的充要条件;基于Schur补原理和不等式变换,将容错控制器收敛条件转换成线性矩阵不等式,当迭代学习收敛速度设定时,基于线性矩阵不等式能快速确定最优迭代控制增益,避免了迭代控制增益设置的盲目性。旋转控制系统的数值仿真,验证了PID迭代容错控制器优良的容错性能和跟踪性能。 相似文献
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An Exploration on Adaptive Iterative Learning Control for a Class of Commensurate High-order Uncertain Nonlinear Fractional Order Systems
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This paper explores the adaptive iterative learning control method in the control of fractional order systems for the first time. An adaptive iterative learning control (AILC) scheme is presented for a class of commensurate high-order uncertain nonlinear fractional order systems in the presence of disturbance. To facilitate the controller design, a sliding mode surface of tracking errors is designed by using sufficient conditions of linear fractional order systems. To relax the assumption of the identical initial condition in iterative learning control (ILC), a new boundary layer function is proposed by employing Mittag-Leffler function. The uncertainty in the system is compensated for by utilizing radial basis function neural network. Fractional order differential type updating laws and difference type learning law are designed to estimate unknown constant parameters and time-varying parameter, respectively. The hyperbolic tangent function and a convergent series sequence are used to design robust control term for neural network approximation error and bounded disturbance, simultaneously guaranteeing the learning convergence along iteration. The system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapnov-like composite energy function (CEF) containing new integral type Lyapunov function, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach. 相似文献
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The tracking control problem via state feedback for uncertain current-fed permanent magnet step motors with non-sinusoidal flux distribution and uncertain position-dependent load torque is addressed: a periodic reference signal (of known period) for the rotor position is required to be tracked. A robust iterative learning control algorithm is designed which, for any motor initial condition and without requiring any resetting procedure, guarantees, despite system uncertainties: exponential convergence of the rotor position tracking error to a residual ball (centered at the origin) whose radius can be made arbitrarily small by properly setting the learning gain; asymptotic convergence of the rotor position tracking error to zero. A sufficient condition for the asymptotic estimation of the uncertain reference input achieving, for compatible initial conditions, perfect tracking is derived. Robustness with respect to a finite memory implementation of the control algorithm based on the piecewise linear approximation theory is shown to be guaranteed; satisfactory performances of a discrete-time implementation of the control algorithm are obtained in realistic simulations for the full-order voltage-fed motor. 相似文献