低频线振动台加速度失真非线性补偿控制方法

为了抑制低频线振动台中存在的模型不确定性及外部扰动,基于模糊基函数网络(FBFN)提出了一种自适应重复学习控制方法.利用FBFN逼近低频线振动台的模型不确定性及外部扰动,将对模型不确定性和扰动的辨识问题转化为对FBFN权系数的辨识问题.所提出的控制律由自适应控制和重复学习控制组成.自适应律用来估计FBFN权系数;为了有效地减弱抖振,使用自适应PI控制结构逼近非连续控制.由于非连续控制的界是未知的,利用自适应律估计这个未知的界.重复学习控制用来提高系统对周期性输入信号的跟踪性能.采用Lyapunov理论设计的自适应重复学习控制律保证了低频线振动台的渐近稳定性和位置跟踪性能.仿真结果表明,自适应重复学习控制律改善了系统的跟踪性能和加速度失真度.     

永磁直线同步电机的鲁棒自适应神经网络控制

针对永磁直线同步电动机的端部效应和非线性摩擦问题,采用一种鲁棒自适应神经网络控制方法,实现了永磁直线电机的跟踪控制.所设计的控制器包含两个部分:一部分是自适应神经网络控制器,用来逼近理想控制器,该神经网络的输入为滑模切换函数;另一部分是鲁棒控制器,用来消除逼近误差.通过李亚普诺夫稳定性定理验证了所设计的控制器能够保证控...     

基于永磁直线同步电机的光刻机掩模台鲁棒自适应神经网络控制

针对光刻机掩模台宏动永磁直线同步电机(PMLSM)提出一种鲁棒自适应神经网络轨迹跟踪补偿控制策略。该策略的主要特点是采用径向基函数(RBF)神经网络实时在线进行模型参数不确定性和各种外界非线性扰动的估计。为了验证策略的效果,建立基于参数不确定性和外界非线性扰动的掩模台宏动PMLSM模型,并针对此模型进行控制策略的规划、推导和稳定性理论分析,分析结果说明该策略可以保证位置和速度跟踪误差的收敛性。通过在光刻机掩模台上进行的五阶S曲线跟踪控制实验验证了此控制策略的实际控制效果,实验结果显示跟踪准确度达到了满意的效果。由于此控制策略的最大优点是不需要对实际物理系统参数和难于测量的外界不确定性扰动做精准的建模,所以非常适合应用在超精密运动控制领域。     

永磁直线同步电机的混合鲁棒最优-H∞控制

为了解决永磁直线同步电机运行过程中对系统参数扰动及端部效应等不确定因素敏感的问题,提出了一种PMLSM的混合鲁棒最优-H∞控制方法。利用最优线性二次（LQ）控制器与Riccati方程结合讨论的思想把最优控制方法、鲁棒镇定方法等结合起来,形成混合鲁棒最优-H∞控制。利用鲁棒最优控制策略、-H∞控制策略设计了永磁直线同步电机的混合鲁棒最优-H∞控制器,该控制器对于较大的外部扰动、内部非线性扰动都能够很好的消除,且控制规律简洁,易于工程实践。数字仿真结果表明与传统PID控制方式比较,混合鲁棒最优-H∞控制器具有很强的鲁棒性和跟踪性。     

永磁直线电机自适应反推滑模鲁棒跟踪控制

针对高速高精伺服系统,考虑永磁直线同步电机(PMLSM)参数变化、外部负载扰动和摩擦力等不确定因素对系统伺服性能的影响,设计自适应反推滑模控制器(ABSMC).由系统位置、速度误差建立滑模面,利用反推理论推导出反推滑模控制律.实际应用中不确定确界未知,通过设计自适应律修正不确定确界观测值.经分析验证,并与反推滑模控制相比,自适应反推滑模算法在保证系统全局一致渐进稳定情况下,能很好抑制不确定因素对系统性能的影响,对参考指令位置跟踪鲁棒性强,同时抖振得到明显削弱.     

机器人的鲁棒自适应分散跟踪控制

提供了一种鲁棒自适应控制策略,用于不确定性机器人的发迹跟踪,该控制器由一个ＰＤ线性反馈、一个立方项偿和非线性项构成。控制律采用分散形式,通过对二自由度机器人的仿真,证明该方法能使跟踪误差快速趋近于零。     

永磁直线同步电机的自适应迭代学习控制

永磁直线同步电机驱动的伺服随动系统,既要对周期性的输入信号具有跟踪能力,又要对周期性的扰动具有抑制能力。对这一问题,从迭代学习控制的本质出发,与自适应算法相结合,提出了一种自适应迭代学习控制策略,解决了伺服系统中对周期性输入信号的跟踪问题,以及对参数摄动和不确定性干扰,尤其是对周期性扰动的抑制问题。在永磁直线同步电机位置控制实验中,将该方法与传统控制进行对比试验,实验结果表明,该方法能够有效地提高系统的位置控制精度。     

基于鲁棒迭代学习的永磁直线电机控制

针对永磁直线电机速度和位置迭代学习跟踪控制中,由测量扰动引起的跟踪误差有界收敛问题,提出一种带有衰减因子的鲁棒迭代学习控制算法.采用λ范数方法分析鲁棒迭代学习控制算法的收敛性,理论结果表明,鲁棒迭代学习控制算法可以保证跟踪误差收敛到零,而P型迭代学习控制算法仅保证直线电机速度和位置的跟踪误差收敛到一个与扰动信号上界有关的域内.仿真结果表明,所提出的鲁棒迭代学习控制算法可以有效抑制测量扰动,获得较好的跟踪性能.带有衰减因子的迭代学习控制方法是一种抑制非重复测量扰动的有效方法.     

直线永磁同步伺服电动机的鲁棒H∞控制

研究直线永磁同步伺服电动机的鲁棒H∞控制器的设计方法.应用Matlab工具箱,使最优H∞控制的求解及加权函数的优化简便可行.仿真结果表明鲁棒H∞控制器具有很强的抗扰动性能.     

采用鲁棒微分器的永磁直线同步电机二阶滑模控制

针对永磁直线同步电机伺服系统容易受到参数变化、端部效应和负载扰动等不确定性因素影响的问题，采用二阶滑模控制中的螺旋算法设计直线伺服系统的速度和电流控制器。在出现参数变化和阻力扰动时，为保证动子速度严格跟踪其参考信号，同时消除磁阻作用和推力波动的影响，分别独立选取速度和直轴电流的滑模量，并利用基于二阶滑模的鲁棒速度微分器来估计螺旋算法所需要的加速度信号。仿真结果表明该策略对负载和参数的变化具有很强的鲁棒性，同时有效地削弱了抖振现象。     

Model reference adaptive iterative learning control for linear systems

In this paper, we propose a model reference adaptive control (MRAC) strategy for continuous‐time single‐input single‐output (SISO) linear time‐invariant (LTI) systems with unknown parameters, performing repetitive tasks. This is achieved through the introduction of a discrete‐type parametric adaptation law in the ‘iteration domain’, which is directly obtained from the continuous‐time parametric adaptation law used in standard MRAC schemes. In fact, at the first iteration, we apply a standard MRAC to the system under consideration, while for the subsequent iterations, the parameters are appropriately updated along the iteration‐axis, in order to enhance the tracking performance from iteration to iteration. This approach is referred to as the model reference adaptive iterative learning control (MRAILC). In the case of systems with relative degree one, we obtain a pointwise convergence of the tracking error to zero, over the whole finite time interval, when the number of iterations tends to infinity. In the general case, i.e. systems with arbitrary relative degree, we show that the tracking error converges to a prescribed small domain around zero, over the whole finite time interval, when the number of iterations tends to infinity. It is worth noting that this approach allows: (1) to extend existing MRAC schemes, in a straightforward manner, to repetitive systems; (2) to avoid the use of the output time derivatives, which are generally required in traditional iterative learning control (ILC) strategies dealing with systems with high relative degree; (3) to handle systems with multiple tracking objectives (i.e. the desired trajectory can be iteration‐varying). Finally, simulation results are carried out to support the theoretical development. Copyright © 2006 John Wiley & Sons, Ltd.     

Robust and simple adaptive control system design

Recently, the simple adaptive control (SAC) method has attracted considerable interest because of the simple structure of its adaptive controller. The method can only be applied to plants with so-called almost strictly positive real (ASPR) characteristics. Unfortunately, most real plants do not satisfy this condition. Furthermore, real plants contain disturbances such as uncertain elements. This paper deals with such problems and proves that the implementation of a parallel feedforward compensator makes it possible to apply the SAC method to non-ASPR SISO plants with plant uncertainties. Furthermore, a robust SAC algorithm in the presence of a class of external disturbances is also considered. The effectiveness of the parallel feedforward compensator and robust adaptive controller designed in this way is examined through several numerical simulations.     

Robust adaptive dynamic surface control for linear time‐varying systems

In this paper, robust output‐feedback tracking control is considered for a class of linear time‐varying plants whose time‐varying parameters are unknown bounded with bounded derivatives and output is affected by unknown bounded additive disturbances. Using adaptive dynamic surface control technique, the proposed scheme possesses the following advantages: (1) the design procedure is simple and the control law is easy to be implemented, and (2) by introducing an initialization technique, together with adjusting some design parameters, the performance of system tracking error can be guaranteed regardless of the time variation. It is proved that with the proposed scheme, all the closed‐loop signals are semi‐globally uniformly ultimately bounded. Simulation results are presented to demonstrate the effectiveness of the proposed scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

周期性输入的直线伺服系统改进重复控制

针对直线电机驱动的凸轮加工随动系统实际加工应用中,要求系统既要对周期性输入信号具有跟踪能力,又要对周期性扰动具有抑制能力。对这一问题,根据基于内模原理的重复控制理论设计实用性强的插入型重复控制器,来消除由周期性输入的基波和谐波所引起的误差,以便减小系统周期性稳态跟踪误差。为进一步改善控制器的性能,有效地增加运行带宽,设计改进的插入型重复控制器,减小系统的跟踪误差,使得系统的跟踪性能得到更好的改善。最后,对直线伺服电机驱动的凸轮加工中心进行了仿真研究,结果表明所提出的控制方案提高了系统跟踪性能和鲁棒性能,既有效地抑制系统周期性扰动的影响,又对周期性输入信号实现准确跟踪。     

Robust gain-scheduled control for vibration suppression

Limited control authority is a key issue in the field of structural control and is a major research area since most of the practical control problems are dominated by constraints on the control signal. The paper presents a simple and practical gain-scheduled controller design procedure for active vibration suppression of a three-storey flexible structure. First, system identification experiments are performed and the plants uncertainty is derived. Next, robust controller design with constraint on the control signal is presented. For a better trade-off between control performance and control constraint a gain-scheduling approach is investigated. Stability analysis of the gain-scheduled controller is analysed using a parameter-independent Lyapunov function (quadratic stability) as well as a parameter-dependent Lyapunov function (biquadratic stability). Finally, the gain-scheduled controller is tested experimentally when the flexible structure is excited with a scaled historical earthquake record (1940 El Centro record). Successful experimental results show that the proposed robust gain-scheduled control approach offers good performance in the case of control authority limitation.Nomenclature M mass matrix - C damping matrix - K stiffness matrix - q relative displacement vector to base - m_a active mass - active mass acceleration - ground (base) acceleration - K_gap transfer gain of the displacement sensor - K_acc transfer gain of the acceleration sensor - K_AMD transfer gain of the active mass damper - _id frequency range of system identification experiments - r control reference - u control signal - d external disturbance - y control output - e control error - x state vector - p(t) time-varying parameter - N_p parameter boxs dimension - V(x) Lyapunov function - V(x,p) parameter-dependent Lyapunov function - largest parameter box where quadratic stability holds - S(s),T(s) sensitivity and complementary sensitivity transfer functions - G_n(s),G(s) transfer function of nominal and real plant - K_rate rate feedback gain - P_n(s) transfer function of nominal plant modified by rate feedback - P(s) transfer function of real plant modified by rate feedback - G_red transfer function of the reduced-order plant - _m(s) multiplicative uncertainty - W_S(s),W_T(s) performance and robustness weighting functions - G_c(s) controllers transfer function - G_c1(s),G_c2(s) transfer function of robust controller for vertex 1 and vertex 2 - G_cs(p,s) transfer function of the gain-scheduled controller - u_A amplitude of the control signal - K_min,K_max minimum and maximum controller gain - K(p) scheduled controller gain - J₁,J₂,J₃,J₄,J₅ performance evaluation parameters     

MIMO multi‐periodic repetitive control system: universal adaptive control schemes

This paper presents a simple adaptive multi‐periodic repetitive control scheme when the MIMO LTI plant is not necessarily positive real (PR), however it is strictly minimum‐phase, the spectrum of high‐frequency gain matrix CB is symmetric and lies in the open right/left half complex plane(sign/spectrum definite). The non‐identifier‐based direct adaptive control technique, which does not need plant parameter information, is used to construct adaptive schemes and the system stability is analysed by Lyapunov second method. The extension to plant under certain non‐linear perturbations and an exponential stability scheme are also discussed. Finally, an adaptive proportional plus multi‐periodic repetitive control scheme is proposed. The theoretical findings are supported with simulations. Copyright © 2006 John Wiley & Sons, Ltd.     

直线电机伺服定位系统时间最优鲁棒控制

无铁心永磁同步直线电机伺服定位系统点位运动控制中Bang-Bang控制满足庞特里亚金极小值原理条件.为确定Bang-Bang控制中的切换时间,提出一种基于粒子群优化算法的切换时间计算方法.为保证电机系统的稳定性和鲁棒性,提出先用Bang-Bang控制后用快速终端滑模控制的两阶段控制方案.系统起始阶段采用Bang-Ban...