输入具有齿隙非线性特性的周期系统的自适应控制

针对一类输入含齿隙非线性动态特性的周期时变系统, 在周期不确定性可时变参数化的条件下设计自适应控制器. 对周期时变参数进行傅里叶级数展开, 并采用微分自适应律估计未知傅里叶系数和齿隙动态特性参数, 通过鲁棒方法消除截断误差和齿隙模型的有界误差项对系统性能的影响. 采用双曲函数替代符号函数确保控制器可微, 同时能有效抑制颤振. 引入Δ函数, 避免参数估计发散, 并保证系统输出渐近跟踪理想轨迹. 理论分析与仿真结果表明, 闭环系统所有信号有界.     

具有输入齿隙的一类非线性不确定系统自适应鲁棒控制

针对一类具有未知输入齿隙、参数不确定以及未建模动态和干扰的非线性系统,设计了自适应鲁棒控制器.将齿隙非线性模型等价表示为具有有界建模误差的全局线性化模型,在此基础上设计了包含自适应模型补偿、反馈稳定和鲁棒反馈3部分的自适应鲁棒控制器,并给出了系统动态跟踪误差和稳态误差指标.理论分析证明,闭环控制系统信号有界且跟踪误差在任意期望的精度范围内,仿真研究验证了所提出方法的有效性.     

具有未知死区输入非线性系统的迭代学习控制

针对一类具有死区输入非线性系统,提出一种实现有限作业区间轨迹跟踪控制的神经网络迭代学习算法.基于Lyapunov-like方法设计学习控制器,回避了常规迭代学习控制中受控系统非线性特性需满足全局Lipschitz连续条件的要求.为处理输入死区,利用神经网络逼近这种强非线性特性;同时,通过对神经网络逼近误差界的估计并在控制器中设置补偿作用以消除其影响,从而提高系统的跟踪性能.     

离散非线性时变系统开闭环PI型迭代学习控制律及其收敛性

对于具有重复运动性质的对象,迭代学习控制是一种有效的控制方法.针对一类离散非线性时变系统在有限时域上的精确轨迹跟踪问题,提出了一种开闭环PI型迭代学习控制律.这种迭代律同时利用系统当前的跟踪误差和前次迭代控制的跟踪误差修正控制作用.给出了所提出的学习控制律收敛的充分必要条件,并采用归纳法进行了证明.最后用仿真结果对收敛条件进行了验证.     

连续非线性系统的迭代学习控制方法*

本文根据误差收敛准则,提出了连续非线性系统的迭代学习控制算法,给出了ＰＩＤ型学习控制算法的收效条件,实际应用表明,该方法可以逼近预定的任意轨线。     

非线性系统闭环P型迭代学习控制的收敛性

本文得到并证明了当被控系统的状态方程为一类非线性方程时,采用闭环Ｐ型学习律迭代学习控制的收敛的充分条件和必要条件,最后,我们给出了典型的仿真结果。     

非线性参数化系统自适应迭代学习控制

研究一类含有未知时变参数的非线性参数化系统的学习控制问题.利用参数分离技术和信号置换思想,通过置换系统方程,合并所有时变参数为一个未知时变参数,用迭代自适应方法估计该未知参数,设计了一种自适应迭代学习控制方法,使得跟踪误差的平方在一个有限区间上的积分渐近收敛于零.通过构造一个类Lyapunov函数,给出了跟踪误差收敛和所有闭环系统信号有界的一个充分条件.仿真结果验证了该方法的有效性.     

机器人系统有限时间自适应迭代学习控制

研究任意初态下;机器人系统的有限时间自适应迭代学习控制方法。引入初始修正吸引子的概念;构造一个含有初始修正项的误差变量。针对定常机器人系统和时变机器人系统;采用Lyapunov-like方法;分别设计迭代学习控制器处理系统中不确定性。并且;采用未含/含限幅学习机制;保证闭环系统各变量的一致有界性和误差变量在整个作业区间一致收敛性。藉以实现跟踪误差在预先指定区间的完全跟踪。仿真结果验证所设计控制方法的有效性。     

非线性系统的PD型迭代学习控制

非线性系统的ＰＤ型迭代学习控制孙明轩黄宝健张学智（西安工业学院电子系西安７１００３２）关键词初始条件问题,迭代学习控制,非线性系统．１）国家自然科学基金资助项目．收稿日期１９９６－０７－２５１引言运用迭代学习控制技术设计控制器时,只需要通过重复操作获...     

非线性时变系统开闭环P型迭代学习控制的收敛性

对于非线性时变系统,给出了其开闭环P型迭代学习控制收敛的充要条件.这些收敛条件与被控系统状态方程的具体形式无关.对比表明,该文的结论改进了现有结果.     

Necessary and sufficient condition for convergence of iterative learning algorithm

This correspondence is concerned with an iterative learning algorithm for MIMO linear time-varying systems. We provide a necessary and sufficient condition for the existence of a convergent algorithm. The result extends the main result in Saab (IEEE Trans. Automat. Control 40(6) (1995) 1138).     

非参数不确定系统的有限时间迭代学习控制

针对任意初态情形,引入初始修正作用,研究一类非参数不确定时变系统能够达到实际完全跟踪性能的迭代学习控制方法. 采用Lyapunov-like综合,设计迭代学习控制器处理不确定性时变系统非参数化问题,其中含有有限时间控制作用,以实现在预先指定区间上的零误差跟踪. 并且,运用完全限幅学习机制,保证闭环系统中各变量的一致有界性以及跟踪误差的一致收敛性. 仿真结果表明了所提出控制方法的有效性.     

Adaptive inverse compensation for actuator backlash with piecewise time-varying parameters

Existing adaptive inverse compensation methods for cancelling actuator backlash nonlinearity are all restricted to handle constant backlash parameters. In other words, when discontinuity and time variation as both ubiquitous phenomena in practical actuators exist, such inverse compensation methods are no longer applicable theoretically. So far, no result has been reported in addressing such an issue, regardless of its importance in practice. In this paper, we solve this problem by developing a new piecewise Lyapunov function analysis and using parameter projection adaptation mechanism. Based on such approaches, an adaptive inverse compensation control scheme is designed to compensate for piecewise time-varying actuator backlash nonlinearity. It is proved that all signals of closed-loop system are ensured bounded. Moreover, the steady-state error is bounded by an adjustable scalar approaching to zero arbitrarily. Simulation also illustrates the obtained theoretical results.     

ITERATIVE LEARNING CONTROL IN FEEDBACK SYSTEMS BASED ON AN OBJECTIVE FUNCTION

An objective function is proposed and an iterative learning control algorithm is derived based on this. The objective function is a quadratic form consisting of the output error and the input. By adjusting the weights in the objective function, the control objective of good command following at smaller input energy can be realized. The weight on the input energy in the objective function is shown to be directly related to the forgetting factor for robust iterative learning control. The convergence of the control algorithm has been proven and its characteristics are shown in the simulation examples.     

严格反馈非线性时变系统的迭代学习控制

针对一类含未知时变参数的严格反馈非线性系统, 提出一种实现有限作业区间轨迹跟踪控制的迭代学习算法. 基于Lyapunov-like方法设计控制器, 回避了常规迭代学习控制中受控系统非线性特性需满足全局Lipschitz连续条件的要求. 以反推设计(Backstepping)方法设计控制器, 为使得虚拟控制项可导, 引入一级数收敛序列; 将时变参数展开为有限项多项式形式, 在控制器设计中采取双曲正切函数处理余项对于系统跟踪性能的影响. 理论分析表明, 闭环系统所有信号有界, 并能够实现系统输出完全收敛于理想轨迹.     

一种新的非线性离散时间系统迭代学习控制的前馈－反馈机制

This paper presents a new feedback-feedforward configuration for the iterative learning control (ILC) design withfeedback, which consists of a feedback and a feedforward component. The feedback integral controller stabilizes the system,and takes the dominant role during the operation, and the feed-forward ILC compensates for the repeatable nonlinear/unknowntime-varying dynamics and disturbances, thereby enhancing the performance achieved by feedback control alone. As the mostfavorable point of this control strategy, the feedforward ILC and the feedback control can work either independently or jointlywithout making efforts to recongurate or retune the feedforward/feedback gains. With rigorous analysis, the proposedlearning control scheme guarantees the asymptotic convergences along the iteration axis.     

Networked iterative learning control approach for nonlinear systems with random communication delay

This paper constructs a proportional-type networked iterative learning control (NILC) scheme for a class of discrete-time nonlinear systems with the stochastic data communication delay within one operation duration and being subject to Bernoulli-type distribution. In the scheme, the communication delayed data is replaced by successfully captured one at the concurrent sampling moment of the latest iteration. The tracking performance of the addressed NILC algorithm is analysed by statistic technique in virtue of mathematical expectation. The analysis shows that, under certain conditions, the expectation of the tracking error measured in the form of 1-norm is asymptotically convergent to zero. Numerical experiments are carried out to illustrate the validity and effectiveness.     

非线性系统的一种加权自适应控制方法

非线性系统的一种加权自适应控制方法１）许向阳祝和云（浙江大学工业控制研究所杭州３１００２７）关键词自适应控制,非线性系统,间隙非线性．１）国家级工业控制技术重点实验室资助课题．收稿日期１９９５－０３－０７１引言由于非线性系统的多样性,不能用统一的模型...