本文则将鞅理论应用于迭代学习控制中。
In this paper, martingale theory is used in iterative learning control.
提出了一类离散系统的最优迭代学习控制方法。
In this paper, an optimal iterative learning control scheme for discrete systems is presented.
型迭代学习控制律是迭代学习控制的一种主要学习律。
D-type iterative learning control (ILC) law is one of the main laws of ILC.
传统的D型迭代学习控制律依赖于被控系统的相对度。
The classical D-type ILC law depends on the relative degree of the controlled system.
对非正则系统的迭代学习控制，需要采用高阶微分学习律。
And high order differential learning law must be adapted for irregular systems.
本文主要讨论了带时滞超前PD型迭代学习控制的初值问题。
This article mainly study the initial value problem of time-delayed PD-type ILC.
这类新算法与目前所有迭代学习控制算法不同，具有非线性结构。
The new algorithm is different from the algorithms of iterative learning control proposed recently, and is with nonlinear structure.
在神经网络辨识的基础上，提出一种新的鲁棒迭代学习控制方法。
Using identification of neural networks, a new method of robust iterative learning control algorithm is proposed in the paper.
针对不确定的线性系统，研究鲁棒梯度型迭代学习控制的设计问题。
Robust gradient-type iterative learning control (ILC) was studied for a class of uncertain linear systems.
基于2- D线性系统理论研究了迭代学习控制的收敛性问题。
运用即时学习算法来解决一类非线性系统的迭代学习控制初值问题。
A method is proposed to solve the problem of the initial control input using lazy learning method.
传统的D型迭代学习控制的控制律设计方案依赖于被控系统的相对度。
The design scheme of the classical D-type iterative learning control law depends on the relative degree of the controlled systems.
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。
For repetitive movements of the objects, iterative learning control is an positive and effective control method.
针对具有可重复工作方式的机器人，提出了一种PD迭代学习控制方法。
In this paper a PD iterative learning control method for robots with repetitive operation is proposed.
研究结果表明，采用迭代学习控制算法可以有效地提高力系统的跟随精度。
The research results show that using iterative learning control algorithm can improve the tracing accurate of the force system.
本文研究系统状态初值漂移和系统参数扰动对迭代学习控制算法收敛性的影响。
In this paper, the influence about system initial shift and system parameter disturbance on convergence of the algorithm is studied.
通过大量试验得到迭代学习因子的变化规律，从而采用变因子p型迭代学习控制。
P mode iterative learning control with variable learning factor is adopted in this paper.
开环迭代学习控制学习周期长，在迭代学习的初期容易出现不稳定和高增益的现象。
But the learning period of opened-loop iterative learning control is long, and the unstable and high gain phenomena may be taken place during the initial stage of iterative learning control.
迭代学习算法设计一直是迭代学习控制研究的重点，本文从一些新的视角做了探讨。
Designs of the iterative learning algorithms, the most important problems in the ILC, are also studied in this dissertation.
迭代学习控制是一种能有效处理重复性跟踪问题或周期性干扰抑制问题的控制方法。
Iterative learning control is one kind of control methodology effectively dealing with repeated tracking control problems or periodic disturbance rejection problems.
对一类连续系统的迭代学习控制问题进行了讨论，提出了一种新的迭代学习控制算法。
A discussion is made on the iterative learning control for a class of continuous systems.
针对非线性离散时变系统的迭代学习控制问题，提出了一种改进的迭代学习控制算法。
Aimed at the problem of iterative learning control for nonlinear discrete time-variant system, the improved iterative learning control algorithm is given.
利用状态反馈部分线性化技术研究了一类非线性相似组合大系统的迭代学习控制问题。
A class of nonlinear composite large-scale systems with similar structure is analyzed by using partially linearization technique.
考虑到两连杆机械臂的实际执行过程，D型迭代学习控制并不能达到仿真结果中的效果。
Considering the real execution of a two-link robotic manipulator arm, D-type ILC can't achieve the effects of simulation results.
对一类不确定非线性系统，包括不确定性机器人，提出一种自适应鲁棒迭代学习控制方案。
An adaptive robust iterative learning control scheme is developed for a class of uncertain nonlinear systems, including robotics as a subset.
对于完成重复轨迹跟踪任务的系统，迭代学习控制是一种能有效地改进其跟踪性能的技术。
Iterative learning control is an effective technique for improving the tracking performance of systems that execute the same trajectory motion again and again.
针对具有噪声的工业过程稳态优化进程，提出迭代学习控制以期改善控制系统的动态品质。
The iterative learning control is studied for the procedure of industrial process steady state optimization in order to improve the dynamic performance of control systems.
提出了一个新的迭代学习控制(ilc)更新律用于连续线性系统的有限时间区间跟踪控制。
A new iterative learning control (ILC) updating law is proposed for the tracking control of continuous linear system over a finite time interval.
然后，文章针对非线性离散时变系统的迭代学习控制问题，提出了一种改进的迭代学习控制算法。
Then, aimed at the problem of iterative learning control for nonlinear discrete time-variant system, the improved iterative learning control algorithm was given in the paper.
一些仿真结果表明给出的依条件期望稳定的合理性，改进的迭代学习控制律和稳定性定理的有效性。
Some simulation results show the rationability of stable in the conditional expectation and the efficiency of improved iterative learning control law.
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