System identification plays an important role in high performance automation technologies such as adaptive control and learning control.
系统辨识是高性能自动化技术(如适应控制与学习控制)中的重要内容。
Iterative learning control is an effective technique for improving the tracking performance of systems that execute the same trajectory motion again and again.
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 one kind of control methodology effectively dealing with repeated tracking control problems or periodic disturbance rejection problems.
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。
Direct learning control(DLC) can fully utilize the pre-stored control profiles and it can directly generate the desired control without any repetitive learning process.
直接学习控制能够充分利用系统的先前控制经验，直接产生期望控制信号，不需要任何重复的学习过程。
Iterative learning control is a new control technology, which is a branch of intelligent control theory and particularly suitable for a controlled object with a repetitive motion.
迭代学习控制是一种新兴控制技术，它是智能控制理论的一个分支，特别适合于具有重复运动特性的被控对象。
In this paper, martingale theory is used in iterative learning control.
本文则将鞅理论应用于迭代学习控制中。
D-type iterative learning control (ILC) law is one of the main laws of ILC.
型迭代学习控制律是迭代学习控制的一种主要学习律。
This paper proposes a learning control based high-speed scanning mode for an AFM system.
本文针对原子力显微镜系统，提出了一种基于学习控制的快速扫描模式。
A discussion is made on the iterative learning control for a class of continuous systems.
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。
For Variable Valve Timing (VVT) system, a kind of self-learning control method was proposed.
针对可变相位机构，提出了一种自学习型的控制方法。
In this paper, an optimal iterative learning control scheme for discrete systems is presented.
提出了一类离散系统的最优迭代学习控制方法。
In this paper a PD iterative learning control method for robots with repetitive operation is proposed.
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。
Robust gradient-type iterative learning control (ILC) was studied for a class of uncertain linear systems.
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。
In this paper, an iterative learning control scheme is proposed for a class of nonlinear uncertain systems.
本文提出一种带饱和限幅的迭代学习控制器设计方法。
The optimal control for the temperature is achieved by using self learning control based on a neural network.
运用神经网络自学习控制解决温度优化控制问题。
For repetitive movements of the objects, iterative learning control is an positive and effective control method.
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。
This paper presents an iterative learning control technique for batch processes based on time varying perturbation models.
为了克服模型与过程间的偏差，提出了一个基于时变偏扰模型的间歇过程迭代学习控制方法。
An optimal learning control method for a robot is introduced with acceleration error used to correct the motion of actuators.
为工业机器人提出了一种最优学习控制法。这种控制法用加速度误差校正驱动器运动。
It can be seen that the multiple-type iterative learning control can be used in high frequency angle-vibration table control.
结论表明这种复合迭代控制器可以应用于高频角振动转台的控制。
Using identification of neural networks, a new method of robust iterative learning control algorithm is proposed in the paper.
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。
To overcome the nonlinear effects, the discrete learning control strategy is presented. The convergence theorem is also given.
针对多指手爪的非线性影响，提出了一种位置离散学习控制方法，并给出了这种方法的收敛性定理。
The research results show that using iterative learning control algorithm can improve the tracing accurate of the force system.
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 design scheme of the classical D-type iterative learning control law depends on the relative degree of the controlled systems.
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 new algorithm is different from the algorithms of iterative learning control proposed recently, and is with nonlinear structure.
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。
Not only Intelligent control and self-learning control but also the basic principle of the iteration self-learning control are described.
概述了智能控制和自学习控制，阐述了迭代自学习控制的基本原理。
An adaptive robust iterative learning control scheme is developed for a class of uncertain nonlinear systems, including robotics as a subset.
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。
A new iterative learning control (ILC) updating law is proposed for the tracking control of continuous linear system over a finite time interval.
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。
The actual output trajectory of the system achieved better convergence to the desired trajectory by using the iterative learning control algorithm.
利用该算法进行学习控制，使系统的实际输出能更好地收敛于系统的理想输出。
A novel repetitive learning control method is proposed for the tracking or rejection of unknown periodic reference or disturbance with a known period.
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。
A novel repetitive learning control method is proposed for the tracking or rejection of unknown periodic reference or disturbance with a known period.
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。
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