Titlebook: Iterative Learning Control; Analysis, Design, In Zeungnam Bien,Jian-Xin Xu Book 1998 Springer Science+Business Media New York 1998 Nonlinea

溫室

Design of an Iterative Learning Controller for a Class of Linear Dynamic Systems with Time-Delay andith time-delay, erratic estimation of delay time may cause the control input to diverge. In order to resolve such a difficulty due to uncertainty of the delay time, a new ILC algorithm is proposed, in which the holding mechanism is adopted to hold the control input at a constant value for the durati

圓桶

Manifest

共同生活

Model Reference Learning Control with a Wavelet Networkarity cannot be neglected if a driving point varies in a large region. In this chapter, we present a Model Reference Learning Control(MRLC) with a wavelet network as one of methods which don’t neglect the nonlinearity. MRLC estimates the characteristics of a controlled object by learning through rep

叢林

Neural-Based Iterative Learning Controlning controller (ILC) is used for a process of short term memory involved in a temporary learning manipulation and a storage of a specific temporary action. The leaxning gain of the iterative learning law is estimated by using a neural network for an unknown system except relative degrees. The contr

ADORN

Adaptive Learning Control of Robotic Systems and its Extension to a Class of Nonlinear Systemschieves system stability and boundedness by using the feedback controller coupled with nonlinear or fuzzy compensator and achieves precise tracking by using the iterative learning rules. In the feedback plus adaptive compensator unit, the feedback control part stabilizes the overall closed-loop syst

冷淡一切

Direct Learning Control of Non-Uniform Trajectoriespre-obtained control profiles are chosen properly, the desired control input can be obtained directly and precisely by using DLC without repeated learning process. Singularity problems have been discussed and a revised algorithm is proposed to deal with these problems. Through several sets of simula

lethal

羅盤

past control informa- tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in Iterative Learning Control: first the long term memory components are used to store past control infor- mation, then the stored control informat

HALO