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Noncausal effective learning control system and method of precision motion control system

A technology of learning control and control system, applied in the direction of digital control, electrical program control, etc., can solve the problems of long dynamic adjustment time and low system work efficiency, and achieve the effect of enhancing applicability, increasing pertinence, and simple and easy implementation.

Active Publication Date: 2013-02-13
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to solve the problem that the dynamic adjustment time of the precision motion control system is long and the working efficiency of the system is low, and provides a non-causal effective learning control system and control method of the precision motion control system

Method used

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  • Noncausal effective learning control system and method of precision motion control system
  • Noncausal effective learning control system and method of precision motion control system
  • Noncausal effective learning control system and method of precision motion control system

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specific Embodiment approach 1

[0030] Specific implementation mode one: the following combination figure 1 Describe this embodiment, the acausal effective learning control system of the precision motion control system described in this embodiment, it includes control object P, this control object P is a precision motion control system, it includes acausal learning control law module, effective learning function f(t, e) module, memory M and feedback control law C module,

[0031] The acausal learning control law module consists of a time delay factor z d module, causal learning law L module and filter Q, d is the delay time parameter,

[0032] The error amount e between the reference control input quantity R of the control object P and the actual output quantity Y k Input to the memory M, the control quantity u of the memory M k Output to filter Q;

[0033] The error amount e of the memory M k gives the time delay factor z d module, time delay factor z d The output signal of the module is given to the...

specific Embodiment approach 2

[0038] Specific implementation mode two: the following combination Figure 1 to Figure 9 Describe this embodiment. This embodiment is a control method based on the non-causal effective learning control system of the precision motion control system described in Embodiment 1. It uses a memory M to store the error amount e of the iterative process k and control quantity u k , k=1, 2, 3..., k is the motion cycle,

[0039] The amount of error e in the memory M k elapsed time delay factor z d The module obtains the error amount at time t+d, and the error amount at time t+d obtains the change amount of learning control through the causal learning law L module. bad get e k moment,

[0040] At the same time, the control quantity u in the memory M k The modified control amount of the kth motion cycle is obtained through the filter Q, and the modified control amount is added to the change amount of the learning control output by the causal learning law L module to obtain the learni...

specific Embodiment approach 3

[0046] Specific Embodiment 3: This embodiment is a further description of Embodiment 2. During the motion cycle of k=1, the control amount u k = 0, error amount e k =0.

[0047] This embodiment shows that the process of effective learning control is to first set the initial condition, that is, in the first motion cycle, the initial control amount u in the memory M 1 and the error amount e 1 Both are 0. If the time range included in a motion cycle is t0~tf, and the sampling period is ts, then the dimension of the control amount and the error amount is 1+(tf-t0) / ts.

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Abstract

The invention relates to noncausal effective learning control system and method, and belongs to the technical field of control over precision motion control systems, and the system and the method are used for solving the problem that the working efficiency of the system is low due to the long dynamic regulation time of the precision motion control system. The control system comprises a control object P, a noncausal learning control law module, an effective learning function f (t, e) module, a memorizer M and a feedback control law C module, wherein the noncausal learning control law module is composed of a time delay factor zd module, a causal learning law L module and a filter Q. The control method comprises the following steps of: carrying out preliminary shaping on the learning control system by adopting the time delay factor, confirming d according to the bandwidth of a feedback system composed of P and C and then confirming the low band range meeting the convergence requirements; and shaping the high band parts through the causal learning law L module and the filter Q to enable the high band parts to meet the convergence requirements. The control system and the control method which are disclosed by the invention are suitable for the control over the precision motion control system.

Description

technical field [0001] The invention relates to a non-causal effective learning control system and a control method of a precision motion control system, belonging to the technical field of control of the precision motion control system. Background technique [0002] Precision motion control systems are widely used in industrial systems and scientific research. For example, in the semiconductor manufacturing industry, the workpiece table system of the lithography machine is a typical precision motion control system. It is used to ensure the accuracy of the dynamic exposure of the wafer, thereby ensuring that the chip Quality and production capacity play a key role in the entire semiconductor manufacturing. In recent years, with the continuous improvement of the level of science and technology, the requirements for the control accuracy of precision motion control systems have become higher and higher, and the requirements for system work efficiency have also become higher and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/414
Inventor 陈兴林姜晓明刘杨
Owner HARBIN INST OF TECH
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