Trajectory updating integrated prediction ILC (Iterative Learning Control) algorithm under restricted conditions

A technology of iterative learning control and comprehensive prediction, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve problems such as reducing the efficiency of solving problems and not making full use of it

Active Publication Date: 2017-07-07
TSINGHUA UNIV
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Problems solved by technology

However, this method does not make full use of the degrees of freedom of those non-specific ...

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  • Trajectory updating integrated prediction ILC (Iterative Learning Control) algorithm under restricted conditions
  • Trajectory updating integrated prediction ILC (Iterative Learning Control) algorithm under restricted conditions
  • Trajectory updating integrated prediction ILC (Iterative Learning Control) algorithm under restricted conditions

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Embodiment Construction

[0113] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0114] The following describes the integrated prediction iterative learning control algorithm for trajectory update under restricted conditions in the embodiment of the present invention with reference to the accompanying drawings.

[0115] At present, the effect of controlling the intermittent production process through traditional control methods is not very good. In related technologies, the iterative learning control method reduces the requirement for the accuracy of the system model. However, the trajectory tracking problem ...

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Abstract

The invention provides a trajectory updating integrated prediction ILC algorithm under restricted conditions, and aims at problems in point-to-point tracking control in an intermittent process. Under the condition that input and output of a controlled system are restricted (including restriction of the direct input size, restriction of input change in time and batch orientations and restriction of the output size), trajectory tracking and error convergence tracking are realized, the advantage that a trajectory update algorithm takes both time orientation performance and utilization of the freedom degree of non-key points into consideration is reserved, the convergence speed is higher and the tracking error is lower compared with a traditional algorithm, input and output restricted conditions are taken into consideration, and the tracking error is lower, the anti-interference capability is higher and the application range is wider compared with a restriction-free trajectory update algorithm.

Description

technical field [0001] The invention relates to the technical field of automatic control, in particular to a track update comprehensive prediction iterative learning control algorithm under restricted conditions. Background technique [0002] The batch production process is a production method in which the manufacturing process is repeated in batches, and there is a certain intermittent time between batches. In industrial fields such as biological products, pharmaceutical production, fine chemicals, and semiconductor integrated circuits, batch production processes are widely used, especially in small-batch, multi-variety, and high-value-added industrial products. [0003] In order to ensure the high quality and stability of the product, the control of the production process is particularly important. However, the batch production process usually has the characteristics of discontinuity, instability, strong nonlinearity and time variation. It is very difficult to establish a...

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 窦珊王凌锋熊智华洪英东
Owner TSINGHUA UNIV
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