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Grid binary tree method of control system midpoint locating method

A control system and binary tree technology, applied in data processing applications, prediction, calculation, etc., can solve the problems of insufficient preprocessing time, unsatisfactory online efficiency, and unsatisfactory performance, so as to improve online computing time and reduce complexity. , the effect of reducing preprocessing time

Inactive Publication Date: 2016-06-08
ZHEJIANG UNIV OF TECH
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Problems solved by technology

Although they can actually and effectively solve the point positioning problem, they can no longer meet our control needs in terms of performance.
Compared with other point positioning methods, the traditional binary tree method has unmatched advantages in storage space requirements and online search efficiency, but its preprocessing time cannot meet the requirements of our control system. The traditional hash table method The demonstrated online efficiency also leaves us unflattered

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  • Grid binary tree method of control system midpoint locating method
  • Grid binary tree method of control system midpoint locating method
  • Grid binary tree method of control system midpoint locating method

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Embodiment Construction

[0065] The steps of the grid binary tree method of the present invention will be further described below in conjunction with the accompanying drawings. Refer to attached Figure 1-6 ,Table 1.

[0066] Grid binary tree method of the present invention, concrete steps are as follows:

[0067] Step 1. The offline preprocessing process of the grid binary tree method, see the flow chart for details Figure 4 and Figure 5

[0068] 1.1. Introduce multi-parameter quadratic programming into the control system, divide the system state space into convex partitions, and calculate the control rate corresponding to each partition, and save it in the FG array. For a schematic diagram of the state space partition, see figure 1 .

[0069] 1.2. Calculate and group the synonymous partitions by the formula used to determine the synonymous partitions. Only one eigenvalue data is reserved for each group of synonymous partitions.

[0070] 1.3. Calculate the hash function according to the part...

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Abstract

A grid binary tree method is divided into two main phases-an offline preprocessing phase and an online computation phase. The theory of multi-parameter secondary programming is introduced in the offline preprocessing phase. A computer can autonomously divide the state space of a control system into convex partitions and obtains control rate corresponding to each partition through computation. Then we construct a hash table grid area polytope according to division parameters and construct a binary tree in a grid area in which a conflict exists. In the online computation phase, firstly the located grid area is rapidly determined according to the coordinates of state points, the control rate of the state points is obtained through screening of the constructed binary tree or is directly obtained, and control output quantity of the system is obtained through simple linear operation.

Description

technical field [0001] The present invention is aimed at the optimization of the midpoint positioning method of explicit model predictive control. Compared with the traditional binary tree method, the grid binary tree method only needs to deal with fewer polytopic partition scales, reduces the complexity of preprocessing, and greatly reduces preprocessing time. At the same time, it also solves the conflict problem in the hash table method, and improves the online calculation time of the hash table method. In terms of the performance of storage space requirements, it also meets our requirements for the control system. Background technique [0002] In the traditional model predictive control, there are repeated online optimization calculations, which cause the controller to be overloaded and inefficient. In order to solve these problems, scholars such as Manfred Morari and Alberto Bemporad introduced the multi-parameter quadratic programming theory around 2002, and establish...

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Application Information

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IPC IPC(8): G06Q10/04
Inventor 张聚刘敏超胡标标林广阔
Owner ZHEJIANG UNIV OF TECH
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