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Fractional order parameter adjustment controller algorithm of PI<alpha>D<beta> controller

A parameter self-tuning and controller technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problems of lack of mature technology for digital realization and parameter tuning

Inactive Publication Date: 2012-07-11
DALIAN JIAOTONG UNIVERSITY
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Problems solved by technology

[0002] Fractional PI α D. β The controller has attracted the attention of researchers in the field of control, and some specific application examples have appeared, but due to the fractional order PI α D. β The controller lacks mature technology in terms of digital realization and parameter setting, so it is still in the research stage

Method used

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  • Fractional order parameter adjustment controller algorithm of PI&lt;alpha&gt;D&lt;beta&gt; controller
  • Fractional order parameter adjustment controller algorithm of PI&lt;alpha&gt;D&lt;beta&gt; controller
  • Fractional order parameter adjustment controller algorithm of PI&lt;alpha&gt;D&lt;beta&gt; controller

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Embodiment Construction

[0042] The present invention will be further described below in conjunction with the accompanying drawings.

[0043] figure 1 Provided is a fractional-order parameter self-tuning controller structure diagram, and what is provided in the solid line box in the figure is the Tustin operator fractional-order parameter self-tuning controller based on the neural network proposed by the present invention, the fractional-order PI α D. β The five tunable parameters of the controller are given by figure 2 The neural network is given. figure 2 Given is a neural network consisting of an input layer, a hidden layer and an output layer, in the figure (e, e -1 ,ce,ce -1 ) and (k p , k i , k d , α, β) are the input and output of the neural network; w ij and w li are the weight connections from the input layer to the hidden layer and from the hidden layer to the output layer, respectively; represent the output of each layer node respectively.

[0044] The problem that the presen...

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Abstract

The invention discloses a fractional order parameter adjustment controller algorithm of a PI<alpha>D<beta> controller, which comprises the following steps of: bestowing an initial right to a neural network; calculating a change rate of errors through system output errors obtained by control periods so as to obtain an input variable of the neural network; positively calculating outputs of a hidden layer and an output layer of a network by applying formulas (1)-(8) according to a selected transfer function; calculating a system output error; and judging whether the system output error meets the error requirement. Because parallel regulation is carried out by adopting the neural network, thus compared with the linear time-invariant integer order PID controller adopted commonly at present, a fractional order parameter adjustment controller has the great advantage in the adaptability. According to the fractional order parameter adjustment controller algorithm, parameters can be automatically adjusted, and the parameters obtained by the adjustable during the use are fixed; and the parameters can be automatically adjusted in real time in an application process. The invention can realize automatic adjustment of the parameters under the condition of different objects, and realizes optimal control property.

Description

technical field [0001] The invention relates to an automatic control technology, especially a PI α D. β Controller fractional order parameter tuning controller algorithm. Background technique [0002] Fractional PI α D. β The controller has attracted the attention of researchers in the field of control, and some specific application examples have appeared, but due to the fractional order PI α D. β The controller lacks mature technology in terms of digital realization and parameter setting, so it is still in the research stage. The mathematical model of the fractional order controller can be expressed by the following formula [0003] G ( s ) = U ( s ) E ( s ) = K p ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
Inventor 李文赵慧敏聂冰邓武
Owner DALIAN JIAOTONG UNIVERSITY
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