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Parameter self-tuning method of siso partial scheme model-free controller based on partial derivative information

A parameter self-tuning, model-free technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the time-consuming and laborious debugging process of the SISO partial format model-free controller, and restrict the SISO partial format model-free control The popularization and application of controllers, affecting the control effect of SISO partial format model-free controller, etc., to achieve good control effect

Active Publication Date: 2020-06-09
ZHEJIANG UNIV
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  • Claims
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Problems solved by technology

The lack of effective parameter tuning methods not only makes the debugging process of the SISO partial format model-free controller time-consuming and laborious, but also sometimes seriously affects the control effect of the SISO partial format model-free controller, restricting the development of the SISO partial format model-free controller. Promote application

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  • Parameter self-tuning method of siso partial scheme model-free controller based on partial derivative information
  • Parameter self-tuning method of siso partial scheme model-free controller based on partial derivative information
  • Parameter self-tuning method of siso partial scheme model-free controller based on partial derivative information

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0042] figure 1 The principle block diagram of the present invention is given. Determine the control input linearization length constant L of the SISO partial model-free controller, L is an integer greater than 1; the parameters of the SISO partial model-free controller include the penalty factor λ and the step factor ρ 1 ,…,ρ L ; Determine the SISO partial format model-free controller to be tuned parameters, the SISO partial format model-free controller to be tuned parameters, part or all of the SISO partial format model-free controller parameters, including penalty factor λ and step size factor ρ 1 ,…,ρ L any one or combination of any of the figure 1 Among them, the parameters to be tuned for the SISO partial scheme model-free controller are the penalty factor λ and the step factor ρ 1 ,…,ρ L ; Determine the number of input layer nodes...

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Abstract

The invention discloses an offset-guiding-information-based parameter self-setting method of a single-input-and-single-output (SISO) partial-format model-free controller. Offset guiding information isused as an input of a BP neural network and the BP neural network carries out forward calculation and outputs to-be-set parameters like a penalty factor and a step-size factor of a controller throughan output layer. Calculation is carried out by using a control algorithm of the controller to obtain a control input for a controlled object; a control input is calculated; and for gradient information of all to-be-set parameters, with minimization of a value of a system error function as an objective, system error back-propagation calculation is carried out by combining the gradient informationbased on a gradient descent method. A hidden layer weight coefficient and an output layer weight coefficient of the BP neural network are updated in real time in an online manner; the gradient information is stored as offset guiding information and is used as an input of the BP neural network at a next time. With the offset-guiding-information-based parameter self-setting method, the setting problem of the parameters of the controller can be solved; and the good control effect is realized.

Description

technical field [0001] The invention belongs to the field of automatic control, and in particular relates to a parameter self-tuning method of a SISO partial format model-free controller based on partial derivative information. Background technique [0002] Model-free controller is a new type of data-driven control method, which does not rely on any mathematical model information of the controlled object, but only relies on the real-time measured input and output data of the controlled object for controller analysis and design, and realizes concise, computational The burden is small and the robustness is strong, and the unknown nonlinear time-varying system can also be well controlled, and has a good application prospect. [0003] There are many implementation methods of model-free controllers, among which SISO (Single Input and Single Output, single input and single output) partial format model-free controller is one of the main implementation methods of model-free controll...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 卢建刚李雪园
Owner ZHEJIANG UNIV
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