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Recent update information-based dynamic linearization self-adaptive control law algorithm for SISO system

An adaptive control and linearization technology, applied in the direction of adaptive control, general control system, control/adjustment system, etc., can solve problems such as low precision, poor convergence, and weak trajectory tracking ability, and achieve good tracking Ability, strong convergence, rich and flexible parameter adjustment methods

Inactive Publication Date: 2017-07-18
HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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AI Technical Summary

Problems solved by technology

[0002] The traditional model-free adaptive control (MFAC) algorithm has weak trajectory tracking ability, low precision, poor convergence, and simple adjustment method

Method used

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  • Recent update information-based dynamic linearization self-adaptive control law algorithm for SISO system
  • Recent update information-based dynamic linearization self-adaptive control law algorithm for SISO system
  • Recent update information-based dynamic linearization self-adaptive control law algorithm for SISO system

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Embodiment Construction

[0025] specific implementation plan

[0026] The present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings.

[0027] A general nonlinear discrete-time system can be expressed as:

[0028]

[0029] in, y(k-1)...y(k-n)}, μ(k-2)…μ(k-m)}, μ(k) and y(k) are the input and output of the system respectively, f(*) is any nonlinear function, m and n are the unknown order of the system respectively . attached figure 1 middle, y * (k+1) is the tracking signal expected by the system.

[0030] The dynamic linearization parameter pseudo partial derivative identification model of single-input single-output SISO system is decomposed into two dynamic linearization parameter sub-identification models for input and output respectively and as follows:

[0031]

[0032]

[0033] Use the projection method to identify the two sub-identification models decomposed above and and get its estimation algo...

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Abstract

The invention proposes a dynamic linearization adaptive control law algorithm based on the latest updated information for a single-input single-output system. The purpose of the algorithm is to solve the problems of low tracking accuracy and weak convergence of the identification algorithm of adaptive control. The algorithm adopts the principle of matrix inversion and hierarchical identification method to carry out online identification and latest information update of the pseudo partial derivative of the dynamic linearization parameter of the nonlinear system, and sets the reset condition of the pseudo partial derivative, and then combines the model-free adaptive control law, thus forming a series of new dynamic linearization adaptive control law algorithms based on the latest updated information for single-input single-output systems. The adaptive control algorithm is run by adjusting weight factors, step factors, initial conditions, and reset conditions. Compared with the prior art, the present invention has stronger convergence and better restraint ability to overshoot, oscillation, etc.; has higher output precision and better adjustment ability, and has richer and more flexible parameter adjustment methods.

Description

technical field [0001] The invention relates to the technical field of model-free adaptive control, in particular to a dynamic linearization-based adaptive control algorithm for single-input and single-output systems. Background technique [0002] The traditional model-free adaptive control (MFAC) algorithm has weak trajectory tracking ability, low precision, poor convergence, and simple adjustment method. Contents of the invention [0003] In order to overcome the deficiencies of the prior art, the present invention provides a dynamic linearization adaptive control law algorithm based on latest updated information. For reaching above-mentioned object, the present invention realizes by following technical scheme: [0004] A dynamic linearization adaptive control law algorithm based on the most recently updated information of a SISO system, the algorithm decomposes the dynamic linearization parameter pseudo partial derivative identification model of a single-input single-o...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 吴爱国胡志勇张颖
Owner HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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