Supercharge Your Innovation With Domain-Expert AI Agents!

Simulation method for self-adaptive sliding-mode control of nonlinear system

An adaptive sliding mode, nonlinear system technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., to achieve the effect of solving asymptotic stability

Inactive Publication Date: 2018-06-01
DALIAN NATIONALITIES UNIVERSITY
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem of the asymptotic stability of the closed-loop control system, and to verify the influence of the adaptive sliding mode control method on the asymptotic stability of the closed-loop control system, the present invention proposes the following scheme:

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Simulation method for self-adaptive sliding-mode control of nonlinear system
  • Simulation method for self-adaptive sliding-mode control of nonlinear system
  • Simulation method for self-adaptive sliding-mode control of nonlinear system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0017] Embodiment 1: This embodiment proposes an adaptive control slipping modeling method or system based on Lyapunov functions for a class of nonlinear systems containing uncertainties and unknown bounded external disturbances. The nonlinear function approximation ability of LS-SVM regression is used to design a feedback linearization controller, and the sliding mode control is introduced to compensate the approximation error of LS-SVM regression and the influence of uncertain external disturbance on the system output, and the Lyapunov function is used to calculate the weight parameters of LS-SVM Finally, a simulation example is used to verify the design scheme.

[0018] 1 Problem description

[0019] Consider nonlinear uncertain systems

[0020]

[0021] in is the unknown nonlinear function, b is the unknown control gain, d is the bounded disturbance, u∈R and y∈R are the input and output of the system respectively, and n is the order of the system state. Assume is...

Embodiment 2

[0088] Embodiment 2, as the system executed by the method in Embodiment 1, this embodiment includes the following scheme:

[0089] A kind of adaptive sliding mode control system of nonlinear system, stores a plurality of instructions, and described instruction is suitable for processor to load and execute:

[0090] Approximate an ideal state feedback controller using the LS-SVM structure for the nonlinear system to construct a new feedback controller;

[0091] Approximation error and / or uncertain external disturbance compensation for LS-SVM regression by applying sliding mode control to it;

[0092] Determines the weight parameter vector at an adaptive rate.

[0093] The nonlinear system is based on using the LS-SVM structure to approximate the ideal state feedback controller to construct a new feedback controller

[0094] The nonlinear system

[0095]

[0096] in: is the unknown nonlinear function, b is the unknown control gain, d is the bounded disturbance, u∈R and y∈R...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a simulation method for self-adaptive sliding-mode control of a nonlinear system. The simulation method belongs to the field of artificial intelligence and control, and is usedfor solving the problem of asymptotic stability of a closed-loop control system. The simulation method is characterized by comprising the steps of applying a self-adaptive sliding-mode control methodto the nonlinear system, setting input of LS-SVM structure regression to be x=[x1 x2]<T>, setting output to be u*, selecting 100 pairs of data from u and x data as training samples, selecting 40 pairs of data from the 100 pairs of data as test samples, regarding a mean square error of output errors of an output system as an evaluation index, calculating hyper-parameters of the LS-SVM structure regression by utilizing cross-validation optimization, carrying out learning and training again by using the hyper-parameters obtained through optimization, acquiring parameter initial values of a nonlinear feedback controller based on LS-SVM structure regression fitting, and selecting a system reference signal to be ym(t)=sin (t) and an initial state x=[0 1]<T>, and using a formula (9) for conducting on-line simulation experiment on the system.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and control, and relates to an adaptive sliding mode control method for nonlinear systems. Background technique [0002] Sliding mode variable structure control of nonlinear uncertain systems has always been a hot spot in the control field, and many scholars have achieved research results in this field. Since the sliding mode control of the nonlinear system requires a rough mathematical model of the known system, the dependence of the sliding mode control on the system model is increased. With the development of artificial intelligence theory, fuzzy logic and neural network are introduced into the design of sliding mode control, which effectively reduces the dependence of sliding mode control on the system model. Literature [3] studied the adaptive fuzzy sliding mode control of nonlinear system based on high-gain observer, and literature [4] studied the adaptive sliding mode control of nonl...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 谢春利赵丹丹
Owner DALIAN NATIONALITIES UNIVERSITY
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com