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Estimation and compensation of periodic disturbance using internal-model-based equivalent-input-disturbance approach
by
Liu, Zhentao
, Wu, Min
, She, Jinhua
, Mei, Qicheng
in
Algorithms
/ Automation
/ Compensators
/ Computer Science
/ Controllers
/ Disturbances
/ Equivalence
/ Guarantees
/ Inequality
/ Information Systems and Communication Service
/ Linear matrix inequalities
/ Linear quadratic regulator
/ Optimization
/ Particle swarm optimization
/ Repetitive controllers
/ Research Paper
/ State feedback
2022
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Estimation and compensation of periodic disturbance using internal-model-based equivalent-input-disturbance approach
by
Liu, Zhentao
, Wu, Min
, She, Jinhua
, Mei, Qicheng
in
Algorithms
/ Automation
/ Compensators
/ Computer Science
/ Controllers
/ Disturbances
/ Equivalence
/ Guarantees
/ Inequality
/ Information Systems and Communication Service
/ Linear matrix inequalities
/ Linear quadratic regulator
/ Optimization
/ Particle swarm optimization
/ Repetitive controllers
/ Research Paper
/ State feedback
2022
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Estimation and compensation of periodic disturbance using internal-model-based equivalent-input-disturbance approach
by
Liu, Zhentao
, Wu, Min
, She, Jinhua
, Mei, Qicheng
in
Algorithms
/ Automation
/ Compensators
/ Computer Science
/ Controllers
/ Disturbances
/ Equivalence
/ Guarantees
/ Inequality
/ Information Systems and Communication Service
/ Linear matrix inequalities
/ Linear quadratic regulator
/ Optimization
/ Particle swarm optimization
/ Repetitive controllers
/ Research Paper
/ State feedback
2022
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Estimation and compensation of periodic disturbance using internal-model-based equivalent-input-disturbance approach
Journal Article
Estimation and compensation of periodic disturbance using internal-model-based equivalent-input-disturbance approach
2022
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Overview
This paper presents an improved equivalent-input-disturbance (EID) approach to deal with periodic disturbances. The approach has two degrees of freedom. One is an improved EID compensator, in which a repetitive controller is inserted in this study. The other is a conventional servo system for a reference input. The improved EID compensator estimates and compensates for periodic disturbances without steady-state error, and the servo system ensures a satisfactory tracking performance. The improved EID compensator is designed using the linear-matrix-inequality (LMI) method. Three parameters in an LMI are selected using the particle-swarm-optimization (PSO) algorithm. The state-feedback gain of the conventional servo system is designed using the linear-quadratic-regulator (LQR) method. Simulation results of a rotational control system demonstrate the validity of the approach and its advantage over others.
Publisher
Science China Press,Springer Nature B.V
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