Nonlinear Adaptive Control of Hydraulic System With Observing and Compensating Mismatching Uncertainties

Hydraulic servomechanism is the typical mechanical/hydraulic double-dynamics coupling system with heavy nonlinearity, parametric uncertainties, and mismatching uncertainties input problems. How to estimate and compensate mismatching uncertainties by observer is a very important issue. This paper pro...

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Vydáno v:IEEE transactions on control systems technology Ročník 26; číslo 3; s. 927 - 938
Hlavní autoři: Wang, Chengwen, Quan, Long, Jiao, Zongxia, Zhang, Shijie
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.05.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Actuators
Adaptive control
Control rods
Disturbances
Disturbances estimation and compensation
extended state observer (ESO)
Hydraulic equipment
hydraulic servo system
Hydraulic servomechanisms
Hydraulics
mismatching uncertainties
nonlinear adaptive control
Nonlinear control
Nonlinear dynamical systems
Nonlinearity
Parameter uncertainty
Servomotors
Tracking control
Uncertainty
Valves
ISSN:1063-6536, 1558-0865
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Shrnutí:Hydraulic servomechanism is the typical mechanical/hydraulic double-dynamics coupling system with heavy nonlinearity, parametric uncertainties, and mismatching uncertainties input problems. How to estimate and compensate mismatching uncertainties by observer is a very important issue. This paper proposes an extended-state-observer (ESO)-based nonlinear adaptive control scheme for the motion tracking control of the hydraulic valve-controlled single-rod actuator system. This paper provides a solution to estimate and compensate the mismatching disturbances, i.e., the mechanical dynamics uncertainties. With the developed method, both the hydraulic dynamics uncertainties and the mechanical dynamics uncertainties can be estimated and compensated effectively. Moreover, the parameters adaptive mechanism is also supplemented with ESO to further improve the tracking performance. The parametric uncertainties, modeling, and unknown external disturbances are comprehensively addressed. In theory, the asymptotic tracking can be achieved even in the presence of unknown external constant disturbances and parametric uncertainties. Besides giving the theoretical results and proof, the effectiveness of the proposed method is verified through extensive comparative experiments.
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ISSN:1063-6536
1558-0865
DOI:10.1109/TCST.2017.2699166