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Nonlinear Predictive Control System for Stiction Compensation in Electropneumatic Control Valves
by
Santos, W. M.
, Gadelha, J. R. T.
, Araújo, Fábio M. U.
, Maitelli, André Laurindo
, Araújo, M. E. U. J.
in
Computer simulation
/ Control stability
/ Control systems
/ Control valves
/ Controllers
/ Efficiency
/ Engineering
/ Friction
/ Linear programming
/ Maintenance costs
/ Mathematical models
/ Nonlinear control
/ Parameter estimation
/ Predictive control
/ Process controls
/ Signal processing
/ Static friction
/ Stiction
/ Valves
2018
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Nonlinear Predictive Control System for Stiction Compensation in Electropneumatic Control Valves
by
Santos, W. M.
, Gadelha, J. R. T.
, Araújo, Fábio M. U.
, Maitelli, André Laurindo
, Araújo, M. E. U. J.
in
Computer simulation
/ Control stability
/ Control systems
/ Control valves
/ Controllers
/ Efficiency
/ Engineering
/ Friction
/ Linear programming
/ Maintenance costs
/ Mathematical models
/ Nonlinear control
/ Parameter estimation
/ Predictive control
/ Process controls
/ Signal processing
/ Static friction
/ Stiction
/ Valves
2018
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Do you wish to request the book?
Nonlinear Predictive Control System for Stiction Compensation in Electropneumatic Control Valves
by
Santos, W. M.
, Gadelha, J. R. T.
, Araújo, Fábio M. U.
, Maitelli, André Laurindo
, Araújo, M. E. U. J.
in
Computer simulation
/ Control stability
/ Control systems
/ Control valves
/ Controllers
/ Efficiency
/ Engineering
/ Friction
/ Linear programming
/ Maintenance costs
/ Mathematical models
/ Nonlinear control
/ Parameter estimation
/ Predictive control
/ Process controls
/ Signal processing
/ Static friction
/ Stiction
/ Valves
2018
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Nonlinear Predictive Control System for Stiction Compensation in Electropneumatic Control Valves
Journal Article
Nonlinear Predictive Control System for Stiction Compensation in Electropneumatic Control Valves
2018
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Overview
This paper presents the implementation of a system that deals with static friction (stiction) in electropneumatic control valves, one of the most common nonlinearities that causes problems such as limit cycles and consequently wear of the valve and its moving parts, as well as losses in production and maintenance costs. This system is composed of a nonlinear predictive controller with adjustable constraints and an online database for estimation of the stiction parameters. The predictive controller uses constraints on the valve speed during its excursion, as well as constraints on the control signal to bring the valve to the desired position and slip it when necessary. The strategy adopted also showed robustness, being able to cope with changes in the spring and stiction parameters, which caused mismatch between the model and the controller and consequently loss of performance or even instability.
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