INGAR 05399
INSTITUTO DE DESARROLLO Y DISEÑO
Unidad Ejecutora - UE
artículos
Título:
Nonlinear parametric predictive control. Application to a continuous stirred tank reactor
Autor/es:
ARMANDO ASSANDRI; SMARANDA CRISTEA; CÉSAR DE PRADA; ERNESTO MARTÍNEZ
Revista:
Asia-Pacific Journal of Chemical Engineering
Editorial:
Wiley
Referencias:
Lugar: New York; Año: 2009 vol. 4 p. 858 - 869
ISSN:
1932-2135
Resumen:
This paper presents a non-linear model-based controller based on the ideas of parametric
predictive control applied to a Continuous Stirred Tank Reactor (CSTR) process unit. Controller
design aims at avoiding the complexity of implementation and long computational times associated
to conventional NMPC while maintaining the main advantage of taking into account process nonlinearities
that are relevant for control. The design of the parametric predictive controller is based
on a rather simplified process model having parameters that are instrumental in determining the
required changes to the manipulated variables for error reduction. The nonlinear controller is easy
to tune and can operate successfully over a wide range of operating conditions. The use of an
estimator of unmeasured disturbances and process-model mismatch further enhances the behaviour
of the controller.
that are relevant for control. The design of the parametric predictive controller is based
on a rather simplified process model having parameters that are instrumental in determining the
required changes to the manipulated variables for error reduction. The nonlinear controller is easy
to tune and can operate successfully over a wide range of operating conditions. The use of an
estimator of unmeasured disturbances and process-model mismatch further enhances the behaviour
of the controller.
that are relevant for control. The design of the parametric predictive controller is based
on a rather simplified process model having parameters that are instrumental in determining the
required changes to the manipulated variables for error reduction. The nonlinear controller is easy
to tune and can operate successfully over a wide range of operating conditions. The use of an
estimator of unmeasured disturbances and process-model mismatch further enhances the behaviour
of the controller.
of taking into account process nonlinearities
that are relevant for control. The design of the parametric predictive controller is based
on a rather simplified process model having parameters that are instrumental in determining the
required changes to the manipulated variables for error reduction. The nonlinear controller is easy
to tune and can operate successfully over a wide range of operating conditions. The use of an
estimator of unmeasured disturbances and process-model mismatch further enhances the behaviour
of the controller.
