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1
artículo
Publicado 2007
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The objective of this work is the re-identification of the process model that is used in existing predictive controllers (MPC) using closed-loop operation data. The controller is assumed to have a two-layer structure, where in the upper layer a simple economic optimization algorithm determines a set of optimal steady-state values ("targets"), which are passed to the MPC for implementation. This is the case for several commercial MPC packages applied in the industry. This paper focuses on the case where the model represents significant benefits in the MPC re-commissioning procedure. A new methodology is proposed to excite the system in closed loop, introducing persistent excitation signals in the objective function of the upper layer of the MPC. This strategy allows the continuous operation of the system, respecting the constraints of the process and meeting the specifications of th...
2
artículo
Publicado 2007
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Enlace
This paper deals with the model re-identification in closed-loop systems with already existing MPC controllers. lt is assumed that the controller has a two-layer structure where the upper layer performs a simplified economic optimization in which the economic objective is represented as a linear combination of the process inputs. This is the case of several commercial MPC packages applied in industry. This work focuses on the case where the existing process model shows signs of deterioration and there is benefit in obtaining a new model. It is proposed a methodology where the test signal is introduced in the coefficients of the objective function of the economic layer. The approach allows the continuous operation of the system as the process constraints and product specification can be satisfied during the test. The application of the method is illustrated by simulation on a C3/C4 splitt...
3
artículo
Publicado 2007
Enlace
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This paper deals with the model re-identification in closed-loop systems with already existing MPC controllers. lt is assumed that the controller has a two-layer structure where the upper layer performs a simplified economic optimization in which the economic objective is represented as a linear combination of the process inputs. This is the case of several commercial MPC packages applied in industry. This work focuses on the case where the existing process model shows signs of deterioration and there is benefit in obtaining a new model. It is proposed a methodology where the test signal is introduced in the coefficients of the objective function of the economic layer. The approach allows the continuous operation of the system as the process constraints and product specification can be satisfied during the test. The application of the method is illustrated by simulation on a C3/C4 splitt...
4
artículo
Nowadays, an engineer’s work consists more and more of obtaining mathematical models of the studied processes. Great part of the literature referring to system identification deals with how to find polynomial models as Prediction Error Methods (PEM) and Instrumental Variable Methods (IVM). In case of complex systems, the state space model appears as an alternative to PEM and IVM models. For multivariable systems, these methods provide reliable state space models directly from input and output data. As systems of large dimensions are usually found in industry, the application of subspace identification algorithms in this field is very promising. Currently the subspaceidentification models Multivariable Output Error State sPace (MOESP) and Numerical algorithms for Subspace State Space System IDentification (N4SID), are topic of study. The objective of this work is to implement th...
5
artículo
Nowadays, an engineer’s work consists more and more of obtaining mathematical models of the studied processes. Great part of the literature referring to system identification deals with how to find polynomial models as Prediction Error Methods (PEM) and Instrumental Variable Methods (IVM). In case of complex systems, the state space model appears as an alternative to PEM and IVM models. For multivariable systems, these methods provide reliable state space models directly from input and output data. As systems of large dimensions are usually found in industry, the application of subspace identification algorithms in this field is very promising. Currently the subspaceidentification models Multivariable Output Error State sPace (MOESP) and Numerical algorithms for Subspace State Space System IDentification (N4SID), are topic of study. The objective of this work is to implement th...
6
artículo
Publicado 2020
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
7
artículo
Publicado 2007
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El objetivo de este trabajo es la re-identificación del modelo de proceso que se utiliza en controladores predictivos (MPC) ya existentes usando datos de operación en lazo cerrado. Se asume que el controlador tiene una estructura en dos capas, donde en la capa superior un simple algoritmo optimización económica determina un conjunto de valores óptimos en estado estacionario (“targets ”), los cuales son pasados al MPC para su implementación. Este es el caso de varios paquetes comerciales MPC aplicados en la industria. El presente trabajo enfoca el caso donde el modelo del proceso presenta signos de deterioro, por lo que obtener un nuevo modelo representa beneficios significativos en el procedimiento de re-comisionamiento del MPC. Se propone una nueva metodología para excitar el sistema en lazo cerrado, introduciendo señales de excitación persistente en la función objetivo de...
