This work provides the theoretical formulation, implementation directives and validation case for the extension of the nonlinear model predictive control from the time domain to the spatio-temporal domain. Effectiveness and online feasibility are demonstrated for industrial processes of distributed nature. The case of methanol synthesis (control of hot-spot temperature and axial position) is selected. © 2012 Elsevier B.V.30867871Bendersky, E., Christofides, P.D., Optimization of transport-reaction processes using nonlinear model reduction (2000) Chemical Engineering Science, 55, pp. 4349-4366Buzzi-Ferraris, G., Manenti, F., A Combination of Parallel Computing and Object-Oriented Programming to Improve Optimizer Robustness and Efficiency (20...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
This paper presents the application of an identification algorithm based on local model networks abl...
This work provides the theoretical formulation, implementation directives and validation case for th...
The possibility to apply the nonlinear model predictive control (NMPC) to the fixed-bed tubular reac...
The purpose of this work is to develop a reasonably detailed dynamic model of a Lurgi-type industria...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
Large-scale chemical process systems are characterized by highly nonlinear behavior and the coupling...
A nonlinear model predictive control (NMPC) is applied to a slurry polymerization stirred tank react...
Abstract — Moving horizon estimation (MHE) has been ap-plied to an industrial gas phase polymerizati...
A nonlinear model predictive control scheme based on the second-order Volterra model is presented. F...
Linear Model Predictive Control (MPC) can be considered as the state of the art advanced process con...
The aim of this thesis was to develop an advanced two-layer control structure for the semi-batch pol...
Abstract: A large-scale set of differential and algebraic equations (DAEs) is used to model and cont...
Novel computational intelligence-based methods have been investigated to quantify uncertaintie...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
This paper presents the application of an identification algorithm based on local model networks abl...
This work provides the theoretical formulation, implementation directives and validation case for th...
The possibility to apply the nonlinear model predictive control (NMPC) to the fixed-bed tubular reac...
The purpose of this work is to develop a reasonably detailed dynamic model of a Lurgi-type industria...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
Large-scale chemical process systems are characterized by highly nonlinear behavior and the coupling...
A nonlinear model predictive control (NMPC) is applied to a slurry polymerization stirred tank react...
Abstract — Moving horizon estimation (MHE) has been ap-plied to an industrial gas phase polymerizati...
A nonlinear model predictive control scheme based on the second-order Volterra model is presented. F...
Linear Model Predictive Control (MPC) can be considered as the state of the art advanced process con...
The aim of this thesis was to develop an advanced two-layer control structure for the semi-batch pol...
Abstract: A large-scale set of differential and algebraic equations (DAEs) is used to model and cont...
Novel computational intelligence-based methods have been investigated to quantify uncertaintie...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and pro...
This paper presents the application of an identification algorithm based on local model networks abl...