Model predictive control: theory and practice—a survey
Automatica (Journal of IFAC)
State-space interpretation of model predictive control
Automatica (Journal of IFAC)
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
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Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Brief Subspace identification of closed loop systems by the orthogonal decomposition method
Automatica (Journal of IFAC)
MPC for stable linear systems with model uncertainty
Automatica (Journal of IFAC)
Proper orthogonal decomposition for reduced basis feedback controllers for parabolic equations
Mathematical and Computer Modelling: An International Journal
Modeling and control of physical processes using proper orthogonal decomposition
Mathematical and Computer Modelling: An International Journal
Control of laser surface hardening by a reduced-order approach using proper orthogonal decomposition
Mathematical and Computer Modelling: An International Journal
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This paper studies the application of proper orthogonal decomposition (POD) to reduce the order of distributed reactor models with axial and radial diffusion and the implementation of model predictive control (MPC) based on discrete-time linear time invariant (LTI) reduced-ordermodels. In this paper, the control objective is to keep the operation of the reactor at a desired operating condition in spite of the disturbances in the feed flow. This operating condition is determined by means of an optimization algorithm that provides the optimal temperature and concentration profiles for the system. Around these optimal profiles, the nonlinear partial differential equations (PDEs), that model the reactor are linearized, and afterwards the linear PDEs are discretized in space giving as a result a high-order linear model. POD and Galerkin projection are used to derive the low-order linear model that captures the dominant dynamics of the PDEs, which are subsequently used for controller design. An MPC formulation is constructed on the basis of the low-order linear model. The proposed approach is tested through simulation, and it is shown that the results are good with regard to keep the operation of the reactor.