On nonlinear distributed parameter model predictive control strategy: On-line calculation time reduction and application to an experimental drying process

Abstract : It is now recognized that model predictive control (MPC) is an interesting alternative for real-time control of industrial processes. In the meantime, some problems do still remain in progress: for theoretical aspects, the a priori guarantee of the stability and for the practical aspects, the guarantee of sufficient time to solve to optimization problem at each sampled time positions. In this paper, we propose a global method that aims to reduce the on-line calculation time due to the PDE model based optimization task resolution. It is addressed for a particular class of systems not very often studied in this context: systems described by partial differential equations (PDEs) which are, in the present case, nonlinear and parabolic. In order to decrease the computational burden, the nonlinear PDE system is solved off-line. Then, a linearized PDE model around the previous off-line behavior is used to find the optimal variations for the on-line predictive control. The real-time control application given is concerned with a infrared drying process of painting film.
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Computers and Chemical Engineering, Elsevier, 2003, 27 (11), pp.1533-1542. 〈10.1016/S0098-1354(03)00099-1〉
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Pascal Dufour, Youssoufi Touré, Denise Blanc, Pierre Laurent. On nonlinear distributed parameter model predictive control strategy: On-line calculation time reduction and application to an experimental drying process. Computers and Chemical Engineering, Elsevier, 2003, 27 (11), pp.1533-1542. 〈10.1016/S0098-1354(03)00099-1〉. 〈hal-00352371v2〉

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