Nonlinear model predictive control with moving-horizon state and disturbance estimation - with application to MSW combustion
| Authors: | Leskens Martijn, TNO Science and Industry, Netherlands
van Kessel L.B.M., TNO Science and Industry, Netherlands
Van den Hof P.M.J., Delft University of Technology, Netherlands
Bosgra O.H., Delft University of Technology, Netherlands |
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| Topic: | 6.1 Chemical Process Control |
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| Session: | Advances in Process Control |
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| Keywords: | nonlinear model predictive control, moving horizon estimation, extended Kalman filter, municipal solid waste combustion |
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Abstract
This paper presents a nonlinear model predictive control (NMPC) strategy that can be used to tackle model predictive control problems that involve relatively simple nonlinear dynamic models, as for example obtained with first-principles modeling. The main feature of the proposed NMPC strategy is the usage of a moving horizon estimator (MHE) for the estimation of the states and disturbances (and, if desired, parameters). The closed-loop performance properties of the proposed NMPC strategy are demonstrated by applying it to a model of a municipal solid waste (MSW) combustion plant under a realistic disturbance realization. In addition, a comparison is made with extended Kalman filter (EKF) based NMPC.
