Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation

M Ławryńczuk - ISA transactions, 2017 - Elsevier
ISA transactions, 2017Elsevier
This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-
turbine unit, which is a nonlinear multiple-input multiple-output process. The control
objective is to follow set-point changes imposed on two state (output) variables and to satisfy
constraints imposed on three inputs and one output. In order to obtain a computationally
efficient control scheme, the state-space model is successively linearised on-line for the
current operating point and used for prediction. In consequence, the future control policy is …
Abstract
This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant.
Elsevier
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