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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 linearized on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimization 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 linearization gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimization repeated at each sampling instant.
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