Nonlinear Model Predictive Control applied to Transient Operation of a Gas Turbine

This work aims to investigate the application of a comprehensive nonlinear model-based predictive control strategy as a means to avoid unsafe or inappropriate operation of a gas turbine. Herein, the nonlinear model-based predictive control is employed to control compressor speed by varying the fuel flow in the combustion chamber. The methodology complies with the gas turbine constraints explicitly in the optimization procedure and, therefore, the nonlinear model-based predictive control algorithm ensures that process constraints are not violated. The nonlinear dynamic behaviour of the gas turbine is modelled with the aid of a first principle process simulator, which solves the equations of state and the conservation equations of mass, energy and momentum. The optimization procedure is achieved through the implementation of an evolutionary algorithm. Three scenarios are simulated: fuel consumption optimization, load removal/addition and load rejection. The proposed control strategy is successfully applied to both transient and steady-state operational modes of the gas turbine.