Nonlinear model predictive control experiments on a laboratory gas turbineinstallation

Results an the feasibility and benefits of model based predictive control a pplied to a gas turbine are presented. For a laboratory gas turbine install ation, the required dynamic simulation model and the real-time (nonlinear) model predictive control (MPC) implementation are discussed Results on both model validation and control performance are presented. We applied a nonli near MPC configuration to control the laboratory gas turbine installation a , rd succeeded in a real-time implementation. Although the available comput ation time for prediction and optimization of the model limits the sample t ime, the advantages of MPC, i.e. constraint handling, and anticipation to f uture (set-point) changes are Sully reached, and the control performance is good. Special attention is paid to the performance of the applied filter t hat compensates for inevitable mismatches between model and process measure ments. In general, the opportunities of model based control of turbomachine ry are promising.