Stable constrained model predictive control based on IOFL technique for boiler-turbine system

Due to the strong nonlinearities of the boiler-turbine system, feasibility and high response capability are hard to realize using traditional linear controllers. Advanced controllers that can ensure stability and feasibility without violating system constraints, and enhance the system’s dynamic output performance, are needed. Therefore, this paper proposes a stable input/output feedback linearization (IOFL) model predictive controller (MPC) technique for the boiler-turbine system. This nonlinear system is decoupled using the IOFL method into a novel linearized model, which is then used for constituting the proposed stable IOFL MPC problem. The proposed scheme uses a constraint mapping method that converts actual input limits into limits on the basis of the control output variable to ensure a feasible solution over the whole prediction horizon. Moreover, a min-max MPC technique in the form of linear matrix inequality with the realization of the input rate-of-change constraints is utilized to ensure the boiler-turbine unit’s stability. The process model and proposed control scheme are executed using MATLAB and the simulation results demonstrate that the proposed controller has an enhanced dynamic output performance compared with an advanced control scheme under various load variations.