Predictive control for the ALSTOM gasifier problem

Abstract

Model predictive control (MPC) has become the first choice of control strategy in many cases especially in the process industry because it is intuitive and can explicitly handle MIMO (multiple input multiple output) systems with input and output constraints. The authors implemented a simple MPC algorithm based on the state space formulation to control the ALSTOM gasifier. Among three operating conditions of the plant, 0% load condition is identified as the worst case. A linearised state space model at 0% load condition of the non-linear plant is adopted as the internal model for performance prediction. Because of this choice, the control system comfortably achieves performance requirements at the most difficult load condition. Meanwhile, the case study shows that the model is also adequate to pass all tests under other load conditions specified in the benchmark problem. The MPC algorithm uses standard formulation and off-the-shelf software with a few tunable parameters. Thus, it is easy to implement and to tune to achieve satisfactory performance.