Citation:
Seyab, R.K.A.; Cao, Y.; Yang, S.H. Predictive control for the ALSTOM gasifier
problem. IEE Proceedings: Control Theory and Applications. Vol 153 Iss 3, 9 May
2006, pp286- 292
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.