Abstract :
A model-based fuzzy gain scheduling technique is proposed. Fuzzy gain scheduling is a form of variable
gain scheduling which involves implementing several linear controllers over a partitioned process space.
A higher-level rule-based controller determines which local controller is executed. Unlike conventional
gain scheduling, a controller with fuzzy gain scheduling uses fuzzy logic to dynamically interpolate controller
parameters near region boundaries based on known local controller parameters. Model-based
fuzzy gain scheduling (MFGS) was applied to PID controllers to control a laboratory-scale water-gas
shift reactor. The experimental results were compared with those obtained by PID with standard fuzzy
gain scheduling, PID with conventional gain scheduling, simple PID and a nonlinear model predictive
control (NMPC) strategy. The MFGS technique performed comparably to the NMPC method. It exhibited
excellent control behaviour over the desired operating space, which spanned a wide temperature
range. The other three PID-based techniques were adequate only within a limited range of the same operating
space. Due to the simple algorithm involved, the MFGS technique provides a low cost alternative
to other computationally intensive control algorithms such as NMPC.
