Several fuzzy logic control schemes have been developed, including some adaptive methods. However, many of these methods can only handle single input, single output (SISO) systems and stability of the overall system may not be guaranteed. In this paper, a self-learning FLC with on-line scaling factor tuning is discussed and stability analysis of the adaptive FLC is developed. Simulation results employing the adaptive FLC on a model of an experimental dyeing process testbed are presented to illustrate the approach. These results show that the self-learning fuzzy logic control algorithm is a viable approach for system compensation when models are incomplete or unknown.
展开▼
