TS fuzzy modeling based anytime control methodology for situational control

Nowadays, modern approaches to complex system´s control show the need for preparing strategies also for the atypical operational situations, like crisis, emergency, structural failures, starting and stopping of plants, etc. Situational control tries to handle the problem of the contradiction arising from the existence of the large number of situations and the limited number of used control strategies by grouping the possible situations into a treatable (finite) number of model classes of operational situations and assigning certain control algorithms to the defined control regimes. Anytime control algorithms fit into the frame of situational control concept. They aim to offer a tradeoff between resource consumption (including time and data as well) and output quality. In this paper, an anytime control methodology is presented which combines Takagi-Sugeno fuzzy modeling techniques with anytime processing. The proposed method can be used in situational control advantageously and is able to cope with atypical situations, time and resource insufficiency.