Multiple-model estimation with variable structure: Model-group switching algorithm

A general multiple-model estimator with variable structure (VSMM), called model-group switching (MGS) algorithm, is presented. It assumes that the total set of models can be covered by a number of model groups, each representing a cluster of closely related system behavior patterns or structures, and a particular group is running at any given time determined by a hard decision. This algorithm is the first VSMM estimator that is generally applicable to a large class of problem with hybrid (continuous and discrete) uncertainties and easily implementable. The algorithm is promising in the sense of being substantially more cost-effective than the Interacting Multiple-Model (IMM) estimator.