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

A general multiple-model (MM) estimator with a 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 problems with hybrid (continuous and discrete) uncertainties. It is also easily implementablc. It is illustrated via a simple fault detection and identification example that the MGS algorithm provides a substantial reduction in computation while having identical performance with the fixed-structure Interacting Multiple-Model (FSIMM) estimator.