Identification of switching systems using change detection

Abstract — The paper describes an identification technique of switching system. The considered system is represented as a weighted sum of local models. To estimate the switching times, a change detection technique is applied. It provides the weights associated to the local models. The Markov parameters of these models are identified by a subspace method. This cal-culation can yield similar local models which are merged. The procedure of parameter identification an models merging is repeated until convergence. The performance of the approach is investigated on a simulation example. Index Terms — switching system, identification, detection of abrupt model changes, Markov parameters, subspace method I