Convergence analysis of a real-time identification algorithm for switched linear systems with bounded noise

Abdelhak Goudjil (1) , Mathieu Pouliquen (1) , Eric Pigeon (1) , Olivier Gehan (1)

1 LAC - Laboratoire d'automatique de Caen

We consider the problem of a real-time identification of switched linear systems in the presence of bounded noise. This is a challenging problem that involves the association of each data to the most suitable sub-system and the estimation of the parameters of all sub-systems. The proposed algorithm is based on an Outer Bounding Ellipsoid (OBE) type algorithm appropriate for real-time system identification with bounded noise. An analysis of convergence and stability is provided.

Keywords: Switches; Estimation; Algorithm design and analysis; Linear systems; Convergence; Real-time systems; Stochastic processes; Parameter estimation; Stability; Switching systems (control); Switched linear systems; Recursive identification; Bounded noise; Analysis of convergence

Domains: Engineering Sciences [physics]; Automatic

Abdelhak Goudjil, Mathieu Pouliquen, Eric Pigeon, Olivier Gehan. Convergence analysis of a real-time identification algorithm for switched linear systems with bounded noise. 2016 IEEE 55th Conference on Decision and Control (CDC), Dec 2016, Las Vegas, United States. pp.2957-2962, ⟨10.1109/CDC.2016.7798710⟩. ⟨hal-01825011⟩