It is a pleasure to announce you that my work “A switched nonlinear system identification method with switching location refinement”, co-authored by Miao Yu and Luigi Piroddi, has been accepted for presentation at the presented at the 60th Conference on Decision and Control – CDC2021- December 13-15, 2021, Austin, Texas, USA.
Abstract
The identification of switched nonlinear systems involves solving a combinatorial problem that simultaneously addresses the sample-mode assignment and nonlinear model structure selection tasks. The complexity of this problem is often prohibitive, since mode switchings can take place at arbitrary times. To reduce it to an affordable level, one can constrain the mode switchings to occur only at few specific instants. This approach is effective if combined with a refinement strategy, aiming at correcting the number and location of switchings. In this paper, one such strategy is discussed, which employs a local
optimization process to correct the position of switchings, and is also capable of detecting and removing redundant modes. An iterative method, applying both an identification step and a refinement step at all iterations, is tested on several numerical benchmarks to illustrate the effectiveness of the refinement strategy. The method does not require prior assumptions on the number of modes.
Federico Bianchi 