Robust identification of continuous-time models with arbitrary time-delay from irregularly sampled data. (January 2015)

• Record Type: Journal Article
• Authors: Chen, Fengwei; Garnier, Hugues; Gilson, Marion
• Is Part Of: Journal of process control. Volume 25(2015:Jan.)
• Page Start: 19
• Page End: 27
• Publication Date: 2015-01
• Subjects: Continuous-time models -- Identification -- Time-delay estimation -- Irregularly sampled data; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2014.10.003
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract : Highlights: Identification of continuous-time systems with time-delay from irregular data is considered in this paper. A combined instrumental variable (IV) and gradient search method is proposed. The plant and the time-delay are estimated in a separate way by the IV and gradient methods, respectively. A low-pass filter is used to expand the convergence region for time-delay estimation. Abstract: This paper presents a new approach to identify continuous-time systems with arbitrary time-delay from irregularly sampled input–output data. It is based on the separable nonlinear least-squares method which combines in a bootstrap manner the iterative optimal instrumental variable method for transfer function model estimation with an adaptive gradient-based technique that searches for the optimal time-delay. Since the objective function may have several local minima with respect to the unknown parameters (especially the time-delay), the initialization requires special attention. Here, a low-pass filtering strategy is used to widen the convergence region around the global minimum. Simulation results are included to show the performance of the proposed method.