Realization of multi-input/multi-output switched linear systems from Markov parameters. (May 2023)
- Record Type:
- Journal Article
- Title:
- Realization of multi-input/multi-output switched linear systems from Markov parameters. (May 2023)
- Main Title:
- Realization of multi-input/multi-output switched linear systems from Markov parameters
- Authors:
- Bencherki, Fethi
Türkay, Semiha
Akçay, Hüseyin - Abstract:
- Abstract: This paper presents a four-stage algorithm for the realization of multi-input/multi-output (MIMO) switched linear systems (SLSs) from Markov parameters. In the first stage, a linear time-varying (LTV) realization that is topologically equivalent to the true SLS is derived from the Markov parameters assuming that the discrete states have a common MacMillan degree and a mild condition on their dwell times holds. In the second stage, stationary point set of a Hankel matrix with fixed dimensions built from the Markov parameters is examined. Splitting of this set into disjoint intervals and complements reveals linear time-invariant dynamics prevailing on these intervals. Clustering over a feature space permits recovery of the discrete states up to similarity transformations which is complete if a unimodality assumption holds and the discrete states satisfy a residence requirement. In the third stage, the switching sequence is estimated by three schemes. The first scheme is non-iterative in time. The second scheme is based on matching the estimated and the true Markov parameters of the SLS system over segments. The third scheme works also on the same principle, but it is a discrete optimization/hypothesis testing algorithm. The three schemes operate on different dwell time and model structure requirements, but the dwell time requirements are weaker than that needed to recover the discrete states. In the fourth stage, the discrete state estimates are brought to a commonAbstract: This paper presents a four-stage algorithm for the realization of multi-input/multi-output (MIMO) switched linear systems (SLSs) from Markov parameters. In the first stage, a linear time-varying (LTV) realization that is topologically equivalent to the true SLS is derived from the Markov parameters assuming that the discrete states have a common MacMillan degree and a mild condition on their dwell times holds. In the second stage, stationary point set of a Hankel matrix with fixed dimensions built from the Markov parameters is examined. Splitting of this set into disjoint intervals and complements reveals linear time-invariant dynamics prevailing on these intervals. Clustering over a feature space permits recovery of the discrete states up to similarity transformations which is complete if a unimodality assumption holds and the discrete states satisfy a residence requirement. In the third stage, the switching sequence is estimated by three schemes. The first scheme is non-iterative in time. The second scheme is based on matching the estimated and the true Markov parameters of the SLS system over segments. The third scheme works also on the same principle, but it is a discrete optimization/hypothesis testing algorithm. The three schemes operate on different dwell time and model structure requirements, but the dwell time requirements are weaker than that needed to recover the discrete states. In the fourth stage, the discrete state estimates are brought to a common basis by a novel basis transformation which is necessary for predicting outputs to prescribed inputs. Robustness of the four-stage algorithm to amplitude bounded noise is studied and it is shown that small perturbations may only produce small deviations in the estimates vanishing as noise amplitude diminishes. Time complexities of the stages are also studied. A numerical example illustrates the derived results. Highlights: An algorithm for realization of MIMO-switched systems from Markov parameters is proposed. Robustness to amplitude bounded noise is established. Time-complexity of the algorithm is studied. Detailed numerical example illustrates effectiveness of the proposed algorithm. … (more)
- Is Part Of:
- Nonlinear analysis. Volume 48(2023)
- Journal:
- Nonlinear analysis
- Issue:
- Volume 48(2023)
- Issue Display:
- Volume 48, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 48
- Issue:
- 2023
- Issue Sort Value:
- 2023-0048-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-05
- Subjects:
- Hybrid system -- Switched linear system -- State-space -- Realization -- Markov parameters
Nonlinear functional analysis -- Periodicals
Analyse fonctionnelle non linéaire -- Périodiques
Nonlinear functional analysis
Periodicals
515.7248 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1751570X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.nahs.2022.101311 ↗
- Languages:
- English
- ISSNs:
- 1751-570X
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 6117.315800
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