TY - GEN
T1 - Path-dependent controller and estimator synthesis with robustness to delayed and missing data
AU - Hassaan, Syed M.
AU - Shen, Qiang
AU - Yong, Sze Zheng
N1 - Funding Information:
This work was partially supported by the NSF grants CNS-1943545 and CNS-1932066.
Publisher Copyright:
© 2021 ACM.
PY - 2021/5/19
Y1 - 2021/5/19
N2 - This paper presents path-dependent feedback controllers and estimators with bounded tracking and estimation error guarantees for discrete-time affine systems with time-varying delayed and missing data, where the set of all temporal patterns for the missing or delayed data is constrained by a fixed-length language. In particular, we propose two controller/estimator synthesis approaches based on output feedback and output error feedback parameterizations such that the tracking or estimation errors satisfy a property known as equalized recovery, where the errors are guaranteed to satisfy a recovery level at the start and the end of a finite time horizon, but may temporarily increase (by a bounded amount) within the horizon. To achieve this, we introduce a mapping of the fixed-length delayed/missing data language onto a reduced event-based language, and present designs with feedback gain matrices that adapt based on the observed path in the reduced language, resulting in improved performance. Furthermore, we propose a word observer that finds the set of words (i.e., the delayed/missing data patterns) in the original fixed-length language that are compatible with the observed path. The effectiveness of the proposed approaches when compared to existing approaches is demonstrated using several illustrative examples.
AB - This paper presents path-dependent feedback controllers and estimators with bounded tracking and estimation error guarantees for discrete-time affine systems with time-varying delayed and missing data, where the set of all temporal patterns for the missing or delayed data is constrained by a fixed-length language. In particular, we propose two controller/estimator synthesis approaches based on output feedback and output error feedback parameterizations such that the tracking or estimation errors satisfy a property known as equalized recovery, where the errors are guaranteed to satisfy a recovery level at the start and the end of a finite time horizon, but may temporarily increase (by a bounded amount) within the horizon. To achieve this, we introduce a mapping of the fixed-length delayed/missing data language onto a reduced event-based language, and present designs with feedback gain matrices that adapt based on the observed path in the reduced language, resulting in improved performance. Furthermore, we propose a word observer that finds the set of words (i.e., the delayed/missing data patterns) in the original fixed-length language that are compatible with the observed path. The effectiveness of the proposed approaches when compared to existing approaches is demonstrated using several illustrative examples.
UR - http://www.scopus.com/inward/record.url?scp=85105867661&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85105867661&partnerID=8YFLogxK
U2 - 10.1145/3447928.3456655
DO - 10.1145/3447928.3456655
M3 - Conference contribution
AN - SCOPUS:85105867661
T3 - HSCC 2021 - Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control (part of CPS-IoT Week)
BT - HSCC 2021 - Proceedings of the 24th International Conference on Hybrid Systems
PB - Association for Computing Machinery, Inc
T2 - 24th ACM International Conference on Hybrid Systems Computation and Control, HSCC 2021, held as part of the 14th Cyber Physical Systems and Internet-of-Things Week, CPS-IoT Week 2021
Y2 - 19 May 2021 through 21 May 2021
ER -