TY - GEN
T1 - Hierarchical estimation for complex multi-domain dynamical systems
AU - Tannous, Pamela J.
AU - Docimo, Donald J.
AU - Pangborn, Herschel C.
AU - Alleyne, Andrew G.
N1 - Funding Information:
*Research supported by the National Science Foundation Engineering Research Center for Power Optimization of Electro Thermal Systems (POETS) with cooperative agreement EEC-1449548. P. J. Tannous (e-mail: tannous2@illinois.edu), D. J. Docimo (e-mail:
Publisher Copyright:
© 2019 American Automatic Control Council.
PY - 2019/7
Y1 - 2019/7
N2 - Complex power systems have dynamics spanning multiple energy domains and operating at multiple time scales. Hierarchical control has been proven to guarantee successful management of the coupling between the resulting fast transients and slow dynamics. It is usually prohibitively expensive or even infeasible to measure every signal in the system. Therefore, a reliable estimation framework that provides accurate estimates is vital to the success of the control design. This paper proposes a multi-level hierarchical estimation approach that can be used to supply reliable estimates to hierarchical controllers of complex multi-domain power systems. Models of complex multi-domain power systems can be accurately represented using graphs. System decomposition can be then achieved using clustering algorithms from graph theory. In this work, local estimates at each level of the hierarchical estimator are obtained using extended Kalman filters. A hierarchical estimator-controller is designed for an automotive electric vehicle as an illustrative example.
AB - Complex power systems have dynamics spanning multiple energy domains and operating at multiple time scales. Hierarchical control has been proven to guarantee successful management of the coupling between the resulting fast transients and slow dynamics. It is usually prohibitively expensive or even infeasible to measure every signal in the system. Therefore, a reliable estimation framework that provides accurate estimates is vital to the success of the control design. This paper proposes a multi-level hierarchical estimation approach that can be used to supply reliable estimates to hierarchical controllers of complex multi-domain power systems. Models of complex multi-domain power systems can be accurately represented using graphs. System decomposition can be then achieved using clustering algorithms from graph theory. In this work, local estimates at each level of the hierarchical estimator are obtained using extended Kalman filters. A hierarchical estimator-controller is designed for an automotive electric vehicle as an illustrative example.
UR - http://www.scopus.com/inward/record.url?scp=85072295606&partnerID=8YFLogxK
U2 - 10.23919/acc.2019.8814330
DO - 10.23919/acc.2019.8814330
M3 - Conference contribution
AN - SCOPUS:85072295606
T3 - Proceedings of the American Control Conference
SP - 909
EP - 915
BT - 2019 American Control Conference, ACC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 July 2019 through 12 July 2019
ER -