TY - GEN
T1 - Quantifying Controllability for Nonlinear State-Dependent Riccati Equation Control
AU - Hu, Yuhui
AU - Neusypin, Konstantin Avenirovich
AU - Shen, Kai
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Degree of controllability (DOC) characterizes how controllable a given system is and thus quantifying controllability can facilitate the control system synthesis and optimization. In this paper, the controllability of nonlinear input-affine systems and the state-dependent-coefficient (SDC) factorization are first reviewed. A computational procedure based on the scalarization of the controllability Gramian is proposed to quantify the controllability of both system and state variables of the SDC factored system for state-dependent Riccati equation (SDRE) control. The simulation of coordinate satellite control is carried out to validate the effectiveness of the proposed DOC criterion. It is shown that SDC-parameterized models with higher DOC can promote the performance of the SDRE control algorithm.
AB - Degree of controllability (DOC) characterizes how controllable a given system is and thus quantifying controllability can facilitate the control system synthesis and optimization. In this paper, the controllability of nonlinear input-affine systems and the state-dependent-coefficient (SDC) factorization are first reviewed. A computational procedure based on the scalarization of the controllability Gramian is proposed to quantify the controllability of both system and state variables of the SDC factored system for state-dependent Riccati equation (SDRE) control. The simulation of coordinate satellite control is carried out to validate the effectiveness of the proposed DOC criterion. It is shown that SDC-parameterized models with higher DOC can promote the performance of the SDRE control algorithm.
KW - controllability Gramian
KW - degree of controllability
KW - state-dependent Riccati equation
KW - state-dependent coefficient
UR - http://www.scopus.com/inward/record.url?scp=85140908597&partnerID=8YFLogxK
U2 - 10.1109/RusAutoCon54946.2022.9896348
DO - 10.1109/RusAutoCon54946.2022.9896348
M3 - Conference contribution
AN - SCOPUS:85140908597
T3 - Proceedings - 2022 International Russian Automation Conference, RusAutoCon 2022
SP - 80
EP - 85
BT - Proceedings - 2022 International Russian Automation Conference, RusAutoCon 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Russian Automation Conference, RusAutoCon 2022
Y2 - 4 September 2022 through 10 September 2022
ER -