TY - JOUR
T1 - A Distributed Indirect Adaptive Approach to Cooperative Tracking in Networks of Uncertain Single-Input Single-Output Systems
AU - Baldi, Simone
AU - Azzollini, Ilario A.
AU - Ioannou, Petros A.
PY - 2021
Y1 - 2021
N2 - Current approaches to the cooperative control of network systems are based on a priori knowledge about the (follower) system dynamics: Either the dynamics are known, or assumed to be minimum phase, or initial stabilizing controllers are available for each system. The purpose of this article is to show that for single-input single-output systems (SISO) the above assumptions can be relaxed. We propose an indirect adaptive methodology that does not require the knowledge of the parameters of the systems, or the systems to be minimum phase, or initial stabilizing controllers, in order to guarantee asymptotic tracking.
AB - Current approaches to the cooperative control of network systems are based on a priori knowledge about the (follower) system dynamics: Either the dynamics are known, or assumed to be minimum phase, or initial stabilizing controllers are available for each system. The purpose of this article is to show that for single-input single-output systems (SISO) the above assumptions can be relaxed. We propose an indirect adaptive methodology that does not require the knowledge of the parameters of the systems, or the systems to be minimum phase, or initial stabilizing controllers, in order to guarantee asymptotic tracking.
KW - Adaptive control
KW - cooperative tracking
KW - leader and followers uncertain parameters
UR - http://www.scopus.com/inward/record.url?scp=85097182560&partnerID=8YFLogxK
U2 - 10.1109/TAC.2020.3038742
DO - 10.1109/TAC.2020.3038742
M3 - Article
AN - SCOPUS:85097182560
SN - 0018-9286
VL - 66
SP - 4844
EP - 4851
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
IS - 10
ER -