TY - GEN
T1 - Robust control of nonlinear strict-feedback systems with measurement errors
AU - Liu, Tengfei
AU - Jiang, Zhong Ping
AU - Hill, David J.
N1 - Funding Information:
This study was funded by operating grants from the Canadian Institutes of Health Research (grant number #133477 ), the Multiple Sclerosis Scientific Research Foundation of the Multiple Sclerosis Society of Canada (grant number EGID678 ), and the Alberta Innovates — Health Solutions ' CRIO Team program (grant number #3769 ). We thank Yan Fan, Tammy Wilson, Janet Wang, Brooke Verhaeghe and Claudia Silva for skilled technical assistance.
PY - 2011
Y1 - 2011
N2 - This paper presents a new method for robust control of a class of uncertain nonlinear systems in strict-feedback form with state measurement errors. The measurement feedback control problem is solved by recursively designing input-to-state stability (ISS) induced nonlinear state estimators and virtual control laws. With the gain assignment technique, the closed-loop system can be transformed into an interconnection of ISS subsystems, the ISS and input-to-output stability (IOS) of which can be guaranteed by the cyclic-small-gain theorem. Moreover, the IOS gain from the measurement error of the system output (the first state) to the system output can be designed to be linear and arbitrarily close to the identity function.
AB - This paper presents a new method for robust control of a class of uncertain nonlinear systems in strict-feedback form with state measurement errors. The measurement feedback control problem is solved by recursively designing input-to-state stability (ISS) induced nonlinear state estimators and virtual control laws. With the gain assignment technique, the closed-loop system can be transformed into an interconnection of ISS subsystems, the ISS and input-to-output stability (IOS) of which can be guaranteed by the cyclic-small-gain theorem. Moreover, the IOS gain from the measurement error of the system output (the first state) to the system output can be designed to be linear and arbitrarily close to the identity function.
UR - http://www.scopus.com/inward/record.url?scp=84860682557&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84860682557&partnerID=8YFLogxK
U2 - 10.1109/CDC.2011.6160668
DO - 10.1109/CDC.2011.6160668
M3 - Conference contribution
AN - SCOPUS:84860682557
SN - 9781612848006
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 2034
EP - 2039
BT - 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Y2 - 12 December 2011 through 15 December 2011
ER -