Abstract
Stochastic adaptive control of a discrete-time system in the presence of unmodeled dynamics is considered. Unmodeled dynamics can consist of multiplicative as well as additive system uncertainty. The adaptive controller is based on the pole-placement method. For the identification of the nominal system parameters, a stochastic approximation algorithm with parameter projection and modified gain sequence is used. Minimum phase assumption for the nominal system is not required. The self-stabilization mechanism, inherent to adaptive control, is evaluated analytically. Global stability is obtained without requiring the persistency exciting condition to be satisfied. It is shown that the projection mechanism together with the simple modification of the gain sequence in the identification algorithm is sufficient to guarantee robust mean-square boundedness with respect to unmodeled dynamics. >
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.