Abstract
In this paper convergence of an adaptive pole-placement algorithm based on the minimization of a predefined criterion is analysed. It is supposed that an external random excitation with possibly decreasing variance is injected into the system. The main result is the proof. of the convergence w.p.1 of the regulator parameter estimates to the optimal ones, i.e. convergence w.p.l of the closed loop poles to the desired ones, derived in two methodologically different ways. Convergence is ensured under mild conditions concerning the number of estimated parameters and requiring irreducibility of the optimal regulator transfer function. It isdemonstrated that the algorithm converges even in the case of an external random excitation whose variance tends to zero, despite the fact that the persistence of excitation is notsatisfied. Consistency proof for the parameter estimate s in minimum variance self-tuning control algorithms can be derived as a special case.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Adaptive Systems in Control and Signal Processing 1986
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.
