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Journal of Applied Mathematics
Volume 2014, Article ID 191256, 9 pages
http://dx.doi.org/10.1155/2014/191256
Research Article

Data-Weighting Periodic RLS Based Adaptive Control Design and Analysis without Linear Growth Condition

1School of Automation & Electronic Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
2Advanced Control Systems Lab, School of Electronics & Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Received 5 March 2014; Accepted 27 June 2014; Published 10 July 2014

Academic Editor: Nazim I. Mahmudov

Copyright © 2014 Ronghu Chi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A new periodic recursive least-squares (PRLS) estimator is developed with data-weighting factors for a class of linear time-varying parametric systems where the uncertain parameters are periodic with a known periodicity. The periodical time-varying parameter can be regarded as a constant in the time interval of a periodicity. Then the proposed PRLS estimates the unknown time-varying parameter from period to period in batches. By using equivalent feedback principle, the feedback control law is constructed for the adaptive control. Another distinct feature of the proposed PRLS-based adaptive control is that the controller design and analysis are done via Lyapunov technology without any linear growth conditions imposed on the nonlinearities of the control plant. Simulation results further confirm the effectiveness of the presented approach.