Adaptive online estimation of time-varying parameter nonlinear systems

Jing Na, Juan Yang, Xuemei Ren, Yu Guo

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

7 Citations (Scopus)


This paper addresses adaptive online estimation of time-varying parameters for a class of linearly parameterized nonlinear systems. By dividing time into small intervals, polynomials with unknown coefficients are adopted to approximate time-varying parameters within each local interval. Then a novel adaptive law for parameter estimation is developed to estimate the unknown constant coefficients of polynomials, for which the parameter estimation error is explicitly derived in terms of filter operations and used to drive the adaptations. A resetting scheme is used at the beginning of each time interval to guarantee the continuity of parameter estimation. The error convergence and the robustness against bounded external disturbances are all proved. Simulation results are included to demonstrate the effectiveness of the proposed algorithm for time-varying parameters.

Original languageEnglish
Title of host publicationChinese Control Conference, CCC
PublisherIEEE Computer Society
Number of pages6
ISBN (Print)9789881563835
Publication statusPublished - 18 Oct 2013
Event32nd Chinese Control Conference, CCC 2013 - Xi'an, United Kingdom
Duration: 26 Jul 201328 Jul 2013


Conference32nd Chinese Control Conference, CCC 2013
Country/TerritoryUnited Kingdom


  • adaptive estimation
  • parameter estimation
  • System identification
  • time-varying system


Dive into the research topics of 'Adaptive online estimation of time-varying parameter nonlinear systems'. Together they form a unique fingerprint.

Cite this