A systematic approach to adaptive observer synthesis for nonlinear systems

Young Man Cho, Rajesh Rajamani

Research output: Contribution to journalArticlepeer-review

242 Scopus citations


Geometric techniques of controller design for nonlinear systems have enjoyed great success. A serious shortcoming, however, has been the need for access to full-state feedback. This paper addresses the issue of state estimation from limited sensor measurements in the presence of parameter uncertainty. An adaptive nonlinear observer is suggested for Lipschitz nonlinear systems, and the stability of this observer is shown to be related to finding solutions to a quadratic inequality involving two variables. A coordinate transformation is used to reformulate this inequality as a linear matrix inequality. A systematic algorithm is presented, which checks for feasibility of a solution to the quadratic inequality and yields an observer whenever the solution is feasible. The state estimation errors then are guaranteed to converge to zero asymptotically. The convergence of the parameters, however, is determined by a persistence-of-excitation-type constraint.

Original languageEnglish (US)
Pages (from-to)534-537
Number of pages4
JournalIEEE Transactions on Automatic Control
Issue number4
StatePublished - Dec 1 1997


  • Adaptive observer
  • Interior point method
  • Linear matrix inequality
  • Nonlinear systems

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