Robust output-feedback control of strict-feedback systems with unknown nonlinearities

Gurdal Arslan, M Tamer Basar

Research output: Contribution to journalConference articlepeer-review


We study the problem of output tracking for uncertain strict-feedback systems with output and derivative information. The unknown nonlinear terms in the system description are not linearly parameterized, but it is assumed that the optimal parameters that characterize a neural net based approximation to the nonlinearities lie within a known compact set. The proposed controllers, with output and derivative information, guarantee the boundedness of all signals in the closed-loop system, and, at the expense of increased control effort, the output tracking error can be driven to an arbitrarily small neighborhood of the origin arbitrarily fast. Also, the closed loop signals satisfy a relevant disturbance attenuation inequality, which, under certain conditions, implies asymptotic tracking.

Original languageEnglish (US)
Pages (from-to)4748-4753
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1999
EventThe 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA
Duration: Dec 7 1999Dec 10 1999

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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