Locally optimal risk-sensitive controllers for strict-feedback nonlinear systems

M Tamer Basar, Cheng Tang

Research output: Contribution to journalArticlepeer-review


For a class of risk-sensitive nonlinear stochastic control problems with dynamics in strict-feedback form, we obtain through a constructive derivation state-feedback controllers which (i) are locally optimal, (ii) are globally inverse optimal, and (iii) lead to closed-loop system trajectories that are bounded in probability. The first feature implies that a linearized version of these controllers solve a LEQG problem, and the second feature says that there exists an appropriate cost function according to which these controllers are optimal.

Original languageEnglish (US)
Pages (from-to)115-120
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1999

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality


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