Identification of Disturbed Control Systems

Abstract

This paper studies the identification of nonlinearly parameterized control systems in given experiments. Several identifiability criteria are established and an implementable algorithm is proposed for practicality with the convergence rate explicitly computed.

References in corpus (1)

• Conditional least squares estimation in nonstationary nonlinear stochastic regression models