In this paper, we extend stable inversion to nonlinear time-varying systems and study computational issues—the technique is applicable to minimum-phase as well as nonminimum-phase systems. The inversion technique is new, even in the linear time-varying case, and relies on partitioning (the dichotomic split of) the linearized system dynamics into time-varying, stable, and unstable, submanifolds....

Recently, switched systems have been found in many practical applications such as in communication network dynamics, robot manipulators, traffic management, etc. In this paper, we study the stability of time-varying linear switched systems under perturbations that satisfy linear growth condition, which is not available in current literature. By introducing a new Liao-type exponent for time-vary...

We describe an adaptive observerlidentifier for single input-single output observable nonlinear systems that can be transformed to a certain observable canonical form. We provide sufficient conditions for stability of this observer. These conditions are in terms of the structure of the system and its canonical form, the boundedness of the parameter variations, and the sufficient richness of som...

Kalman-based state estimators assume a priori knowledge of the covariance matrices of the process and observation noise. However, in most practical situations, noise statistics are often unknown and need to be estimated from measurement data. This paper presents a new auto-covariance least squares method for noise covariance estimation of linear time-varying and nonlinear systems. The new algor...