This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...

Robustness analysis is considered for systems with structured uncertainty involving a combination of linear time-invariant and linear time-varying perturbations, and parametric uncertainty. A necessary and suucient condition for robust stability in terms of the structured singular value is obtained, based on a nite augmentation of the original problem. The augmentation corresponds to considerin...

In this paper, problems of stability in measure and optimal control are considered for an uncertain continuous-time singular system which can be described by uncertain differential equations. Singular system is assumed to be regular and impulse-free. Under some given assumptions, the existence and uniqueness of the solution, and stability in measure of the singular system are presented. Then, b...

This paper relates the singular perturbation approximation technique for model reduction to the direct truncation technique if the system model to be reduced is stable, minimal, and internally balanced. It shows that these two methods constitute two fully compatible model reduction techniques for a continuous-time system, and both methods yield a stable, minimal, and internally balanced reduced...

In this paper, we consider the time minimal problem for an Autonomous Underwater Vehicle. We investigate, on a simplified model, the existence of singular extremals and discuss their optimality status. Moreover, we prove that singular extremals corresponding to the angular acceleration are of order 2. We produce in this case a semicanonical form of our Hamiltonian system and we can conclude the...