— This paper is concerned with the problem of state estimation for descriptor systems subject to uncertainties. Kalman type recursive algorithms for robust filtered, predicted and smoothed estimates are derived. A numerical example is included to demonstrate the performance of the proposed robust filter.
—In this paper we revisit the Lyapunov theory for singular systems. There are basically two well known generalized Lyapunov equations used to characterize stability for singular systems. We start with the Lya-punov theorem of , . We show that the Lyapunov equation of that theorem can lead to incorrect conclusion about stability. Some cases where that… (More)
— The optimal recursive estimation problem for general time-variant descriptor systems is considered in this paper. We show that the filter recursion can be obtained as solution of appropriate data fitting problems. We can consider the fitting evolving the entire trajectory at once or consider a one step correction.
— This paper develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.
—In this note, the presence of impulsive responses in descriptor systems and how it relates to impulse controllability and impulse observ-ability is considered. It is shown that the equivalence between impulse controllability (observability) and the existence of an impulse eliminating semistate feedback (output injection) gain, although true for square… (More)
In this paper, robotic systems when two or more underactuated manipulators are working in cooperative way are studied. The underactuation effects on object to be controlled and on load capacity of the cooperative arms are analyzed. A hybrid control of motion and squeeze force is proposed. For the motion control, a Jacobian matrix that relates the torques in… (More)
— This work addresses the problem of stochastic data fusion for systems liable to heavy disturbances, which denote environmental perturbations strong enough to modify the system's internal structure, including signal interference, sensor faults, physical structure modification, and many other sources of disturbance. In these such cases, traditional… (More)