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Journals and Conferences
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.
In this note, the presence of impulsive responses in descriptor systems and how it relates to impulse controllability and impulse observability 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)
This note is concerned with the problem of state estimation for descriptor systems subject to uncertainties. A Kalman type recursive algorithm is derived. Numerical examples are included to demonstrate the performance of the proposed robust filter.
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 paper deals with the H∞ recursive estimation problem for general rectangular time-variant descriptor systems in discrete time. Riccati-equation based recursions for filtered and predicted estimates are developed based on a data fitting approach and game theory. In this approach, the nature determines a state sequence seeking to maximize the estimation… (More)
In this paper, the Kalman filter and the corresponding Riccati equation for discrete-time, time-variant descriptor systems are addressed in their most general formulation. A new “9-block” form for the optimal filter is derived using deterministic approach. This new expression, besides including one step delayed state, presents an interesting simple and… (More)
Despite the solid contribution of recent techniques for the analysis of networked controls systems (NCSs), the use of dynamic controllers has received little attention in the literature. Adapting these methods to consider dynamic controllers in the feedback loop is seldom trivial, however, neglecting this class of controllers restricts the universe of… (More)
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.
This paper presents information filters in Riccati recursions and in array algorithms for descriptor systems subject to parameters uncertainties. The filters are developed in filtered and predicted forms. The inversion of the state matrix is avoided in the new information recursive formulas. Therefore, it turns out clear that the invertibility of the state… (More)