This paper proposes stability conditions and a stabilization method for linear time-varying bounded descriptor systems. Two necessary and sufficient conditions are obtained for exponential stability in terms of linear matrix differential inequalities (LMdIs) . Then, one of the stability conditions is utilized to derive a necessary and sufficient condition of an LMdI type for exponential stabilizability, where the stabilizing control law feeds back only the dynamic part of the descriptor variable. A practical method for solving the LMdI is presented to compute a feedback gain.
This paper addresses a sensor scheduling problem for a class of networked sensor systems whose sensors are spatially distributed and measurements are influenced by state dependent noise. Sensor scheduling is required to achieve power saving since each sensor operates with a battery power source. A networked sensor system usually consists of a large number of sensors, but the sensors can be classified into a few different types. We therefore introduce a concept of sensor types in the sensor model to provide fast sensor scheduling algorithms for a class of networked sensor systems. The computation time of the proposed algorithms is exponential in the number of the sensor types, while that of standard algorithms increases exponentially with the number of the sensors.
In this paper, we introduce and analyze Hamiltonian systems subject to nonholonomic affine constraints. We first sum up some concepts of Hamiltonian systems defined on both the phase space and the expanded phase space. Next, we derive nonholonomic Hamiltonian systems with affine constraints (NHSAC) by using a transformation and reduction on the expanded phase space. Then, passivity of the NHSAC with the control input term and the output equation is investigated. Finally, a coin on a rotating table is illustrated to confirm the results as a physical example.