Monitoring large supply networks can be efficiently performed by employing active radio-frequency identification (a-RFID) sensors. Relay nodes collect and process workflow information from the sensors. The knowledge derived from the collected information is periodically communicated to monitors using onboard energy sources. Energy can be saved by communicating with closer monitors. In this setup, multiple decision makers with their own deployment budget collaborate to deploy monitors for minimizing energy consumption of the relay nodes. The contribution of this paper is threefold. It elaborates a mathematical model for distributed monitor deployment in budget-constrained supply-chain networks, it proposes a heuristic technique to find near-optimal allocation of monitors in tractable manner, and it illustrates a collaborative procedure to jointly minimize energy consumption along with a fair sharing of total deployment cost among multiple decision makers. The approach is presented through a case study. In addition, benchmark results are provided for a number of problem instances.

Summary form only given. The routing and munitions management of multiple formations of unmanned combat aerial vehicles (UCAVs) through network enabled sensing will be discussed. The ability of the UCAVs to group into large formations and to divide into smaller formations on their way to high-value, tactical targets will be cast in the optimization. To solve such problem a sensory information management (SIM) network will handle data from a set of mobile sensors. SIM will determine whether sensor redundancy should and can be used, before it estimates an information state vector on the locations of the adversarial ground units and decoys. The networked UCAVs will calculate the worst-case minimization policy for an effective routing and munitions management relying on the SIM-net supplied information state vector. As in any time-critical control problem, closing the loop requires that sensor management, estimation, and high-level decision be accomplished within hard real-time constraints. Heuristic algorithms aiming at achieving real-time performance will be discussed. The effectiveness of UCAV routing and munitions management will be illustrated by means of examples featuring trajectory planning of multiple formations evolving in a dynamic urban theatre.

Robotics manipulators may exhibit flexibility that adversely affects the dynamic and even static performance of controllers designed for rigid robots. Full state measurement is costly, so that part of the state must often be reconstructed. We present the design of two observers: 1) a variable structure observer requiring the measurement of link positions to estimate the full state of a flexible joint manipulator; and 2) a reduced adaptive observer that requires the measurement of link and motor positions. Stability and robustness properties are established and we propose a methodology to design the variable structure observer by solving simultaneously a Lyapunov equation and a matching condition. Simulation results are provided to evaluate their performance.