In this paper, we consider a new inventory control technique for large-scale supply chains including repairs. The part flow is bidirectional with broken parts propagated upstream for repair. It is well known that available optimization techniques for inventory control for bidirectional stochastic supply chains are computationally intractable and also necessitate several simplifying assumptions. In contrast, the proposed approach is an adaptive scheme that scales well to practically interesting large-scale multi-item supply chains. Furthermore, practical issues such as stochastic transport delays, manufacturing times, and repair times and probabilistic characterization of part repair success are handled in a unified framework. The control scheme is based on a hierarchical two-level architecture that comprises an adaptive set point generator and a lower-level order-up-to policy. An application to aircraft supply chains involving multiple original equipment manufacturers (OEMs), depots, bases, squadrons, and planes is also investigated.

Describes how decentralized control theory can be used to analyze the control of multiple cooperative robotic vehicles. Models of cooperation are discussed and related to the input/output reachability, structural observability, and controllability of the entire system. Whereas decentralized control research in the past has concentrated on using decentralized controllers to partition complex physically interconnected systems, this work uses decentralized methods to connect otherwise independent nontouching robotic vehicles so that they behave in a stable, coordinated fashion. A vector Liapunov method is used to prove stability of two examples: the controlled motion of multiple vehicles along a line and the controlled motion of multiple vehicles in formation. Also presented are three applications of this theory: controlling a formation, guarding a perimeter, and surrounding a facility.

An analysis is made of the experimental results of a minimum-time trajectory control scheme for a two-link flexible robot. An offline optimization routine determines a minimum-time, straight-line tip trajectory which stays within the torque constraints of the motors and ends with no vibrational transients. An efficient finite-element model is used in the optimization to approximate the flexible arm dynamics. The control strategy described is used to determine the feedback gains for the position, velocity, and strain gage signals from a quadratic cost criterion based on the finite-element model linearized about the straight-line tip trajectory. These feedback signals are added to the modeled torque values obtained from the optimization routine and used to control the robot arm actuators. The results indicate that this combination of model-based and error-driven control strategies, achieves a closer tracking of the desired trajectory and a better handling of modeling errors than either strategy alone.>