DRUM Collection: Institute for Systems Research Technical Reportshttp://hdl.handle.net/1903/43762015-05-28T07:10:33Z2015-05-28T07:10:33ZAmbiguous Behavior of Logic Bistable SystemsHurtado, MarcoElliott, David L.http://hdl.handle.net/1903/163392015-05-01T02:30:13Z1975-10-04T00:00:00ZTitle: Ambiguous Behavior of Logic Bistable Systems
Authors: Hurtado, Marco; Elliott, David L.
Abstract: The standard specification of logic bistable devices do not specify the behavior under conditions in which the input is logically undefined or in which certain kinds of multiple input changes occur. These conditions are unavoidable in logic synchronizers and arbiters. A general deterministic model of bistable devices is proposed, consisting of a non-liner differential system with some adequate properties. Analysis of this model shows that bistable devices can be driven into a logically undefined region by certain admissible inputs and can remain in this region for an unbounded length of time.1975-10-04T00:00:00ZInstances for the Generalized Regenerator Location ProblemChen, SiLjubic, IvanaRaghavan, S.http://hdl.handle.net/1903/163282015-03-23T14:06:25Z2015-01-01T00:00:00ZTitle: Instances for the Generalized Regenerator Location Problem
Authors: Chen, Si; Ljubic, Ivana; Raghavan, S.2015-01-01T00:00:00ZA GENERAL FRAMEWORK FOR CONSENSUS NETWORKSSomarakis, Christoforoshttp://hdl.handle.net/1903/163242015-03-12T02:30:09Z2015-03-10T00:00:00ZTitle: A GENERAL FRAMEWORK FOR CONSENSUS NETWORKS
Authors: Somarakis, Christoforos
Abstract: A new framework for the analysis of consensus networks is developed. The theory
consists of necessary and sufficient conditions and it is flexible enough to comprise a variety of
consensus systems. Under mild connectivity assumptions, the discussion ranges from linear, nonlinear, ordinary, functional and leader-follower models. The establishment of explicit estimates on
the rate of convergence is the central objective. Our work extends and unifies past related works in
the literature. Illustrative examples and simulations are presented to outline the theoretical results.2015-03-10T00:00:00ZNonlinear Programming Methods for Distributed OptimizationMatei, IonBaras, Johnhttp://hdl.handle.net/1903/160552015-01-31T03:30:12Z2015-01-01T00:00:00ZTitle: Nonlinear Programming Methods for Distributed Optimization
Authors: Matei, Ion; Baras, John
Abstract: In this paper we investigate how standard nonlinear programming algorithms can be used to solve constrained
optimization problems in a distributed manner. The optimization setup consists of a set of agents interacting through
a communication graph that have as common goal the minimization of a function expressed as a sum of (possibly
non-convex) differentiable functions. Each function in the sum corresponds to an agent and each agent has associated
an equality constraint. By re-casting the distributed optimization problem into an equivalent, augmented centralized
problem, we show that distributed algorithms result naturally from applying standard nonlinear programming tech-
niques. Due to the distributed formulation, the standard assumptions and convergence results no longer hold. We
emphasize what changes are necessary for convergence to still be achieved for three algorithms: two algorithms
based on Lagrangian methods, and an algorithm based the method of multipliers. The changes in the convergence
results are necessary mainly due to the fact that the (local) minimizers of the lifted optimization problem are not
regular, as a results of the distributed formulation. Unlike the standard algorithm based on the method of multipliers,
for the distributed version we cannot show that the theoretical super-linear convergence rate can be achieved.2015-01-01T00:00:00Z