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1. A Generalized Gossip Algorithm on Convex Metric Spaces.

Author

Matei, Ion, Somarakis, Christoforos, and Baras, John S.

Subjects
*METRIC spaces, *CONVEX domains, *PROBLEM solving, *GENERALIZATION, *ALGORITHMS, *STOCHASTIC convergence
Abstract

A consensus problem consists of a group of dynamic agents who seek to agree upon certain quantities of interest. This problem can be generalized in the context of convex metric spaces that extend the standard notion of convexity. In this paper we introduce and analyze a randomized gossip algorithm for solving the generalized consensus problem on convex metric spaces, where the communication between agents is controlled by a set of Poisson counters. We study the convergence properties of the algorithm using stochastic calculus. In particular, we show that the distances between the states of the agents converge to zero with probability one and in the r^th mean sense. In the special case of complete connectivity and uniform Poisson counters, we give upper bounds on the dynamics of the first and second moments of the distances between the states of the agents. In addition, we introduce instances of the generalized consensus algorithm for several examples of convex metric spaces together with numerical simulations. [ABSTRACT FROM AUTHOR]

Published
2015
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2. PI Fuzzy Gain-Scheduling Speed Control at Startup of a Gas-Turbine Power Plant.

Author

Rodriguez-Martinez, Arnulfo, Garduno-Ramirez, Raul, and Vela-Valdes, Luis Gerardo

Subjects
*FUZZY systems, *GAS-turbine power-plants, *PROBLEM solving, *PID controllers, *ALGORITHMS, *SIMULATION methods & models, *AEROSPACE engineering
Abstract

Speed control during startup is one of the most critical tasks of gas turbine power plant operation. This paper introduces the PI fuzzy gain-scheduling (PI-FGS) controller to solve the foremost speed-control problems, including tracking of the acceleration pattern and rejection of disturbances caused by operation events throughout startup. Fundamentally, the PI-FGS synthesizes a GS controller from multiple locally tuned generalized proportional integral (PI) algorithms by means of a fuzzy system. The PI-FGS structure permits independent tuning of the tracking and rejection responses at any operating point. In addition, tuning can be carried out on-site based on the operator experience and inspection of the current plant response. Simulation experiments show that the PI-FGS may improve speed-control performance well over that provided by commercially available speed controllers, which are based on a single conventional PI algorithm. [ABSTRACT FROM PUBLISHER]

Published
2011
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