Controlled Markov chains with constraints

We consider the ergodic control of a Markov chain on a countable state space with a compact action space in presence of finitely many (say,m) ergodic constraints. Under a condition on the cost functions that penalizes instability, the existence of an optimal stable stationary strategy randomized at a maximum ofm states is established using convex analytic arguments.     

Stochastic approximation with two time scales

Asymptotic behaviour of a two time scale stochastic approximation algorithm is analysed in terms of a related singular ordinary differential equation.     

Managing interprocessor delays in distributed recursive algorithms

For a class of distributed recursive algorithms, it is shown that a stochastic approximation-like tapering stepsize routine suppresses the effects of interprocessor delays. The research of the first author was supported by the grant ISTC/EE/VS/049 from the ISRO-HSc Space Technology Cell. The research of the second author was supported by U.S. Office of Naval Research Grant No.00014-92-J-1324 under an Indo-U.S. project.     

A sub-130-nm conditional keeper technique

Increasing leakage currents combined with reduced noise margins significantly degrade the robustness of wide dynamic circuits. In this paper, we describe two conditional keeper topologies for improving the robustness of sub-130-nm wide dynamic circuits. They are applicable in normal mode of operation as well as during burn-in test. A large fraction of the keepers is activated conditionally, allowing the use of strong keepers with leaky precharged circuits without significant impact on performance of the circuits. Compared to conventional techniques, up to 28% higher performance has been observed for wide dynamic gates in a 130-nm technology. In addition, the proposed burn-in keeper results in 64% active area reduction     

A variant of cyclic pursuit for target tracking applications: theory and implementation

This paper presents a variant of the cyclic pursuit strategy that can be used for target tracking applications. Cyclic pursuit has been extensively used in multi-agent systems for a variety of applications. In order to monitor a target point or to track a slowly moving vehicle, we propose to use a group of non-holonomic vehicles. At equilibrium, the vehicles form a rigid polygonal around the target while encircling it. Necessary conditions for the existence of equilibrium and the stability of equilibrium formations are analysed considering unicycle model of the vehicles. The strategy is then applied to miniature aerial vehicles (MAV) represented by 6-DOF dynamical model. Finally the results are verified in a hardware in-loop simulator in real time, which included all on-board electronics of the MAVs.     

Decentralized State Initialization with Delay Compensation for Multi-modal Sensor Networks

Decentralized processing algorithms are attractive alternatives to centralized algorithms for target tracking applications in smart sensor networks since they provide the ability to scale, reduce vulnerability, reduce communication, and share processing responsibilities among individual nodes. Sharing the processing responsibilities allows parallel processing of raw data at the individual nodes. However, this introduces other difficulties in multi-modal smart sensor networks, such as non-observability of the targets’ states at any individual node and various delays such as varying processing delays, communication delays and signal propagation delays for the different modalities. In this paper, we provide a novel algorithm to determine the initial probability distribution of multiple targets’ states in a decentralized manner. The targets’ state vectors consist of the targets’ positions and velocities on the 2D plane. Our approach can determine the state vector distribution even if the individual sensors alone are not capable of observing it. Our approach can also compensate for varying delays among the assorted modalities. The resulting distribution can be used to initialize various tracking algorithms. Our approach is based on Monte Carlo methods, where the state distributions are represented by a weighted set of discrete state realizations. A robust weighting strategy is formulated to account for missed detections, clutter and estimation delays. To demonstrate the effectiveness of the algorithm, we simulate a network with direction-of-arrival nodes and range-Doppler nodes.     

Environmentally clean synthesis of diphenylmethanes using silica gel-supported ZnCl2 and FeCl3

Lewis acids such as FeCl₃ and ZnCl₂ were supported on silica gel, alumina, zirconia and titania by co-grinding with anhydrous Lewis acids in appropriate proportions in an agate mortar. The catalysts have good shelf life and reusability. Synthesis of diphenylmethanes with these catalysts was studied; silica gel was the best support. © 1998 SCI     

Distributed topology control of wireless networks

We propose and analyaze a distributed control law that will maintain prescribed local properties of a wireless ad hoc network in the presence of node mobility, MAC layer power control and link fades. The control law uses a simple and intuitive power adaptation mechanism. We consider as an example the topology requirement of maintaining the out-degrees of each node at prescribed values and keeping the in-degree close to the out-degree. The topology objective is achieved by adapting the transmission power based only on local information. This power adaptation algorithm is analyzed using the o.d.e. approach to stochastic approximation. Simulation results verify the analysis and demonstrate its effectiveness. We also study the ability of the proposed objective to maintain connectivity. Although many heuristics are described in the literature to maintain local topological properties, the algorithm proposed in this paper is the first one that has proven convergence properties. Vivek S. Borkar got his B. Tech. (Elec. Engg.) from Indian Institute of Technology, Mumbai, in 1976, M. S. (Systems and Control) from Case Western Reserve Uni. in 1977 and Ph.D. (Elec. Engg. and Comp. Sci.) from Uni. of California, Berkeley. He was with Uni. of Twente (1980–81), TIFR Centre, Bangalore (1982–89), Indian Inst. of Science (1989–99), and has been with School of Technology and Computer Science, Tata Inst. of Fundamental Research, Mumbai, since April 1999. His research interests include stochastic optimization and applications. D. Manjunath received his B.E. from Mysore University, M.S. from Indian Institute of Technology, Madras and Ph.D. from Rensselaer Polytechnic Inst, Troy NY in 1986, 1989 and 1993 respectively. He has been a summer intern in the Corporate R & D Center of GE (1990), a visiting faculty in the Computer and Information Sciences Dept. of the University of Delaware (1992-93), a post doctoral fellow in the Computer Science Dept. of the University of Toronto (1993–84) and on the Electrical Engineering faculty of the Indian Inst. of Technology, Kanpur (1994–98).He has been with the Elec Enggg. Dept. of Indian Inst. of Technology, Bombay in Mumbai since July 1998 where he is now an Associate Professor. His research interests are in the areas of communication networks, performance analysis of systems, queueing systems and multimedia communications.