Sliding mode control-based algorithms for consensus in connected swarms

In this article, finite-time consensus algorithms for a swarm of self-propelling agents based on sliding mode control and graph algebraic theories are presented. Algorithms are developed for swarms that can be described by balanced graphs and that are comprised of agents with dynamics of the same order. Agents with first and higher order dynamics are considered. For consensus, the agents' inputs are chosen to enforce sliding mode on surfaces dependent on the graph Laplacian matrix. The algorithms allow for the tuning of the time taken by the swarm to reach a consensus as well as the consensus value. As an example, the case when a swarm of first-order agents is in cyclic pursuit is considered.

Embedded Thin Film Resistors on BCB by Low-Cost PWB Compatible Electroless Plating by Direct Foil Lamination Transfer Processes

Benzocyclobutene (BCB) has been proposed as a board level dielectric for advanced system-on-package (SOP) module primarily due to its attractive low-loss (for RF application) and thin film (for high density wiring) properties. Realization of embedded resistors on low loss benzocyclobutene (dielectric loss ~0.0008 at > 40 GHz) has been explored in this study. Two approaches, viz, foil transfer and electroless plating have been attempted for deposition of thin film resistors on benzocyclobutene (BCB). Ni-P alloys were plated using conventional electroless plating, and NiCr and NiCrAlSi foils were used for the foil transfer process. This paper reports NiP and NiWP electroless plated embedded resistors on BCB dielectric for the first time in the literature

An Actor-Critic Algorithm for Finite Horizon Markov Decision Processes

We develop a simulation based algorithm for finite horizon Markov decision processes with finite state and finite action space. Illustrative numerical experiments with the proposed algorithm are shown for problems in flow control of communication networks and capacity switching in semiconductor fabrication.

Scalable processes for fabricating non-volatile memory devices using self-assembled 2D arrays of gold nanoparticles as charge storage nodes

We propose robust and scalable processes for the fabrication of floating gate devices using ordered arrays of 7 nm size gold nanoparticles as charge storage nodes. The proposed strategy can be readily adapted for fabricating next generation (sub-20 nm node) non-volatile memory devices.

Analysis of light‐induced processes in bacteriorhodopsin and its application for spatial light modulation

A simplified energy‐level scheme is proposed for the photochemical cycle of the bacteriorhodopsin molecule. Rate equations are solved for the detailed light‐induced processes based on this model and the intensity‐induced population densities in various states of the molecule at steady state are computed which are used to obtain an analytic expression for the absorption coefficient of the modulation beam. Modulation of the probe laser‐beam transmission by the modulation‐laser‐beam intensity‐induced population changes is analyzed. It is predicted that for a probe beam at 412 nm up to 82% modulation can be achieved using a laser beam intensity of 3.2 W/cm2 at 570 nm. For temperatures ∼77 K, the transmission at 610 nm can be switched from zero to 81% for modulating laser intensity of 11 W/cm2. Construction of a spatial light modulator based on bacteriorhodopsin molecules is proposed and some of its features are discussed.

Transport processes in one component plasmas using Landau equation

A system of transport equations have been obtained for plasma of electrons and having a background of positive ions in the presence of an electric and magnetic field. The starting kinetic equation is the well-known Landau kinetic equation. The distribution function of the kinetic equation has been expanded in powers of generalized Hermite polynomials and following Grad, a consistent set of transport equations have been obtained. The expressions for viscosity and heat conductivity have been deduced from the transport equation.

First passage distributions for long memory processes

We study the distribution of first passage time for Levy type anomalous diffusion. A fractional Fokker-Planck equation framework is introduced.For the zero drift case, using fractional calculus an explicit analytic solution for the first passage time density function in terms of Fox or H-functions is given. The asymptotic behaviour of the density function is discussed. For the nonzero drift case, we obtain an expression for the Laplace transform of the first passage time density function, from which the mean first passage time and variance are derived.

Monsoon Regimes and Processes in CCSM4. Part I: The Asian-Australian Monsoon

The simulation characteristics of the Asian-Australian monsoon are documented for the Community Climate System Model, version 4 (CCSM4). This is the first part of a two part series examining monsoon regimes in the global tropics in the CCSM4. Comparisons are made to an Atmospheric Model Intercomparison Project (AMIP) simulation of the atmospheric component in CCSM4 Community Atmosphere Model, version 4, (CAM4)] to deduce differences in the monsoon simulations run with observed sea surface temperatures (SSTs) and with ocean-atmosphere coupling. These simulations are also compared to a previous version of the model (CCSM3) to evaluate progress. In general, monsoon rainfall is too heavy in the uncoupled AMIP run with CAM4, and monsoon rainfall amounts are generally better simulated with ocean coupling in CCSM4. Most aspects of the Asian-Australian monsoon simulations are improved in CCSM4 compared to CCSM3. There is a reduction of the systematic error of rainfall over the tropical Indian Ocean for the South Asian monsoon, and well-simulated connections between SSTs in the Bay of Bengal and regional South Asian monsoon precipitation. The pattern of rainfall in the Australian monsoon is closer to observations in part because of contributions from the improvements of the Indonesian Throughflow and diapycnal diffusion in CCSM4. Intraseasonal variability of the Asian-Australian monsoon is much improved in CCSM4 compared to CCSM3 both in terms of eastward and northward propagation characteristics, though it is still somewhat weaker than observed. An improved simulation of El Nino in CCSM4 contributes to more realistic connections between the Asian-Australian monsoon and El Nino-Southern Oscillation (ENSO), though there is considerable decadal and century time scale variability of the strength of the monsoon-ENSO connection.

Processes of 30-90 days sea surface temperature variability in the northern Indian Ocean during boreal summer

During summer, the northern Indian Ocean exhibits significant atmospheric intraseasonal variability associated with active and break phases of the monsoon in the 30-90 days band. In this paper, we investigate mechanisms of the Sea Surface Temperature (SST) signature of this atmospheric variability, using a combination of observational datasets and Ocean General Circulation Model sensitivity experiments. In addition to the previously-reported intraseasonal SST signature in the Bay of Bengal, observations show clear SST signals in the Arabian Sea related to the active/break cycle of the monsoon. As the atmospheric intraseasonal oscillation moves northward, SST variations appear first at the southern tip of India (day 0), then in the Somali upwelling region (day 10), northern Bay of Bengal (day 19) and finally in the Oman upwelling region (day 23). The Bay of Bengal and Oman signals are most clearly associated with the monsoon active/break index, whereas the relationship with signals near Somali upwelling and the southern tip of India is weaker. In agreement with previous studies, we find that heat flux variations drive most of the intraseasonal SST variability in the Bay of Bengal, both in our model (regression coefficient, 0.9, against similar to 0.25 for wind stress) and in observations (0.8 regression coefficient); similar to 60% of the heat flux variation is due do shortwave radiation and similar to 40% due to latent heat flux. On the other hand, both observations and model results indicate a prominent role of dynamical oceanic processes in the Arabian Sea. Wind-stress variations force about 70-100% of SST intraseasonal variations in the Arabian Sea, through modulation of oceanic processes (entrainment, mixing, Ekman pumping, lateral advection). Our similar to 100 km resolution model suggests that internal oceanic variability (i.e. eddies) contributes substantially to intraseasonal variability at small-scale in the Somali upwelling region, but does not contribute to large-scale intraseasonal SST variability due to its small spatial scale and random phase relation to the active-break monsoon cycle. The effect of oceanic eddies; however, remains to be explored at a higher spatial resolution.

An Online Actor-Critic Algorithm with Function Approximation for Constrained Markov Decision Processes

We develop an online actor-critic reinforcement learning algorithm with function approximation for a problem of control under inequality constraints. We consider the long-run average cost Markov decision process (MDP) framework in which both the objective and the constraint functions are suitable policy-dependent long-run averages of certain sample path functions. The Lagrange multiplier method is used to handle the inequality constraints. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal solution. We also provide the results of numerical experiments on a problem of routing in a multi-stage queueing network with constraints on long-run average queue lengths. We observe that our algorithm exhibits good performance on this setting and converges to a feasible point.

Optimal Control of Markov Processes with Age-Dependent Transition Rates

We study optimal control of Markov processes with age-dependent transition rates. The control policy is chosen continuously over time based on the state of the process and its age. We study infinite horizon discounted cost and infinite horizon average cost problems. Our approach is via the construction of an equivalent semi-Markov decision process. We characterise the value function and optimal controls for both discounted and average cost cases.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.