Rendezvous in space with minimal sensing and coarse actuation

In this paper, we propose a control law to achieve a rendezvous of autonomous vehicles moving in three-dimensional (3D) space, using minimal data sensing and quantized control. A pre-assigned graph uniquely assigns the pursuer-target pair in a cyclic manner. A quantized control law has been proposed which allows the vehicle to pitch and yaw simultaneously in the required direction and track its target agent. The only measurement required for the proposed control law is the quadrant from which the target vehicle moves out of the field-of-view of the pursuing vehicle. A Lyapunov function is chosen to find a domain for the field-of-view which guarantees rendezvous under the proposed control law. Computer simulations are presented to demonstrate the control law.     

A Novel Multi-agent Formation Control Law With Collision Avoidance

In this paper a stable formation control law that simultaneously ensures collision avoidance has been proposed. It is assumed that the communication graph is undirected and connected. The proposed formation control law is a combination of the consensus term and the collision avoidance term (CAT). The first order consensus term is derived for the proposed model, while ensuring the Lyapunov stability. The consensus term creates and maintains the desired formation shape, while the CAT avoids the collision. During the collision avoidance, the potential function based CAT makes the agents repel from each other. This unrestricted repelling magnitude cannot ensure the graph connectivity at the time of collision avoidance. Hence we have proposed a formation control law, which ensures this connectivity even during the collision avoidance. This is achieved by the proposed novel adaptive potential function. The potential function adapts itself, with the online tuning of the critical variable associated with it. The tuning has been done based on the lower bound of the critical variable, which is derived from the proposed connectivity property. The efficacy of the proposed scheme has been validated using simulations done based on formations of six and thirty-two agents respectively.      

Invariant analysis and conservation laws of (2+1) dimensional time-fractional ZK–BBM equation in gravity water waves

This paper intends to make an in-depth study on the symmetry properties and conservation laws of the ($2+1$) dimensional time fractional Zakharov–Kuznetsov–Benjamin–Bona–Mahony (ZK–BBM) equation with Riemann–Liouville fractional derivative. Symmetry properties have been investigated here via Lie symmetry analysis method. In view of Erdélyi-Kober fractional differential operator, the reduction of ($2+1$) dimensional time fractional ZK–BBM equation has been done into fractional ordinary differential equation. To analyse the conservation laws, new theorem of conservation law has been proposed here for constructing the new conserved vectors for ($2+1$) dimensional time fractional ZK–BBM equation with the help of formal Lagrangian.     

An efficient fast algorithm for discovering closed+ high utility itemsets

In recent years, high utility itemsets (HUIs) mining from the transactional databases becomes one of the most emerging research topic in the field of data mining due to its wide range of applications in online e-commerce data analysis, identifying interesting patterns in biomedical data and for cross marketing solutions in retail business. It aims to discover the itemsets with high utilities efficiently by considering item quantities in a transaction and profit values of each item. However, it produces a tremendous number of HUIs, which imposes further burden in analysis of the extracted patterns and also degrades the performance of mining methods. Mining the set of closed ⁺ high utility itemsets (CHUIs) solves this issue as it is a loss-less and condensed representation of all HUIs. In this paper, we aim to present a new algorithm for finding CHUIs from a transactional database, called the CHUM (Closed ⁺ High Utility itemset Miner), which is scalable and efficient. The proposed mining algorithm adopts a tricky aimed vertical representation of the database in order to speed up the execution time in generating itemset closures and compute their utility information without accessing the database. The proposed method makes use of the item co-occurrences strategy in order to further reduce the number of intersections needed to be performed. Several experiments are conducted on various sparse and dense datasets and the simulation results clearly show the scalability and superior performance of our algorithm as compared to those for the existing state-of-the-art CHUD (Closed ⁺ High Utility itemset Discovery) algorithm.     

Waste collection vehicle routing problem with time windows

In this paper, we address a real life waste collection vehicle routing problem with time windows (VRPTW) with consideration of multiple disposal trips and drivers’ lunch breaks. Solomon's well-known insertion algorithm is extended for the problem. While minimizing the number of vehicles and total traveling time is the major objective of vehicle routing problems in the literature, here we also consider the route compactness and workload balancing of a solution since they are very important aspects in practical applications. In order to improve the route compactness and workload balancing, a capacitated clustering-based waste collection VRPTW algorithm is developed. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems at Waste Management, Inc. A set of waste collection VRPTW benchmark problems is also presented in this paper.Waste collection problems are frequently considered as arc routing problems without time windows. However, that point of view can be applied only to residential waste collection problems. In the waste collection industry, there are three major areas: commercial waste collection, residential waste collection and roll-on-roll-off. In this paper, we mainly focus on the commercial waste collection problem. The problem can be characterized as a variant of VRPTW since commercial waste collection stops may have time windows. The major variation from a standard VRPTW is due to disposal operations and driver's lunch break. When a vehicle is full, it needs to go to one of the disposal facilities (landfill or transfer station). Each vehicle can, and typically does, make multiple disposal trips per day. The purpose of this paper is to introduce the waste collection VRPTW, benchmark problem sets, and a solution approach for the problem. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems of Waste Management, the leading provider of comprehensive waste management services in North America with nearly 26,000 collection and transfer vehicles.     

Functional link neural network approach to solve structural system identification problems

System identification problems are generally inverse vibration problems. Sometimes it is difficult to handle the inverse problems by traditional methods and classical artificial neural network. As such, the objective of this paper is to identify structural parameters by developing a novel functional link neural network (FLNN) model. FLNN model is more efficient than multi-layer neural network (MNN) as computation is less because hidden layer is not required. Here, single-layer neural network with multi-input and multi-output with feed-forward neural network model and principle of error back propagation has been used to identify structural parameters. The hidden layer is excluded by enlarging the input patterns with the help of Legendre and Hermite polynomials. Comparison of results among MNN, Legendre neural network, Hermite neural network and desired is considered and it is found that FLNN models are more effective than MNN.

     

Seismic performance of buckling-restrained braced frames with varying beam-column connections

The effect of beam-column connections and brace configurations on the overall seismic response of a medium-rise bucklingrestrained braced frame (BRBF) is analytically evaluated in the present study. Two types of brace configurations (chevron and Double-X) and a combination of the moment-resisting and the non-moment-resisting beam-column connections are considered. A total of five design cases are studied for a seven-story BRBF in which a constant value of response reduction (R) factor equal to 8 is considered in the design. Nonlinear dynamic analyses are carried out for all study frames for an ensemble of forty ground motions representing the DBE and MCE hazard levels. Fragility curves are developed for all study frames considering the interstory drift ratio and residual drift ratio as the damage parameters. Results showed that a higher value of response reduction factor should be adopted in the design of BRBFs for both pinned and rigid beam-column connections. Further, in order to achieve the desired seismic performance of BRBFs, Double-X brace configurations and rigid beam-column connections at the alternate story levels should be used.     

A novel approach for high precision rapid potentiometric titrations: application to hydrazine assay

We propose a high precision rapid personal computer (PC) based potentiometric titration technique using a specially designed mini-cell to carry out redox titrations for assay of chemicals in quality control laboratories attached to industrial, R&D, and nuclear establishments. Using this technique a few microlitre of sample (50-100 μl) in a total volume of ~2 ml solution can be titrated and the waste generated after titration is extremely low comparing to that obtained from the conventional titration technique. The entire titration including online data acquisition followed by immediate offline analysis of data to get information about concentration of unknown sample is completed within a couple of minutes (about 2 min). This facility has been created using a new class of sensors, viz., pulsating sensors developed in-house. The basic concept in designing such instrument and the salient features of the titration device are presented in this paper. The performance of the titration facility was examined by conducting some of the high resolution redox titrations using dilute solutions--hydrazine against KIO(3) in HCl medium, Fe(II) against Ce(IV) and uranium using Davies-Gray method. The precision of titrations using this innovative approach lies between 0.048% and 1.0% relative standard deviation in different redox titrations. With the evolution of this rapid PC based titrator it was possible to develop a simple but high precision potentiometric titration technique for quick determination of hydrazine in nuclear fuel dissolver solution in the context of reprocessing of spent nuclear fuel in fast breeder reactors.     

Enhancement of electron mobility in GaAs/AlxGa1-xAs square-parabolic double quantum well HEMT structure

Microsystem Technologies - We show that the enhancement of electron mobility μ as function of well width w can be achieved in a GaAs/AlxGa1-xAs square-parabolic double quantum well (SPDQW)...     

Process optimization for biodiesel production from Jatropha, Karanja and Polanga oils

Petroleum sourced fuels is now widely known as non-renewable due to fossil fuel depletion and environmental degradation. Renewable, carbon neutral, transport fuels are necessary for environmental and economic sustainability. Biodiesel derived from oil crops is a potential renewable and carbon neutral alternative to petroleum fuels. Chemically, biodiesel is monoalkyl esters of long chain fatty acids derived from renewable feed stock like vegetable oils and animal fats. It is produced by transesterification in which, oil or fat is reacted with a monohydric alcohol in presence of a catalyst. The process of transesterification is affected by the mode of reaction condition, molar ratio of alcohol to oil, type of alcohol, type and amount of catalysts, reaction time and temperature and purity of reactants. In the present paper various methods of preparation of biodiesel from non-edible filtered Jatropha (Jatropha curcas), Karanja (Pongamia pinnata) and Polanga (Calophyllum inophyllum) oil have been described. Mono esters (biodiesel) produced and blended with diesel were evaluated. The technical tools and processes for monitoring the transesterification reactions like TLC, GC and HPLC have also been used.