Modification of non‐Newtonian flow behavior of aqueous solution of poly(vinyl alcohol) by conducting polypyrrole prepared by in situ polymerization of pyrrole

The rheological behavior of an aqueous solution of poly(vinyl alcohol) (PVA) and polypyrrole (PPY) dispersions prepared by ferric chloride (FeCl₃)‐catalyzed polymerization of pyrrole was investigated at 12°C using a coaxial rotational viscometer. The results show that the addition of a low dose of FeCl₃ to the PVA solution greatly influences its rheology. The prominent shear‐thickening (dilatant) nature of PVA turns significantly pseudoplastic (shear thinning) in the presence of FeCl₃. Polypyrrole‐loaded PVA was obtained in a stable, optically clear dispersion by in situ polymerization of pyrrole in an aqueous PVA solution (5%) using FeCl₃ as the oxidative catalyst at 12°C. The PPY dispersions in aqueous PVA systems having a low loading of PPY and low Fe⁺³ content retain the dilatant character of an aqueous PVA solution; however, for an aqueous PVA system having a relatively high PPY loading and also a high Fe⁺³ content, prominent pseudoplastic (shear thinning) behavior is exhibited. The odd novel rheological patterns exhibited by a PVA solution in the absence and presence of FeCl₃ and the PVA–PPY dispersions containing FeCl₃ under different sets of conditions are explained on the basis of the complexation of PVA by Fe⁺³ and related ions and also as a consequence of some degree of H‐bonding and chemical grafting between the support polymer PVA and the PPY formed. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 91: 3737–3741, 2004     

Synthesis and evaluation of liquid amine‐terminated polybutadiene rubber and its role in epoxy toughening

Epoxy resin is widely used for coatings, adhesives, castings, electrical insulation materials, and other applications. However, unsolved problems still remain in its applications. The main problem is low toughness: cured epoxy resin is rather brittle, with poor resistance to the propagation of cracks derived from the internal stress generated by shrinkage in the cooling process from cure temperature to room temperature. The objective of this study was to improve the flexibility and toughness of diglycidyl ether of bisphenol A based epoxy resin with a liquid rubber. For this purpose, amine‐terminated polybutadiene (ATPB) was synthesized. The product was characterized by Fourier transform infrared and NMR spectroscopy and elemental analysis. ATPB‐modified epoxy networks were made by curing with an ambient‐temperature curing agent, triethylene tetramine. We varied the epoxy/liquid rubber compositions to study the effect of toughener concentration on the impact and thermal properties. Higher mechanical properties were obtained for epoxy resins toughened with 1 phr ATPB. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 2446–2453, 2005     

Prediction of flank wear by using back propagation neural network modeling when cutting hardened H-13 steel with chamfered and honed CBN tools

Productivity and quality in the finish turning of hardened steels can be improved by utilizing predicted performance of the cutting tools. This paper combines predictive machining approach with neural network modeling of tool flank wear in order to estimate performance of chamfered and honed Cubic Boron Nitride (CBN) tools for a variety of cutting conditions. Experimental work has been performed in orthogonal cutting of hardened H-13 type tool steel using CBN tools. At the selected cutting conditions the forces have been measured using a piezoelectric dynamometer and data acquisition system. Simultaneously flank wear at the cutting edge has been monitored by using a tool makers microscope. The experimental force and wear data were utilized to train the developed simulation environment based on back propagation neural network modeling. A trained neural network system was used in predicting flank wear for various different cutting conditions. The developed prediction system was found to be capable of accurate tool wear classification for the range it had been trained.     

Adaptive output feedback tracking control of robot manipulators using position measurements only

In this paper, a new adaptive neuro controller for trajectory tracking is developed for robot manipulators without velocity measurements, taking into account the actuator constraints. The controller is based on structural knowledge of the dynamics of the robot and measurements of joint positions only. The system uncertainty, which may include payload variation, unknown nonlinearities and torque disturbances is estimated by a Chebyshev neural network (CNN). The adaptive controller represents an amalgamation of a filtering technique to generate pseudo filtered tracking error signals (for the elimination of velocity measurements) and the theory of function approximation using CNN. The proposed controller ensures the local asymptotic stability and the convergence of the position error to zero. The proposed controller is robust not only to structured uncertainty such as payload variation but also to unstructured one such as disturbances. Moreover the computational complexity of the proposed controller is reduced as compared to the multilayered neural network controller. The validity of the control scheme is shown by simulation results of a two-link robot manipulator. Simulation results are also provided to compare the proposed controller with a controller where velocity is estimated by finite difference methods using position measurements only.     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

Delay‐dependent LMI condition for global asymptotic stability of discrete‐time uncertain state‐delayed systems using quantization/overflow nonlinearities

A delay‐dependent criterion for the global asymptotic stability of a class of uncertain discrete‐time state‐delayed systems using various combinations of quantization and overflow nonlinearities is presented. The proposed criterion is in the form of a linear matrix inequality and, hence, computationally tractable. A numerical example highlighting the usefulness of the proposed criterion is given. Copyright © 2010 John Wiley & Sons, Ltd.     

Cooperative adaptive control for synchronization of second‐order systems with unknown nonlinearities

This paper studies synchronization to a desired trajectory for multi‐agent systems with second‐order integrator dynamics and unknown nonlinearities and disturbances. The agents can have different dynamics and the treatment is for directed graphs with fixed communication topologies. The command generator or leader node dynamics is also nonlinear and unknown. Cooperative tracking adaptive controllers are designed based on each node maintaining a neural network parametric approximator and suitably tuning it to guarantee stability and performance. A Lyapunov‐based proof shows the ultimate boundedness of the tracking error. A simulation example with nodes having second‐order Lagrangian dynamics verifies the performance of the cooperative tracking adaptive controller. Copyright © 2010 John Wiley & Sons, Ltd.     

Closed-loop identification using direct approach and high order ARX/GOBF-ARX models

Model accuracy plays a key role in the performance of advanced, model predictive control algorithms. Model fidelity is usually affected by routine operating condition changes, which necessitate reidentification. From several theoretical and practical considerations, it is recommended that such re-identification be performed under closed-loop conditions. The direct approach for closed-loop identification, owing to its simplicity, is better suited for MPC. In order to yield unbiased and consistent parameter estimates, however, this approach requires the noise model to be sufficiently parameterized. Towards this objective, high order ARX models are the most suitable candidates from the viewpoint of ease of parameter estimation. For multivariable systems, however, the identification of high order ARX models would require longer experiments to be performed. This being undesirable from a practical viewpoint, there is a need for a parsimonious parameterization that would retain the benefits of high order ARX models. In this work, we propose to use generalized orthonormal basis filters (GOBFs) to achieve this parsimonous parameterization. Further, we propose an approach to obtain reduced order models by emphasizing important frequencies so as to suitably shape the bias. We also show that the choice of the GOBF parameterization has another important merit, viz. their ability to perform well even with minimal perturbation data or short experiment times. The efficacy of the proposed approach is demonstrated via simulations on the benchmark Shell Control Problem and a laboratory quadruple tank setup.     

Differential regulation of redox proteins and chaperones in HbEβ-thalassemia erythrocyte proteome

Purpose: In (hemoglobin, Hb) HbEβ‐thalassemia, HbE (β‐26 Glu→Lys) interacts with β‐thalassemia to produce clinical manifestation of varying severity. This is the first proteomic effort to study changes in protein levels of erythrocytes isolated from HbEβ‐thalassemic patients compared to normal. Experimental design: We have used 2‐DE and MALDI‐MS/MS‐based techniques to investigate the differential proteome profiling of membrane and Hb‐depleted fraction of cytosolic proteins of erythrocytes isolated from the peripheral blood samples of HbEβ‐thalassemia patients and normal volunteers. Results: Our study showed that redox regulators such as peroxiredoxin 2, Cu‐Zn superoxide dismutase and thioredoxin and chaperones such as α‐hemoglobin stabilizing protein and HSP‐70 were upregulated in HbEβ‐thalassemia. We have also observed larger amounts of membrane associated globin chains and indications of disruption of spectrin‐based junctional complex in the membrane skeleton of HbEβ‐thalassemic erythrocytes upon detection of low molecular weight fragments of β‐spectrin and decrease in β‐actin and dematin content. Conclusion and clinical relevance: We have observed interesting changes in the proteomic levels of redox regulators and chaperons in the thalassemic hemolysates and have observed strong correlation or association of the extent of such proteomic changes with HbE levels. This could be important in understanding the role of HbE in disease progression and pathophysiology.