Time Delay Compensation in Networked Control System

Networked control system is a special type of distributed control system where control loop is enclosed by communication medium. Networked Control System (NCS) suffers from the networked induced delay which may be induced in the forward path as well as in the feedback path. This delay is variable in nature. So if a controller is designed without considering the delays or considering the fixed delay then system performance will be degraded and in the worst case the system become unstable. To compensate the network induced variable transporting delay,a number of methods have been proposed in the literature such as robust control, Smith Predictor and Inteligent control theory. But there are few works reported in literature that employ Linear Quadratic Regulator (LQR) to compensate the networked induced delays.Firstly an LQR controller is designed to compensate the networked induced variable delay which is varied up to a maximum value. Then an LQG controller is designed to compensate the networked induced delay in noisy environment. Here the controller is the same controller used in LQR technique. Only difference between the standard LQR and the LQG controller said now is that it uses Kalman Filter to estimate the plant output using noisy measurement. Then an Model Predictive Controller (MPC) controller is designed using Laguerre network considering the constraints on control input and on the rate of control input. An integrator plant is considered for simulation where the above three controllers are applied. From the simulation result, it is observed that LQR gives a better step response but MPC has better disturbance rejection capacity. To validate the controllers in real-time, an experiment has been conducted in the Labrotory. In the experimental setup using one PC is considered as controller and other one is considered as plant. They are connected through an Ethernet network. From the real time experiment results it is seen that LQR exibits superior delay compensation performance

Emerging evidence on the role of secondary metabolites as nutraceutical

Nutraceuticals have time-honored considerable interest because of their reputed safety, nutritional and therapeutic potential effects. Pharmaceutical and nutritional industries are conscious of the monetary success taking advantage of the more health-seeking consumers. Natural products such as cereals are likely to form the basis of nutraceutical as its revolution represents an enormous opportunity for growth and expansion. Wheat, rice, millets, barley, oat, buckwheat, corn, sorghum, flaxseed psyllium, brown rice, and products are notify the most common cereal based functional foods and nutraceuticals. The nutrients in the cereals have identified prospective for reducing the risk of coronary heart disease, diabetes, tumor incidence, cancer risk, blood pressure, reduces the rate of cholesterol and fat absorption, delaying gastrointestinal emptying and providing gastrointestinal health. Thus, the regular insertion of cereals and their processed products can make a payment to health endorsement and disease avoidance

Analysis of magnetic field assisted finishing (MFAF) process parameters for finishing brass workpiece using Soft-Computing Technique

Abstract Magnetic Field Assisted Finishing (MFAF) process is a precise nanofinishing process. Magnetorheological (MR) fluid is the main element in MFAF process. In these process two types of motion, rotational and reciprocation is provided to the MR fluid to get uniform smooth finished surface. Brass is used as the workpiece. The input process parameters are extrusion pressure, number of finishing cycles, rotational speed of the magnet, and volume ratio of carbonyl iron particle (CIP) and silicon carbide (SiC) in the medium. The output process parameter is percentage change in surface roughness. In this study the relationship between the input and output process parameters of MFAF is established using Backpropagation neural network technique. Also a close comparison has been made between the regression analysis model and neural network model of the process parameters. From the simulation results, it has been found that the neural network model yields a more accurate result than the regression analysis method. Further an optimization study has been carried out to optimize the input process parameters to get maximum output. Genetic algorithm (GA) technique is used as the optimization technique consideringregression equation model as the objective function. The optimized process parameters agree well with the experimental results

PHYTO-PHARMACOLOGY of Berberis aristata DC: A REVIEW

ABSTRACT Plants have been the basis of many traditional medicines throughout the world for thousands of years and continue to provide new remedies to mankind. Plants are one of the richest sources of compounds. Berberis aristata is one of the plants used in Ayurveda for several remedies. Berberis aristata commonly known as  “Daru haldhi and Chitra†is spinous herb native to northern Himalaya region. The plant  is  widely distributed  from Himalayas to Srilanka, Bhutan,  and  hilly areas of  Nepal.  Berberis aristata is used  in ayurvedic  medicines  from  very  long time.  It is used as a tonic, alternative, demulscent, diaphoretic, and diuretic, in the treatment of diarrhoea, jaundice and skin diseases, syphilis, chronic rheumatism and urinary disorders. Scientific evidence suggests its versatile biological functions that support its traditional use in the orient.  Phytochemical  studies  shows  that  plant Berberis  aristata contains  mainly  yellow  colored alkaloids Berberine,  oxyberberine,  berbamine,  aromoline,  a  protoberberine  alkaloid  karachine,  palmatine, oxycanthine  and  taxilamine  and  tannins,  sugar,  starch.  The  plant  has  effective  pharmacological  action  and  shows promising future for further researches.  This review aims to highlight the ethnobotany, pharmacognostic and pharmacological uses of Berberis aristat

Inter-Landau-level Andreev Reflection at the Dirac Point in a Graphene Quantum Hall State Coupled to a NbSe2 Superconductor

Superconductivity and quantum Hall effect are distinct states of matter occurring in apparently incompatible physical conditions. Recent theoretical developments suggest that the coupling of quantum Hall effect with a superconductor can provide a fertile ground for realizing exotic topological excitations such as non-abelian Majorana fermions or Fibonacci particles. As a step toward that goal, we report observation of Andreev reflection at the junction of a quantum Hall edge state in a single layer graphene and a quasi-two dimensional niobium diselenide (NbSe2) superconductor. Our principal finding is the observation of an anomalous finite-temperature conductance peak located precisely at the Dirac point, providing a definitive evidence for inter-Landau level Andreev reflection in a quantum Hall system. Our observations are well supported by detailed numerical simulations, which offer additional insight into the role of the edge states in Andreev physics. This study paves the way for investigating analogous Andreev reflection in a fractional quantum Hall system coupled to a superconductor to realize exotic quasiparticles.Comment: published verio

DENDRIMERS IN DRUG DELIVERY, DIAGNOSIS AND THERAPY: BASICS AND POTENTIAL APPLICATIONS

This review gives concise information about the dendrimers, properties, synthesis and application in drug delivery, diagnosis and therapy. Due to their unique architecture these have improved physical and chemical properties. They show high solubility, miscibility and reactivity due to their terminal groups. Dendrimers have well defined size, shape, molecular weight and monodispersity. These properties make the dendrimers a suitable carrier in drug delivery application. Dendrimers are unimolecular miceller in nature and due to this enhances the solubility of poorly soluble drugs. Their compatibility with DNA, heparin and polyanions make them more versatile. Dendrimers, also referred as modern day polymers, they offer much more good properties than the conventional polymers. Due to their multivalent and mono disperse character dendrimers have stimulated wide interest in the field of chemistry biology, especially in applications like drug delivery, gene therapy and chemotherapy. Self assembly produces a faster means of generating nanoscopic functional and structural systems. But their actual utility in drug delivery can be assessed only after deep understanding of factors affecting their properties and their behavior in vivo. Key words: Dendrimers, PAMAM, monodispersity, Divergent-Convergent synthesis, carrier for drug deliveryÂ