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Kulkarni A.,Medicaps Institute of Technology and Management
2014 IEEE International Conference on Computational Intelligence and Computing Research, IEEE ICCIC 2014 | Year: 2015

This paper presents an adaptive control strategy which combines the hierarchical control scheme with adaptive wavelet neural network for a class of multi-input multi-output (MIMO) underactuated systems with uncertain dynamics. Proposed scheme develops a systematic framework of the control components by applying hierarchical scheme to underactuated system. Wavelet neural networks are used to mimic the system uncertainties. Adaptive parameters of the wavelet network are tuned on line using gradient based approach. Uniformly ultimately bounded (UUB) stability of the closed loop system is analyzed in the sense of Lyapunov theory. Simulation results demonstrate the performance of proposed control scheme © 2014 IEEE.


Kulkarni A.,Medicaps Institute of Technology and Management
2013 IEEE International Conference on Computational Intelligence and Computing Research, IEEE ICCIC 2013 | Year: 2013

This paper presents an adaptive controller with wavelet neural network tuner for a class of uncertain underactuated systems. Proposed scheme utilizes the concept of hierarchical structure error surface. Hierarchical structure is obtained by recursive coupling of error surfaces designed for individual subsystems. Error surface coupling is carried out such that the last level error surface includes the error surfaces of all the subsystems. An adaptive control scheme which utilizes wavelet neural network as an adaptive approximator for system uncertainties is proposed to solve the tracking control problem of various subsystems. Stability of integrated error surface and boundedness of closed loop signals is proved in Lyapunov sense. Effectiveness of proposed scheme is illustrated through simulation. low retrieval by CD-ROM software, please include. © 2013 IEEE.


Sharma M.,Medicaps Institute of Technology and Management | Verma A.,Institute of Engineering and Technology
Procedia Engineering | Year: 2012

This paper is concerned with the observer designing problem for the suppression of chatter occurrence due to the existence of hysteresis and time delay in an uncertain two degree of freedom piezo-electric actuated metal cutting is proposed and the novelty is that the Wavelet Neural networks (WNN) observer using reinforcement learning is first incorporated into the controller design for a metal cutting system. An adaptive control strategy is proposed to suppress the undesirable chattering in the turning process. A piezoactuator is introduced for the regulation of the cutting tool displacement as its structure is independent of the tool holder in the machine. Reinforcement learning is used via two Wavelet Neural networks (WNN), critic WNN and action WNN, which are combined to form an adaptive WNN controller. The "strategic" utility function is approximated by the critic WNN and is minimized by the action WNN. Adaptation laws are developed for the online tuning of wavelets parameters. By Lyapunov approach, the uniformly ultimate boundedness of the closed-loop tracking error is verified. Finally, a simulation is performed to verify the effectiveness and performance of the proposed method in eliminating the chattering. © 2012 Published by Elsevier Ltd.


Sharma M.,Medicaps Institute of Technology and Management | Verma A.,Institute of Engineering and Technology
Procedia Engineering | Year: 2012

This Paper investigates the mean to design the reduced order observer and observer based controller for a class of uncertain delayed nonlinear system subjected to actuator saturation using Actor Critic architecture. A new design approach of wavelet based adaptive reduced order observer is proposed. The task of the proposed wavelet adaptive reduced order observer is to identify the unknown system dynamics and to reconstruct the states of the system. Wavelet neural network (WNN) is implemented to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. Reinforcement learning is applied through Actor-Critic architecture where a separate structure is for both perception (critic) and action (actor). Reinforcement learning is used via two Wavelet Neural networks (WNN), critic WNN and action WNN, which are combined to form an adaptive WNN controller. The critic WNN approximates the "strategic" utility function which is then minimized by the action WNN. Using the feedback control, based on reconstructed states, the behavior of closed loop system is investigated. By Lyapunov- Krasovskii approach, the closed- loop tracking error is proved to be uniformly ultimate bounded. A numerical example is provided to verify the effectiveness of theoretical development. © 2012 Published by Elsevier Ltd.


Panda D.K.,Medicaps Institute of Technology and Management | Chakraborty A.,Indian Institute of Technology Kharagpur
International Journal of Microwave and Optical Technology | Year: 2015

A method of moment based analysis of longitudinal H-plane rectangular waveguide power dividers and combiners for high frequency application has been presented using Multi Cavity Modeling Technique (MCMT). The proposed power dividers/combiners can be used as H-plane tee. These longitudinal power dividers/combiners have good agreement with the MCMT and CST microwave studio simulated data. All these structures are well matched without any additional matching. For the Ku, K and Ka band operation these structures provide wide band responses. © 2015 IAMOT.


Saluja R.,Medicaps Institute of Technology and Management | Boyat A.,Medicaps Institute of Technology and Management
2015 International Conference on Computing, Communication and Security, ICCCS 2015 | Year: 2015

An efficient method of removing noise from the image while preserving edges and other details is a great challenge for researcher. Image denoising refers to the task of recovering a good estimate of the true image from the degraded image without altering and changing useful structure in the image such as discontinuities and edges. Various algorithm has been developed in past for image denoising but still it has scope for improvement. In this paper, we introduced an intelligent iterative noise variance estimation system which denoised the noisy image. Proposed algorithm is based on wavelet transform that denoised the noisy image by adding weighted highpass filtering coefficients in wavelet domain that is the novelty of the proposed work. Thereafter denoised algorithm further enhanced by adaptive wiener filter in order to achieve the maximum PSNR. Experimental results show that the proposed algorithm improves the denoising performance measured in terms of performance parameter and gives better visual quality. Mean Square Error (MSE), Root Mean Square Error (RMSE) and Peak Signal to Noise Ratio (PSNR) used as a performance parameters which measure the quality of an image. © 2015 IEEE.


Shaikh S.,Medicaps Institute of Technology and Management | Panda D.K.,Medicaps Institute of Technology and Management
2015 International Conference on Computing, Communication and Security, ICCCS 2015 | Year: 2015

The major part of smart antenna system is the selection of beam forming algorithms in adaptive antenna arrays. Adaptive beam forming algorithms help us to adjust the weight of antenna arrays such that a main beam is formed in the direction of desired target and nulls in the direction of undesired targets. This reduces interference and increases the capacity of communication network which are the desired properties of smart antenna. This piece of work provides comparative analysis of linear least mean square (LMS) and decision feedback equalizer based least mean square (DFE-LMS) algorithm through simulating various parameters such as power, phase and amplitude. Implementation is done with the help of Mat-lab l. The result shows that DFE-LMS algorithm is a more useful one. © 2015 IEEE.


Agrawal A.,Medicaps Institute of Technology and Management
International Journal of ChemTech Research | Year: 2013

This paper consists of a proposed solar water pumping system for a single story house. The proposed system will be used to pump government's supply water stored in an under-ground water storage tank to overhead drinking water storage tank of a single story house. The pump will get the power by a solar panel. Solar energy is the best renewable source of energy. Solar panel converts solar energy to solar power. This solar water pumping system is proposed without battery backup that will reduce the initial cost. DC pump is proposed because DC pumps uses one third to one halfthe energy of a conventional AC pump this will reduce power consumption. The motive of this study is to reduce the initial cost of solar pumping system and to utilize solar energy to run pump which further results in reduction of electricity bills.


Jain P.,Medicaps Institute of Technology and Management | Rane D.,Medicaps Institute of Technology and Management | Patidar S.,Medicaps Institute of Technology and Management
Proceedings of the 2011 World Congress on Information and Communication Technologies, WICT 2011 | Year: 2011

Cloud Computing has emerged as a major information and communications technology trend and has been proved as a key technology for market development and analysis for the users of several field. The practice of computing across two or more data centers separated by the Internet is growing in popularity due to an explosion in scalable computing demands. However, one of the major challenges that faces the cloud computing is how to secure and protect the data and processes the data of the user. The security of the cloud computing environment is a new research area requiring further development by both the academic and industrial research associations. While cloud-bursting is addressing this process of scaling up and down across data centers. To provide secure and reliable services in cloud computing environment is an important issue. One of the security issues is how to reduce the impact of denial-of-service (DoS) attack or distributed denial-of-service (DDoS)in this environment. In this paper we survey several aspects of cloud computing and the security concerns and proposed a novel approach that is Cloud Bursting Brokerage and Aggregation (CBBA). In this approach we consider three clouds for bursting and aggregation operation. We also used secure sharing mechanism so that the cloud resources are shared among different cloud environment. © 2011 IEEE.


Panda D.K.,Medicaps Institute of Technology and Management | Shaikh S.,Medicaps Institute of Technology and Management
International Journal of Engineering and Technology | Year: 2016

The "Smart" part of smart antenna system is the weight adjustment factor. The adaptive algorithms are used in smart antenna in order to adjust the weight of antenna arrays in a way that a main lobe is formed in the direction of desired user and nulls are formed in the direction of undesired user. In this piece of work we have done a comparative analysis of Least Mean Square (LMS) and Decision Feedback Equalizer based Least Mean Square (DFE-LMS) adaptive algorithms on the basis of Signal to Noise Ratio (SNR) and Bit Error Rate (BER). The simulation results observe the graph between SNR and BER on varying the number of iterations as well as modulation index. Implementation is done with the help of Matlab. The result shows that DFE-LMS algorithm has better performance than LMS.

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