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Design of disease prediction method based on whale optimization employed artificial neural network in tomato fruits

Materials Today: Proceedings 2020年 33卷 4907-4918页

作者： S. Dhakshina Kumar S. Esakkirajan C. Vimalraj B. Keerthi Veena Department of Electronics and Communication Engineering University College of Engineering Ramanathapuram India Department of Instrumentation and Control Systems Engineering PSG College of Technology Coimbatore Tamil Nadu India Department of Electrical And Electronics Engineering Sri Venkateshwara College of Engineering and Technology Chittoor Andhra Pradesh India Research Scholar Department of Instrumentation and Control Systems Engineering PSG College of Technology Coimbatore Tamil Nadu India

The advancement made in the field of information technology paves way for developing and utilization of software based technique in various field. The application of software related technique in the field of agriculture was at its peak nowadays. The key problems faced in agriculture are decrease in quality and yield of crops. This was caused due to various reasons such as environmental condition, insects, pest and diseases caused through microorganism. Among these various reasons the major fall in quality and yield of crop was achieved due to variety of disease. So, disease prediction at earlier stage in crops is considered as significant. Many methods were developed for prediction of disease in crop. But, effective prediction with better accuracy was not achieved in any of the developed method. Therefore for solving this issue the proposed system is developed. In the proposed method Whale Optimization Based Artificial Neural Network (WOANN) is used for prediction of different kinds of disease in tomato. Prior to classification of disease in tomato the process of colour image segmentation is carried out using FA in order to attain effective disease prediction ultimately. Further to evaluate the performance of the proposed system some statistical parameter such as accuracy, specificity, sensitivity, error rate, F1 score are calculated. And to prove that the proposed method functions effectively in disease prediction of tomato when compared to other conventional method such as Probabilistic Neural Network (PNN), K-Nearest Neighbour (K-NN) and Back Propagation Artificial Neural Network (BPANN) a comparison analysis is performed.

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Model predictive control of a CSTR: A comparative study among linear and nonlinear model approaches

Model predictive control of a CSTR: A comparative study amon...

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Indian control Conference (ICC)

作者： Ashok Krishnan Bhagyesh V. Patil P. S. V. Nataraj Jan Maciejowski K. V. Ling School of Electrical and Electronic Engineering Nanyang Technological University Singapore Cambridge Centre for Advanced Research in Energy Efficiency Singapore IDP in Systems and Control Engineering IIT Bombay Mumbai Department of Engineering University of Cambridge Cambridge United Kingdom

ISBN: (纸本)9781509017966

This paper presents a comparative study of two widely accepted model predictive control schemes based on mixed logical dynamical (MLD) and nonlinear modeling approaches with application to a continuous stirred tank reactor (CSTR) system. Specifically, we approximate the nonlinear behavior of a CSTR system with multiple local linear models in a MLD framework. The main benefit of such a scheme is the significant improvement in model accuracy when compared with a single linearized model. The benefits and trade-offs associated with predictive control laws synthesized using MLD and nonlinear modeling approaches are also compared.

关键词： Chemical reactors Predictive models Mathematical model Optimization Numerical models Adaptation models Nonlinear systems

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

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Classical and Quantum Gravity 2023年第8期40卷 085015-085015页

作者： H Abe T Akutsu M Ando A Araya N Aritomi H Asada Y Aso S Bae Y Bae R Bajpai K Cannon Z Cao E Capocasa M Chan C Chen D Chen K Chen Y Chen C-Y Chiang Y-K Chu S Eguchi M Eisenmann Y Enomoto R Flaminio H K Fong Y Fujii Y Fujikawa Y Fujimoto I Fukunaga D Gao G-G Ge S Ha I P W Hadiputrawan S Haino W-B Han K Hasegawa K Hattori H Hayakawa K Hayama Y Himemoto N Hirata C Hirose T-C Ho B-H Hsieh H-F Hsieh C Hsiung H-Y Huang P Huang Y-C Huang Y-J Huang D C Y Hui S Ide K Inayoshi Y Inoue K Ito Y Itoh C Jeon H-B Jin K Jung P Jung K Kaihotsu T Kajita M Kakizaki M Kamiizumi N Kanda T Kato K Kawaguchi C Kim J Kim J C Kim Y-M Kim N Kimura T Kiyota Y Kobayashi K Kohri K Kokeyama A K H Kong N Koyama C Kozakai J Kume Y Kuromiya S Kuroyanagi K Kwak E Lee H W Lee R Lee M Leonardi K L Li P Li L C -C Lin C-Y Lin E T Lin F-K Lin F-L Lin H L Lin G C Liu L-W Luo M Ma’arif E Majorana Y Michimura N Mio O Miyakawa K Miyo S Miyoki Y Mori S Morisaki N Morisue Y Moriwaki K Nagano K Nakamura H Nakano M Nakano Y Nakayama T Narikawa L Naticchioni L Nguyen Quynh W-T Ni T Nishimoto A Nishizawa S Nozaki Y Obayashi W Ogaki J J Oh K Oh M Ohashi T Ohashi M Ohkawa H Ohta Y Okutani K Oohara S Oshino S Otabe K-C Pan A Parisi J Park F E Pe na Arellano S Saha Y Saito K Sakai T Sawada Y Sekiguchi L Shao Y Shikano H Shimizu K Shimode H Shinkai T Shishido A Shoda K Somiya I Song R Sugimoto J Suresh T Suzuki H Tagoshi H Takahashi R Takahashi S Takano H Takeda M Takeda K Tanaka T Tanaka S Tanioka A Taruya T Tomaru T Tomura L Trozzo T Tsang J-S Tsao S Tsuchida T Tsutsui D Tuyenbayev N Uchikata T Uchiyama A Ueda T Uehara K Ueno G Ueshima T Ushiba M H P M van Putten J Wang T Washimi C Wu H Wu T Yamada K Yamamoto T Yamamoto K Yamashita R Yamazaki Y Yang S Yeh J Yokoyama T Yokozawa T Yoshioka H Yuzurihara S Zeidler M Zhan H Zhang Y Zhao Z-H Zhu The KAGRA Collaboration Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo 152-8551 Japan Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences Yuseong-gu Daejeon 34047 Republic of Korea School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Beijing 100875 People’s Republic of China Department of Applied Physics Fukuoka University Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy National Tsing Hua University Hsinchu 30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City 32001 Taiwan Department of Physics National Tsing Hua University Hsinchu 30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Univ. Grenoble Alpes Laboratoire d’Annecy de Physique des Particules (LAPP) Université Savoie M

During April 7–21 2020, KAGRA conducted its first scientific observation in conjunction with the GEO600 detector. The dominant noise sources during this run were found to be suspension control noise in the low-frequency range and acoustic noise in the mid-frequency range. In this study, we show that their contributions in the observational data can be reduced by a signal processing method called independent component analysis (ICA). The model of ICA is extended from that studied in the initial KAGRA data analysis to account for frequency dependence, while the linearity and stationarity of the coupling between the interferometer and the noise sources are still assumed. We identify optimal witness sensors in the application of ICA, leading to successful mitigation of these two dominant contributions. We also analyze the stability of the transfer functions for the entire two weeks of data to investigate the applicability of the proposed subtraction method in gravitational wave searches.

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Generating Patterns Using Multiple Targets

Generating Patterns Using Multiple Targets

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European control Conference

作者： Twinkle Tripathy Ankita Humne Arpita Sinha research scholar in Systems & Control Engineering Indian Institute of Technology Bombay India undergraduate student in Aerospace Engineering Indian Institute of Technology Bombay India Faculty of Systems & Control Engineering Indian Institute of Technology Bombay India

ISBN: (纸本)9781509025923

The paper focuses on generating patterns using a single autonomous agent modeled as a unicycle with constant forward speed. The patterns are generated on a plane around multiple points of interest. We call these points as target points. For practical purposes, the target points can represent any buildings of interest, landmarks, etc which need to be monitored continuously. Extending on our previous work on single target, this paper proposes a switching strategy for switching from one target point to another around which the agent traces different patterns. This renders multitudes of different patterns which, along with their aesthetic values, find applications in continuous monitoring, surveillance and so on. The theoretical results obtained in the paper have been validated through simulation results.

关键词： Generating Patterns Multiple Targets

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Practical SOSM controller Design for Short-Circuit Mode of Transfer in GMAW using Two Sliding Surfaces

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IFAC-PapersOnLine 2016年第1期49卷 724-729页

作者： Arun Kumar Paul Manas Kumar Bera B. Bandyopadhyay Electronics Devices (W/W) Pvt. Ltd 22 Mistry Indl. Estate Andheri (E) Mumbai - 93 India Research Scholar Systems and Control Engineering IIT Bombay - 400076 India Professor Systems and Control Engineering IIT Bombay Mumbai - 400076 India

GMAW is a complete arc welding process of creating all types of metal joints of desirable quality involving virtually all metals of any thickness in any position. However, in doing so, there is continuous shift in operating point of arc and/or in arc characteristics leading to wide range parametric variations and disturbances injected into the system. Moreover, the process involves multiple dynamical events such as in arc characteristics, melting rate, dynamics of arc length and droplet transfer mechanism etc. for creating eventual welding joints where each event suffers from non-linearity as well as parametric variations. control of such process optimally, though complex, but is essentially required as welding joints are made through indirect control of operating point of arc where for certain events feedback signals are difficult to get. Sliding mode control (SMC) concepts are considered as robust and have the ability to reject external disturbances and generate parametric insensitive response characteristics. This article, using already established control laws, explores the ability of SOSM in GMAW with robust performance characteristics. Implementation along with results of popular short-circuit mode of transfer is presented here.

关键词： Second order sliding mode (SOSM) gas metal arc welding (GMAW) short-circuit transfer

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Three Dimensional Impact Angle Constrained Guidance Law using Sliding Mode control

Three Dimensional Impact Angle Constrained Guidance Law usin...

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American control Conference

作者： Shashi Ranjan Kumar Debasish Ghose PhD research scholar in the Guidance Control and Decision Systems Laboratory Department of Aerospace Engineering at the Indian Institute of Science Bangalore Guidance Control and Decision Systems Laboratory Department of Aerospace Engineering at the Indian Institute of Science Bangalore

ISBN: (纸本)9781479932757

In this paper, three dimensional impact angle control guidance laws are proposed for stationary targets. Unlike the usual approach of decoupling the engagement dynamics into two mutually orthogonal 2-dimensional planes, the guidance laws are derived using the coupled dynamics. These guidance laws are designed using principles of conventional as well as nonsingular terminal sliding mode control theory. The guidance law based on nonsingular terminal sliding mode guarantees finite time convergence of interceptor to the desired impact angle. In order to derive the guidance laws, multi-dimension switching surfaces are used. The stability of the system, with selected switching surfaces, is demonstrated using Lyapunov stability theory. Numerical simulation results are presented to validate the proposed guidance law.

关键词： Three Dimensional Impact Constrained Guidance using Sliding Mode control Impact angle Variable structure systems Guidance switching surface System stability

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Robust Object Tracking Via Class Aware Partial Least Squares-gabor Wavelet Subspace

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Procedia engineering 2013年 64卷 159-168页

作者： K. Selvakumar Jovitha Jerome Research scholar Department of Instrumentation and Control Systems Engineering PSG College of Technology Coimbatore- 641004 Professor Department of Instrumentation and Control Systems Engineering PSG College of Technology Coimbatore- 641004

Effective tracking is still a big challenge due to lack of robust descriptors which captures discriminative features in non-controlled environment. We propose a novel descriptor based on Gabor wavelet and Partial Least Squares (PLS) discriminant analysis. Multi scale and multi orientation Gabor wavelets can extract selective local frequencies effectively in spatial and frequency domain. Due to the large dimension of feature vectors, dimensionality reduction is done using class aware PLS analysis. Unlike unsupervised Principal Component Analysis (PCA), PLS based subspace model learns target effectively by explicitly knowing the class labels of target and background region feature vectors. Tracking is done using particle filter and similarity between target and candidates is measured using low dimensional subspace model. To combat the target changes during tracking, novel static and dynamic target as well as background update strategy is used. Experimental results of various dataset demonstrate that the proposed tracker improves robustness and accuracy against representative trackers.

关键词： Object tracking Gabor wavelet Partial Least Squares Discriminant Analysis Particle filter

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LQR based Optimal Tuning of PID controller for Trajectory Tracking of Magnetic Levitation System

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Procedia engineering 2013年 64卷 254-264页

作者： E. Vinodh Kumar Jovitha Jerome Research Scholar Department of Instrumentation and Control Systems Engineering PSG College of Technology Coimbatore India-641004 Professor Department of Instrumentation and Control Systems Engineering PSG College of Technology Coimbatore India-641004

In this paper, we consider the stabilization and trajectory tracking of magnetic levitation system using PID controller whose controller gains are determined via Linear Quadratic Regulator (LQR) approach. Firstly, the nonlinear mathematical model of the system is obtained from the first principles. Then by applying Taylor's series, the non linear equation of motion is linearized around the equilibrium point to implement the stabilizing controller. Finally, the gains of the PID controller to achieve the desired response are determined using the LQR theory. Based on the natural frequency and damping ratio of the closed loop system, a new criterion for selecting the weighting matrices of LQR is proposed in this paper. Experiments are conducted on a Quanser magnetic levitation system to evaluate the performance of the proposed methodology and the experimental results prove that the proposed control strategy is effective not only in stabilizing the ball but also in rejecting the disturbance present in the system.

关键词： Trajectory tracking Magnetic levitation PID controller Linear Quadratic Regulator Weighting Matrices Feed forward control

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Robust LQR controller Design for Stabilizing and Trajectory Tracking of Inverted Pendulum

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Procedia engineering 2013年 64卷 169-178页

This paper describes the method for stabilizing and trajectory tracking of Self Erecting Single Inverted Pendulum (SESIP) using Linear Quadratic Regulator (LQR). A robust LQR is proposed in this paper not only to stabilize the pendulum in upright position but also to make the cart system to track the given reference signal even in the presence of disturbance. The control scheme of pendulum system consists of two controllers such as swing up controller and stabilizing controller. The main focus of this work is on the design of stabilizing controller which can accommodate the disturbance present in the system in the form of wind force. An optimal LQR controller with well tuned weighting matrices is implemented to stabilize the pendulum in the vertical position. The steady state and dynamic characteristics of the proposed controller are investigated by conducting experiments on benchmark linear inverted pendulum system. Experimental results prove that the proposed LQR controller can guarantee the inverted pendulum a faster and smoother stabilizing process with less oscillation and better robustness than a Full State Feedback (FSF) controller by pole placement approach.

关键词： Inverted Pendulum LQR controller PV controller Riccatti Equation Full State Feedback controller Pole placement approach

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Design And Analysis Of Model Predictive control Strategy For A Fractional-Order System

Design And Analysis Of Model Predictive Control Strategy For...

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第五届国际自动控制联合会分数阶导数及其应用会议

作者： Sharad P.Jadhav Dr.R.H.Chile Dr.S.T.Hamde Mukesh D.Patil Vishwesh A.Vyawahare Research Scholar Shri Guru Gobind Singhji Institute of Engineering andTechnologyNanded431606India ¤¤ Shri Guru Gobind Singhji Institute of Engineering andTechnology Nanded431606India Shri Guru Gobind Singhji Institute of Engineering andTechnology Nanded431606India IDP in Systems and Control Engg. Indian Institute of TechnologyBombay Mumbai India 400 076 IDP in Systems and Control Engg. Indian Institute of Technology Bombay Mumbai India 400 076

＜正＞Fractional calculus（FC）is an important mathematical tool and is becoming popular in diverse field of research *** is a generalization of the conventional calculus that leads to similar concepts and tools,but w... 详细信息

关键词： Fractional calculus Fractional-order systems Discrete approximations Model Predictive control. fractional order control strategy control Theory Instruction repertory Fractional calculus Model predictive control Predictive control approximation

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