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D-Index & Metrics

Electronics and Electrical Engineering

D-Index
62
Citations
13315
World Ranking
1464
National Ranking
603

Overview

Sarangapani Jagannathan is affiliated with the Missouri University of Science and Technology in the United States. Their research primarily lies within the fields of Computer Science and Engineering, with significant contributions in specialized areas such as Control and Systems Engineering, Artificial Intelligence, and Computational Theory and Mathematics.

Their work covers a range of main topics including:

  • Adaptive Dynamic Programming Control
  • Adaptive Control of Nonlinear Systems
  • Reinforcement Learning in Robotics
  • Distributed Control Multi-Agent Systems
  • Advanced Control Systems Optimization
  • Fault Detection and Control Systems
  • Advanced Neural Network Applications

The scientist has contributed extensively to various publication venues, with a substantial number of papers appearing in:

  • IEEE Transactions on Systems Man and Cybernetics Systems
  • IEEE Transactions on Neural Networks and Learning Systems
  • International Journal of Adaptive Control and Signal Processing
  • IEEE Transactions on Automation Science and Engineering
  • IEEE Transactions on Cybernetics

Frequent collaborators include Enrique Herrera-Viedma, Eddie Tunstel, Andreas Nuernberger, Fei-Yue Wang, and Karen Panetta.

Recent papers authored by or involving Sarangapani Jagannathan cover topics from model compression to control systems and adaptive learning:

  • "A comprehensive survey on model compression and acceleration," 2020, Artificial Intelligence Review
  • "Event-Driven Off-Policy Reinforcement Learning for Control of Interconnected Systems," 2020, IEEE Transactions on Cybernetics
  • "A transfer learning with structured filter pruning approach for improved breast cancer classification on point-of-care devices," 2021, Computers in Biology and Medicine
  • "Dual-Loop Optimal Control of a Robot Manipulator and Its Application in Warehouse Automation," 2020, IEEE Transactions on Automation Science and Engineering
  • "Optimal Adaptive Control of Uncertain Nonlinear Continuous-Time Systems With Input and State Delays," 2021, IEEE Transactions on Neural Networks and Learning Systems

In addition to journal papers, Sarangapani Jagannathan has published multiple books under Springer Science+Business Media, including several editions titled "Advanced Computing" from 2021 and 2022.

Best Publications

  • Output Feedback Control of a Quadrotor UAV Using Neural Networks

    T. Dierks;S. Jagannathan

  • Neural Network Control of Nonlinear Discrete-Time Systems

    Jagannathan Sarangapani

  • Neural Network-Based Event-Triggered State Feedback Control of Nonlinear Continuous-Time Systems

    Avimanyu Sahoo;Hao Xu;Sarangapani Jagannathan

  • Online Optimal Control of Affine Nonlinear Discrete-Time Systems With Unknown Internal Dynamics by Using Time-Based Policy Update

    T. Dierks;S. Jagannathan

  • Reinforcement Learning Neural-Network-Based Controller for Nonlinear Discrete-Time Systems With Input Constraints

    Pingan He;S. Jagannathan

  • Neural Network Control of Robot Arms and Nonlinear Systems

    F.L. Lewis;S. Jagannathan;A. Yeşildirek

  • Stochastic optimal control of unknown linear networked control system in the presence of random delays and packet losses

    Hao Xu;S. Jagannathan;F. L. Lewis

  • 2009 Special Issue: Optimal control of unknown affine nonlinear discrete-time systems using offline-trained neural networks with proof of convergence

    Travis Dierks;Balaje T. Thumati;S. Jagannathan

  • Optimal control of affine nonlinear continuous-time systems

    T. Dierks;S. Jagannathan

  • Multilayer discrete-time neural-net controller with guaranteed performance

    S. Jagannathan;F.L. Lewis

  • Generalized Hamilton–Jacobi–Bellman Formulation -Based Neural Network Control of Affine Nonlinear Discrete-Time Systems

    Zheng Chen;S. Jagannathan

  • Reinforcement Learning Controller Design for Affine Nonlinear Discrete-Time Systems using Online Approximators

    Qinmin Yang;S. Jagannathan

  • Optimal control of unknown affine nonlinear discrete-time systems using offline-trained neural networks with proof of convergence

    Travis Dierks;Balaje T. Thumati;S. Jagannathan

  • Identification of nonlinear dynamical systems using multilayered neural networks

    S. Jagannathan;F. L. Lewis

  • Optimal Control of Nonlinear Continuous-Time Systems in Strict-Feedback Form

    Hassan Zargarzadeh;Travis Dierks;Sarangapani Jagannathan

  • Smart farming system using sensors for agricultural task automation

    Chetan Dwarkani M;Ganesh Ram R;Jagannathan S;R. Priyatharshini

  • Neural Network-Based Optimal Adaptive Output Feedback Control of a Helicopter UAV

    D. Nodland;H. Zargarzadeh;S. Jagannathan

  • Neural Network Control of Mobile Robot Formations Using RISE Feedback

    T. Dierks;S. Jagannathan

  • Predictive Congestion Control Protocol for Wireless Sensor Networks

    M. Zawodniok;S. Jagannathan

  • Discrete-time neural net controller for a class of nonlinear dynamical systems

    S. Jagannathan;F.L. Lewis

Frequent Co-Authors

Frank L. Lewis
Frank L. Lewis The University of Texas at Arlington
Mariesa L. Crow
Mariesa L. Crow Missouri University of Science and Technology
Yilu Liu
Yilu Liu University of Tennessee at Knoxville
Keith Corzine
Keith Corzine University of California, Santa Cruz
David Pommerenke
David Pommerenke Graz University of Technology
S. N. Balakrishnan
S. N. Balakrishnan Missouri University of Science and Technology
Robert Babuska
Robert Babuska Delft University of Technology

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