Engineering Experts

Jagannathan Sarangapani

Missouri University of Science and Technology
United States of America


"Jagannathan Sarangapani is at the Missouri University of Science and Technology, Rolla, MO, USA, where he is a Rutledge-Emerson Distinguished Professor and Site Director for the NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems. He also has a courtesy appointment with the Department of Computer Science. He has co-authored around 138 peer-reviewed journal articles, over 245 refereed IEEE conference articles, several book chapters, and co-authored four books and two edited books. He is awarded with 19 patents, one defense publication, with several pending. He has supervised the completion of 20 doctoral students and 30 M.S. students. His research funding is in excess of $16 million dollars from NSF, NASA, AFRL, Sandia and from other companies. His current research interests include adaptive and neural network control, networked control systems/cyber physical systems, prognostics, and autonomous systems/robotics. He served on various editorial boards and as a co-editor for the IET Book series on Control. Education Doctor of Philosophy in Electrical Engineering (1/92-8/94) Automation and Robotics Research Institute, University of Texas at Arlington Specialization: Nonlinear Adaptive Neural Network Control Master of Science (9/87-12/89); University of Saskatchewan at Saskatoon, Canada Specialization: Embedded Control Systems and Robotics Bachelor of Electrical Engineering (7/82-8/86); Anna University at Madras, India "

Research Interest

" Systems and control Neural network control Event triggered control/cyber-physical systems Resilience/prognostics Autonomous systems/robotics "


  • Qiming Zhao, Hao Xu, and S. Jagannathan, “Finite-horizon near optimal adaptive control of uncertain linear discrete-time systems”, Optimal Control, Applications, and Methods, vol. 36, no. 6, pp. 853-872, November/December 2015.

  • Q. Yang, S. Jagannathan and Y. Sun, “Robust integral of neural network and error sign control of MIMO nonlinear systems”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 12, pp. 3278-3286, 2015, December 2015.

  • H. Zargarzadeh, T. Dierks, and S. Jagannathan, “Optimal control of nonlinear continuous-time systems in strict-feedback form”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 10, pp. 2535-2549, October 2015.

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