Hao Xu

Assistant Professor
Hao Xu

Contact Information

Degrees

  • Ph.D., Electrical Engineering, Missouri University of Science and Technology, 2012
  • M.S., Electrical Engineering, Southeast University, China, 2009

Biography

Hao Xu was born in Nanjing, China in 1984. He received his Master's degree in Electrical Engineering from Southeast University in 2009, and his Ph.D. degree from the Missouri University of Science and Technology (formerly, the University of Missouri-Rolla), Rolla in 2012. From 2012 to 2014, he worked as a research associate at NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems. From 2014 to 2016, he was an assistant professor at Texas A&M University - Corpus Christi.

He started work at the University of Nevada, Reno in July 2016, where he currently holds an assistant professor position with the Department of Electrical and Biomedical Engineering.

Research interests

  • Intelligent control
  • Machine learning
  • Cyber-physical systems
  • Networked control systems
  • Unmanned aircraft systems (UAS)
  • Power control
  • Smart grid
  • Wireless passive sensor network

Associations and memberships

  • Associate Editorship, Transactions of the Institute of Measurement and Control
  • Advisory Board, IEEE Control Systems Society Intelligent Control Technical Committee
  • Advisory Board, IEEE Computational Intelligence Society ADPRL Technical Committee

Languages spoken

  • English
  • Chinese

Selected and recent publications

Book

  • S. Jagannathan and Hao Xu, "Optimal Network Control Systems," Taylor & Francis, CRC Press, 2016.

Journals

  • Hao Xu, S. Jagannathan, and F. L. Lewis, "Stochastic optimal control of unknown networked control systems in the presence of random delays and packet losses," Automatica, vol. 48, pp. 1017-1030, 2012.
  • Hao Xu, and S. Jagannathan, "Stochastic optimal controller design for uncertain nonlinear networked control system via neuro dynamic programming," IEEE Transactions on Neural Networks and Learning Systems, vol. 24, pp. 471-484, 2013.
  • Hao Xu, and S. Jagannathan, "Finite horizon adaptive optimal distributed power allocation for enhanced cognitive radio network in the presence of channel uncertainties," International Journal of Computer Networks and Communications, vol.1, pp. 1-19, 2013.
  • Hao Xu, S. Jagannathan, and F. L. Lewis, "Stochastic optimal output feedback designs for unknown linear discrete-time system zero-sum games under communication constraints," Asian Journal of Control, vol. 16, no. 5, pp. 1263-1276, 2014.
  • Hao Xu, and S. Jagannathan, "Neural network based finite horizon stochastic optimal control design for nonlinear networked control system," IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 3, pp. 472-485, 2015.
  • Hao Xu, A. Sahoo, and S. Jagannathan, "Stochastic adaptive event-triggered control and network scheduling protocol co-design for distributed network systems," IET Control Theory and Applications, vol. 8, no. 18, pp. 2253-2265, 2014.
  • Hao Xu, Q. Zhao, and S. Jagannathan, "Optimal regulation of uncertain dynamic systems by using adaptive dynamic programming," Journal of Control and Decision, vol. 1, no. 3, pp. 226-256, 2014.
  • Hao Xu, Q. Zhao, and S. Jagannathan, "Finite-horizon near optimal output feedback neural network control of quantized nonlinear discrete-time systems with input constraint," IEEE Transactions on Neural Networks and Learning Systems, in press, 2015.
  • Hao Xu, "Finite horizon near optimal design of nonlinear two-player zero-sum game in presence of completely unknown dynamics," Journal of Control, Automation and Electrical Systems, vol. 26, no. 4, pp. 361-370, 2015.
  • Q. Zhao, Hao Xu, and S. Jagannathan, "Near optimal output feedback control of nonlinear discrete-time systems based on reinforcement neural network learning," Acta Automatica Sinica, vol. 1, no. 4, pp. 372-384, 2014.
  • Q. Zhao, Hao Xu, and S. Jagannathan, "Finite horizon adaptive optimal control of linear discrete-time systems in input-output form using learning methodology," Journal of Artificial Intelligence and Soft Computing Research, vol. 3, no. 3, pp. 175-187, 2013.
  • Q. Zhao, Hao Xu, and S. Jagannathan, "Optimal control of uncertain quantized linear discrete-time system," International Journal of Adaptive Control and Signal Processing, vol. 29, no. 3, pp. 325-345, 2015.
  • Q. Zhao, Hao Xu, and S. Jagannathan, "Neural network-based finite horizon optimal control of uncertain affine nonlinear discrete-time systems," IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 3, pp. 486-499, 2015.