Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2014, Article ID 267307, 9 pages
http://dx.doi.org/10.1155/2014/267307
Research Article

Neural Network Observer-Based Finite-Time Formation Control of Mobile Robots

1School of Electrical Engineering, Guangdong Mechanical and Electrical College, Guangzhou 510550, China
2Key Laboratory of Autonomous Systems and Networked Control, Ministry of Education, South China University of Technology, Guangzhou 510640, China
3School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
4School of Biomedical Engineering, National University of Singapore, Singapore 117575

Received 22 March 2014; Accepted 18 June 2014; Published 7 July 2014

Academic Editor: Simin Yu

Copyright © 2014 Caihong Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [10 citations]

The following is the list of published articles that have cited the current article.

  • B.K. Swathi Prasad, Aditya G. Manjunath, and Hariharan Ramasangu, “Multi-agent trajectory control under faulty leader: Energy-level based leader election under constant velocity,” 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 2151–2156, . View at Publisher · View at Google Scholar
  • B.K. Swathi Prasad, and Hariharan Ramasangu, “Goal-based multi-agent tree formation using reinforcement learning,” 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 2180–2184, . View at Publisher · View at Google Scholar
  • B.K. Swathi Prasad, Aditya G. Manjunath, and Hariharan Ramasangu, “Flocking trajectory control under faulty leader: Energy-level based election of leader,” 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), pp. 1–6, . View at Publisher · View at Google Scholar
  • Yongping Pan, Tairen Sun, and Haoyong Yu, “Peaking-Free Output-Feedback Adaptive Neural Control Under a Nonseparation Principle,” Ieee Transactions On Neural Networks And Learning Systems, vol. 26, no. 12, pp. 3097–3108, 2015. View at Publisher · View at Google Scholar
  • Alessandro Freddi, Sauro Longhi, and Andrea Monteriu, “Nonlinear Decentralized Model Predictive Control for Unmanned Vehicles Moving in Formation,” Information Technology And Control, vol. 44, no. 1, pp. 89–97, 2015. View at Publisher · View at Google Scholar
  • Vikas Panwar, “Wavelet neural network-based H∞ trajectory tracking for robot manipulators using fast terminal sliding mode control,” Robotica, vol. 35, no. 7, pp. 1488–1503, 2016. View at Publisher · View at Google Scholar
  • Shuaiby Mohamed, Tobias Rainer Schäfle, and Naoki Uchiyama, “Robust control of a redundant wheeled drive system for energy saving and fail safe motion,” Advances in Mechanical Engineering, vol. 9, no. 5, 2017. View at Publisher · View at Google Scholar
  • Dandan Wang, Xiuyun Zhang, Xinyi Zhao, Shikai Shao, Qun Zong, and Bailing Tian, “Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters,” ISA Transactions, vol. 73, pp. 22–30, 2018. View at Publisher · View at Google Scholar
  • M. Hassan, E. Aljuwaiser, and R. Badr, “A new on-line observer-based controller for leader-follower formation of multiple nonholonomic mobile robots,” Journal of the Franklin Institute, 2018. View at Publisher · View at Google Scholar
  • Behrooz Rezaie, Zahra Rahmani, and Hossein Ghasemi, “Terminal sliding mode control with evolutionary algorithms for finite-time robust tracking of nonholonomic systems,” Information Technology and Control, vol. 47, no. 1, pp. 26–44, 2018. View at Publisher · View at Google Scholar