• DocumentCode
    2381656
  • Title

    Energy optimal control in mobile sensor networks using hybrid systems theory

  • Author

    Yu, Shengwei ; Lee, C. S George ; Hu, Jianghai

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
  • fYear
    2011
  • fDate
    9-12 Oct. 2011
  • Firstpage
    1975
  • Lastpage
    1980
  • Abstract
    This paper studies optimal control in a sensor network system consisting of mobile robots to minimize the overall energy consumption of the whole network. With communication energy cost and mobility energy cost taken into consideration, the problem is formulated as an optimal control of a hybrid system, which is solved by switched Linear Quadratic Regulator (LQR). Though switched LQR obtains globally optimal solution, the computational complexity is too high to implement the algorithm when the control horizon expands. For this reason, we resort to a switched system version of Receding Horizon Control (RHC), which is stable and provides a solution close to the optimal one. Finally, in order to attenuate the complexity due to the large networked system, the centralized RHC is modified into a distributed algorithm, which converges to a solution that can approximate the optimizer quite well as verified by simulations.
  • Keywords
    approximation theory; computational complexity; distributed control; energy consumption; linear quadratic control; mobile robots; networked control systems; optimal control; optimisation; wireless sensor networks; centralized RHC; communication energy cost; computational complexity; distributed algorithm; energy consumption; energy optimal control; hybrid system theory; large networked system; mobile robot; mobile sensor network; mobility energy cost; receding horizon control; switched LQR; switched linear quadratic regulator; switched system; Cost function; Distributed algorithms; Mobile communication; Optimal control; Relays; Robot sensing systems; Switches; Mobile ad hoc network; distributed algorithm; energy optimization; hybrid control systems; optimal control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4577-0652-3
  • Type

    conf

  • DOI
    10.1109/ICSMC.2011.6083961
  • Filename
    6083961