Citation
Konstantinos Gatsis, Alejandro Ribeiro, George Pappas. "Optimal Power Management in Wireless Control Systems". IEEE Transactions on Automatic Control, pp. 1495-1510, June 2014.

Abstract
This paper considers the control of a linear plant when plant state information is being transmitted from a sensor to the controller over a wireless fading channel. The power allocated to these transmissions determines the probability of successful packet reception and is allowed to adapt online to both channel conditions and plant state. The goal is to design plant input and transmit power policies that minimize an infinite horizon cost combining power expenses and the conventional linear quadratic regulator control cost. Since plant inputs and transmit powers are in general coupled, a restricted information structure is imposed allowing them to be designed separately. Under this information structure the standard LQR controller becomes the optimal plant input policy, while the optimal com- munication policy follows a Markov decision process minimizing transmit power at the sensor and state estimation error at the controller. The optimal power adaptation to channel and plant states is examined qualitatively for general forward error correcting codes. In the particular case of capacity achieving codes event-triggered policies are recovered, where the sensor decides whether to transmit or not based on plant and channel conditions. Approximate dynamic programming is employed to derive a family of tractable suboptimal communication policies exhibiting the same qualitative features as the optimal one. The performance of our suboptimal policies is shown in simulations and is contrasted to other simple transmission policies.

Electronic downloads

• http://www.src.org/library/publication/p069199/. (Link to paper on SRC website)
• http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6740858

• HTML

  Konstantinos Gatsis, Alejandro Ribeiro, George Pappas. <a
  href="http://www.terraswarm.org/pubs/242.html"
  >Optimal Power Management in Wireless Control
  Systems</a>, <i>IEEE Transactions on Automatic
  Control</i>, pp. 1495-1510, June 2014.

• Plain text

  Konstantinos Gatsis, Alejandro Ribeiro, George Pappas.
  "Optimal Power Management in Wireless Control
  Systems". <i>IEEE Transactions on Automatic
  Control</i>, pp. 1495-1510, June 2014.

• BibTeX

  @article{GatsisRibeiroPappas14_OptimalPowerManagementInWirelessControlSystems,
      author = {Konstantinos Gatsis and Alejandro Ribeiro and
                George Pappas},
      title = {Optimal Power Management in Wireless Control
                Systems},
      journal = {IEEE Transactions on Automatic Control},
      pages = {1495-1510},
      month = {June},
      year = {2014},
      abstract = {This paper considers the control of a linear plant
                when plant state information is being transmitted
                from a sensor to the controller over a wireless
                fading channel. The power allocated to these
                transmissions determines the probability of
                successful packet reception and is allowed to
                adapt online to both channel conditions and plant
                state. The goal is to design plant input and
                transmit power policies that minimize an infinite
                horizon cost combining power expenses and the
                conventional linear quadratic regulator control
                cost. Since plant inputs and transmit powers are
                in general coupled, a restricted information
                structure is imposed allowing them to be designed
                separately. Under this information structure the
                standard LQR controller becomes the optimal plant
                input policy, while the optimal com- munication
                policy follows a Markov decision process
                minimizing transmit power at the sensor and state
                estimation error at the controller. The optimal
                power adaptation to channel and plant states is
                examined qualitatively for general forward error
                correcting codes. In the particular case of
                capacity achieving codes event-triggered policies
                are recovered, where the sensor decides whether to
                transmit or not based on plant and channel
                conditions. Approximate dynamic programming is
                employed to derive a family of tractable
                suboptimal communication policies exhibiting the
                same qualitative features as the optimal one. The
                performance of our suboptimal policies is shown in
                simulations and is contrasted to other simple
                transmission policies.},
      URL = {http://terraswarm.org/pubs/242.html}
  }
  

Posted by Barb Hoversten on 18 Jan 2014.