Abstract
We consider a networked control loop in which the sensors acquire partial state information and communicate to a remote controller through a lossy communication network. A scheduler, collocated with the sensors, decides to transmit a locally estimated state to the controller based on an event-triggered transmission policy with stochastic thresholds. Assuming that the local estimator either senses the communication channel or receives an ideal acknowledgment from the remote estimator, then the optimal control law can be shown to be a linear function of the conditional expectation of the state. However, the probability distribution of the state conditioned on the information available to the controller based on the mentioned transmission policy and network is not Gaussian, but rather described by a sum of Gaussians with an increasing number of terms at every time-step. We show that the optimal LQG control law can be determined without tracking this probability distribution for finding its expected value. Moreover, we establish that the stochastic event-triggered scheduler can be appropriately regulated in order to achieve a desired triggering probability at every time-step.
| Original language | English |
|---|---|
| Pages (from-to) | 58-63 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 51 |
| Issue number | 23 |
| DOIs | |
| Publication status | Published - 17 Dec 2018 |
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Keywords
- Lossy communication network
- Optimal LQG controller
- Stochastic event-triggered scheduler
- Triggering rate
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An optimal LQG controller for stochastic event-triggered scheduling over a lossy communication network. / Balaghi I., M. Hadi; Antunes, Duarte J.; Mamduhi, Mohammad H.; Hirche, Sandra.
In: IFAC-PapersOnLine, Vol. 51, No. 23, 17.12.2018, p. 58-63.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - An optimal LQG controller for stochastic event-triggered scheduling over a lossy communication network
AU - Balaghi I., M. Hadi
AU - Antunes, Duarte J.
AU - Mamduhi, Mohammad H.
AU - Hirche, Sandra
PY - 2018/12/17
Y1 - 2018/12/17
N2 - We consider a networked control loop in which the sensors acquire partial state information and communicate to a remote controller through a lossy communication network. A scheduler, collocated with the sensors, decides to transmit a locally estimated state to the controller based on an event-triggered transmission policy with stochastic thresholds. Assuming that the local estimator either senses the communication channel or receives an ideal acknowledgment from the remote estimator, then the optimal control law can be shown to be a linear function of the conditional expectation of the state. However, the probability distribution of the state conditioned on the information available to the controller based on the mentioned transmission policy and network is not Gaussian, but rather described by a sum of Gaussians with an increasing number of terms at every time-step. We show that the optimal LQG control law can be determined without tracking this probability distribution for finding its expected value. Moreover, we establish that the stochastic event-triggered scheduler can be appropriately regulated in order to achieve a desired triggering probability at every time-step.
AB - We consider a networked control loop in which the sensors acquire partial state information and communicate to a remote controller through a lossy communication network. A scheduler, collocated with the sensors, decides to transmit a locally estimated state to the controller based on an event-triggered transmission policy with stochastic thresholds. Assuming that the local estimator either senses the communication channel or receives an ideal acknowledgment from the remote estimator, then the optimal control law can be shown to be a linear function of the conditional expectation of the state. However, the probability distribution of the state conditioned on the information available to the controller based on the mentioned transmission policy and network is not Gaussian, but rather described by a sum of Gaussians with an increasing number of terms at every time-step. We show that the optimal LQG control law can be determined without tracking this probability distribution for finding its expected value. Moreover, we establish that the stochastic event-triggered scheduler can be appropriately regulated in order to achieve a desired triggering probability at every time-step.
KW - Lossy communication network
KW - Optimal LQG controller
KW - Stochastic event-triggered scheduler
KW - Triggering rate
UR - http://www.scopus.com/inward/record.url?scp=85058474287&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2018.12.011
DO - 10.1016/j.ifacol.2018.12.011
M3 - Article
AN - SCOPUS:85058474287
VL - 51
SP - 58
EP - 63
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8963
IS - 23
ER -