Fast and optimal sensor scheduling for networked sensor systems

IEEE Trans. Automat. Contr.

Chen³

2011

117

In this technical note, we consider the problem of periodic sensor scheduling with limited resources. Two sensors are used to measure the state of a discrete-time linear process. We assume that each sensor has a maximum duty cycle and at most one sensor can communicate with a remote estimator at each time step due to the limited communication bandwidth. When a sensor is scheduled to send data, it sends the most recent measurement data to the estimator. Upon receiving the measurement data from the sensors, the estimator computes the optimal estimate of the state of the process. We first present a necessary condition for a periodic sensor schedule to be optimal. Based on this necessary condition, we construct an optimal periodic schedule that minimizes the estimation error at the estimator and at the same time satisfies the energy and communication bandwidth constraints. Examples are provided throughout the technical note to demonstrate the results developed.Index Terms-Networked control systems (NCSs).

mentioning

confidence: 67%

Optimal Periodic Sensor Scheduling With Limited Resources

IEEE Trans. Automat. Contr.

Chen³

2011

117

“…Using a time-periodic Kalman filter, they showed how to find an optimal schedule of the sensor communication. Similar work has been done by Arai et al [10], [11] where fast sensor scheduling was proposed for networked sensor systems. Savage and La Scala [12] considered the problem of optimal sensor scheduling for scalar systems that minimizes the terminal error.…”

Section: Introductionmentioning

confidence: 50%

Sensor data scheduling over a packet-dropping network

2010 8th World Congress on Intelligent Control and Automation

Chen

2010

In this paper, we consider sensor data scheduling over a packet-dropping network. A sensor having sufficient computation capability runs a local Kalman filter and needs to communicate its local state estimate to a remote estimator. However, the sensor has to decide at each time whether to send its local estimate data to the remote estimator or not due to its limited communication energy. We first provide a necessary condition for a sensor data scheduling scheme to be optimal. We then make use of this necessary condition to construct an optimal sensor data scheduling scheme that minimizes the estimation error at the remote estimator side and satisfies the energy constraint at the sensor side.

“…They considered two processes and one sensor and proposed schemes to determine which process the sensor needs to observe in order to minimize the total estimation error. Similar work has been done by Arai et al [4], [5] where fast sensor scheduling was proposed for networked sensor systems. Savage and La Scala [6] considered the problem of optimal sensor scheduling for scalar systems that minimizes the terminal error.…”

Section: Introductionmentioning

confidence: 54%

Sensor scheduling with limited communication energy and bandwidth

2010 11th International Conference on Control Automation Robotics &Amp; Vision

Chen

2010

In this paper, we consider the problem of sensor scheduling with limited resources. Two sensors are used to measure the state of a discrete-time linear process. We assume that each sensor has a maximum duty cycle and at most one sensor can communicate with a remote estimator at each time step due to the limited communication bandwidth. When a sensor is scheduled to send data, it sends the most recent measurement data to the estimator. Upon receiving the measurement data from the sensors, the estimator computes the optimal estimate of the state of the process. We first present a necessary condition for a sensor scheduling scheme to be optimal. Based on this necessary condition, we construct an optimal scheduling scheme that minimizes the estimation error at the estimator and at the same time satisfies the energy and communication bandwidth constraints. We also provide a sufficient condition on the minimum such that an optimal scheduling scheme can be constructed. Examples are provided throughout the paper to demonstrate the results developed.