http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:11261 We study a predictive control formulation for discrete-time non-linear plant models where controller output data is transmitted over an unreliable communication channel. The channel is affected by random data-loss and does not provide acknowledgments of receipt. To achieve robustness with respect to dropouts, at every sampling instant the controller transmits packets of data. These contain possible control inputs for a finite number of future time instants, and minimize a finite horizon cost function. At the plant actuator side, received packets are buffered, providing the plant inputs. Within this context, we adopt a stochastic Lyapunov function approach to establish stability results of this networked control system. 2013-03-24T05:11:26.291Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:11259 In this paper, we study the stability of a networked control system involving signal quantization with finitely many levels and a bounded number of consecutive packet-dropouts. To compensate for the effect of packet-dropouts, the controller-encoder sends a packet which contains possible quantized control inputs for finite future steps. At the receiving end, i.e., at the plant actuator side, a buffer decides the actuator input based on the received data. The buffer has memory which is overwritten whenever it receives a packet from the controller. Within this setting, we derive a sufficient condition on quantization parameters for achieving small ℓ^∞ signal ℓ^∞ stability of the feedback system. The stability condition is characterized in terms of the number of quantization levels of the quantizer. 2013-03-24T05:09:52.295Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9214 We study stochastic stability for Kalman filtering over fading wireless channels where variable channel gains are counteracted by the use of power control to alleviate the effects of packet drops. The Kalman filter and the controller are located at a single gateway which acquires data from the wireless sensors. We establish sufficient conditions which ensure that the Kalman filter covariance matrix is exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing optimal power allocation laws which minimize the total sensor power budget. In deriving the optimal power allocation laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases. 2013-03-24T04:54:08.185Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9216 Stochastic stability for centralized Kalman filtering over a wireless sensor network with correlated fading channels is studied. On their route to the gateway, sensor packets, possibly aggregated with measurements from several nodes, may be dropped because of fading links. By assuming the network states to be Markovian, we establish sufficient conditions that ensure the Kalman filter to be exponentially bounded in norm. In the one sensor case, this new stability condition is shown to include previous results obtained in the literature as special cases. The results also hold when applying power control, where the transmission power of each node is a nonlinear mapping of the network state and the channel gains. 2013-03-24T04:53:44.284Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:7868 This paper is concerned with the stability analysis of a networked control system, wherein communication from the controller to the plant input is through a digital channel subject to packet-dropouts and finite-level quantization. No acknowledgments of receipt are available to the controller. To alleviate the effect of packet-dropouts, the controller transmits tentative plant input sequences. Within this setup, we derive a sufficient condition for small ℓ∞ signal ℓ∞ stability of the networked control system. This condition requires the maximum number of consecutive packet-dropouts to be bounded. We also elucidate the trade-off which exists between the disturbance attenuation and the step size of the quantizer and the maximum number of consecutive packet-dropouts. 2013-03-07T23:41:00.072Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:11650 We study a predictive control formulation for uncertain discrete-time non-linear uniformly continuous plant models where controller output data is transmitted over an unreliable communication channel. The channel introduces Markovian data-loss and does not provide acknowledgments of receipt. To achieve robustness with respect to dropouts, at every sampling instant the controller transmits packets of data. These contain possible control inputs for a finite number of future time instants, and minimize a finite horizon cost function. At the actuator side, received packets are buffered, providing the plant inputs. Within this context, we adopt a stochastic Lyapunov function approach to establish stability results of the networked control system. A distinguishing aspect of this work is that it considers situations where the maximum number of consecutive packet dropouts has unbounded support. 2013-03-07T23:39:58.884Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:11732 We study stochastic stability of centralized Kalmanfiltering for linear time-varying systems equipped with wireless sensors. Transmission is over fading channels where variable channel gains are counteracted by power control to alleviate the effects of packet drops. We establish sufficient conditions for the expected value of the Kalman filter covariance matrix to be exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing power control policies which minimize the total sensor power budget. In deriving the optimal power control laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases. 2013-03-07T23:39:08.085Z ]]>