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Author = Braslavsky, J.H.;
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Displaying Results 1  6 of 6 on page 1 of 1
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Channel SignaltoNoise Ratio Constrained Feedback Control: Performance and Robustness
(2009)
Rojas, A.J.; Braslavsky, J.H.; Middleton, R.H.
Channel SignaltoNoise Ratio Constrained Feedback Control: Performance and Robustness
(2009)
Rojas, A.J.; Braslavsky, J.H.; Middleton, R.H.
Abstract:
The limitations in performance and robustness imposed by explicitly considering a communication channel in a control loop have received increased attention in recent years. Previous results in the literature have stated these limitations in terms of a minimal transmission data rate necessary for stabilisation. In this paper a signaltonoise ratio (SNR) approach is used to study two specific cases: (i) performance in terms of model matching and (ii) robustness against a multiplicative uncertainty in the plant model. The analysis performed leads to closedform expressions that allow the quantification of the extra SNR required in both cases.
http://mural.maynoothuniversity.ie/1880/
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Fundamental Limitations in Control over a Communication Channel
(2008)
Rojas, A.J.; Braslavsky, J.H.; Middleton, R.H.
Fundamental Limitations in Control over a Communication Channel
(2008)
Rojas, A.J.; Braslavsky, J.H.; Middleton, R.H.
Abstract:
Fundamental limitations in feedback control is a well established area of research. In recent years it has been extended to the study of limitations imposed by the consideration of a communication channel in the control loop. Previous results characterised these limitations in terms of a minimal data transmission rate necessary for stabilisation. In this paper a signaltonoise ratio (SNR) approach is used to obtain a tight condition for the linear time invariant output feedback stabilisation of a continuoustime, unstable, non minimum phase (NMP) plant with timedelay over an additive Gaussian coloured noise communication channel. By working on a linear setting the infimal SNR for stabilisability is defined as the infimal achievable H2 norm between the channel noise input and the channel signal input. The result gives a guideline in estimating the severity of the fundamental SNR limitation imposed by the plant unstable poles, NMP zeros, timedelay as well as the channel NMP zeros, ...
http://mural.maynoothuniversity.ie/3522/
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Input Disturbance Rejection in Channel SignaltoNoise Ratio Constrained Feedback Control
(2008)
Rojas, A.J.; Middleton, R.H.; Freudenberg, J.S.; Braslavsky, J.H.
Input Disturbance Rejection in Channel SignaltoNoise Ratio Constrained Feedback Control
(2008)
Rojas, A.J.; Middleton, R.H.; Freudenberg, J.S.; Braslavsky, J.H.
Abstract:
Communication channels impose a number of obstacles to feedback control. One recent line of work considers the problem of feedback stabilisation subject to a constraint on the channel signaltonoise ratio (SNR). It has been shown for continuoustime systems that the optimal control problem of achieving the infimal SNR can be formulated as a linear quadratic Gaussian (LQG) control problem with weights chosen as in the loop transfer recovery (LTR) technique. The present paper extends this formulation to: discretetime systems; communications over channels with memory; and input disturbance rejection. By using this formulation, we derive exact expressions for the linear time invariant (LTI) controller that achieves the infimal SNR under the effect of timedelay and additive coloured noise. We then quantify the infimal SNR required for both stabilisation and input disturbance rejection for a relative degree one, minimum phase plant and a memoryless Gaussian channel.
http://mural.maynoothuniversity.ie/2245/
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Minimum Variance Control over a Gaussian Communication Channel
(2008)
Freudenberg, J.S.; Middleton, R.H.; Braslavsky, J.H.
Minimum Variance Control over a Gaussian Communication Channel
(2008)
Freudenberg, J.S.; Middleton, R.H.; Braslavsky, J.H.
Abstract:
We consider the problem of minimizing the response of a plant output to a stochastic disturbance using a control law that relies on the output of a noisy communication channel. We discuss a lower bound on the performance achievable at a specified terminal time using nonlinear timevarying communication and control strategies, and show that this bound may be achieved using strategies that are linear.
http://mural.maynoothuniversity.ie/2244/
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Optimal Signal to Noise Ratio in Feedback over Communication Channels with Memory
(2006)
Rojas, A.J.; Freudenberg, J.S.; Braslavsky, J.H.; Middleton, R.H.
Optimal Signal to Noise Ratio in Feedback over Communication Channels with Memory
(2006)
Rojas, A.J.; Freudenberg, J.S.; Braslavsky, J.H.; Middleton, R.H.
Abstract:
Communication channels impose a number of obstacles to feedback control, such as delay, noise, and constraints in communication datarate. One alternate line of recent work considers the problem of feedback stabilization subject to a constraint in the signaltonoise ratio (SNR). It has been shown for continuoustime systems that the optimal control problem arising in achieving minimal SNR can be formulated as a linear quadratic Gaussian (LQG) control problem with weights chosen as in the loop transfer recovery (LTR) technique. The present paper extends such LQG/LTR formulation to discretetime systems with feedback over channels with memory. By using such formulation, we derive exact expressions for the LTI controller and loop sensitivity functions that achieve minimal SNR under the effect of timedelay, non minimum phase zeros and colored additive noise. For the minimumphase case with white noise and no time delay, we show that the optimal feedback loop obtained after applying LTR...
http://mural.maynoothuniversity.ie/1789/
Marked
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Stabilization with Disturbance Attenuation over a Gaussian Channel
(2007)
Freudenberg, J.S.; Middleton, R.H.; Braslavsky, J.H.
Stabilization with Disturbance Attenuation over a Gaussian Channel
(2007)
Freudenberg, J.S.; Middleton, R.H.; Braslavsky, J.H.
Abstract:
We propose a linear control and communication scheme for the purposes of stabilization and disturbance attenuation when a discrete Gaussian channel is present in the feedback loop. Specifically, the channel input is amplified by a constant gain before transmission and the channel output is processed through a linear time invariant filter to produce the control signal. We show how the gain and filter may be chosen to minimize the variance of the plant output. For an order one plant, our scheme achieves the theoretical minimum taken over a much broader class of compensators.
http://mural.maynoothuniversity.ie/1722/
Displaying Results 1  6 of 6 on page 1 of 1
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