Control of LTI plants over erasure channels

Silva, Eduardo I.; Pulgar, Sebastián A.

doi:10.1016/j.automatica.2011.02.050

Cited by 35 publications

(30 citation statements)

References 21 publications

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“…In that situation, choosing the scaling factors amounts to choosing the equivalent channel noise variance. We also note that the above SNR constrained channel appears naturally when studying networked systems closed over either erasure or digital channels [22], [24].…”

Section: Setup and Problem Definitionmentioning

confidence: 94%

“…This framework is relevant for two reasons: First, it allows one to use well-known LTI synthesis and analysis tools to gain insight into networked control problems. Second, conclusions derived for SNR constrained NCSs can be translated into conclusions valid in more interesting scenarios, including control subject to average data-rate constraints or data-dropouts [22], [24], [25].…”

Section: Introductionmentioning

confidence: 99%

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Performance limitations for SISO LTI plants controlled over SNR constrained channels

Silva

Pulgar

2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

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This paper presents performance limitations in the control of single-input single-output (SISO) linear timeinvariant (LTI) plants over signal-to-noise ratio (SNR) constrained channels. Our main result is a closed form characterization of the minimal stationary plant output variance when the controller has access to plant output measurements and the channel is placed between the controller and the actuator. We explicitly quantify the effects of plant dynamical features, namely unstable poles, non-minimum phase zeros, and frequency response, as well as the effects of channel feedback, on the best achievable performance. Our results shed light into the interplay between optimal performance and SNR constraints.

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Section: Setup and Problem Definitionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Performance limitations for SISO LTI plants controlled over SNR constrained channels

Silva

Pulgar

2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

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“…Consistent with the motivation above, we consider a situation where the sensor sends the measurements y over an analog erasure channel (see e.g., [3], [4]) without preprocessing. The channel output, say y θ , is thus given by…”

Section: Setup and Problem Definitionmentioning

confidence: 99%

“…Our main result is an explicit expression for the jointly optimal dropout compensator and state estimator designs, that minimize the stationary state estimation error variance. For doing so, we exploit the results in [3] to show that the considered optimal design problem is equivalent to an auxiliary optimal quadratic control problem subject to an SNR constraint. In a second step, we solve the auxiliary problem by using standard optimal control and estimation theories [23], [29].…”

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confidence: 99%

An approach to stationary state estimation with missing data

Silva

Solís

2011

2011 9th IEEE International Conference on Control and Automation (ICCA)

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This paper deals with state estimation in networked scenarios. We focus on a situation where the output of an LTI system is measured over an erasure channel and design a class of switched state estimators. In the considered class, the estimators use the channel output and instantaneous information on the channel state, to construct both a state estimate and, when data dropouts occur, an estimate of the missing data. Our focus is on stationary performance and present explicit expressions for the optimal designs that minimize the stationary state estimation error variance. A toy-example is provided to illustrate our results.

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“…For example, in [1], [2] the authors addressed the problem of stabilization of an unstable plant through a rate-limited erasure channel where no performance index is considered besides stability. Other researchers have tried to tackle the channel limitations by using analog models in order to {chiuso|schenato}@dei.unipd.it avoid the difficulties associated with explicit design of digital channel encoder/decoder and to optimize some performance metrics among all possible stabilizing controllers subject to packet loss [3], [4] or subject to a maximum signal-tonoise (SNR) ratio [5], [6]. Finally, another well explored approach is the analysis of control systems subject to random packet loss [7], [8], [9], [10] under LQG framework.…”

Section: Introductionmentioning

confidence: 99%

Remote estimation subject to packet loss and quantization noise

Dey

Chiuso

Schenato

2013

52nd IEEE Conference on Decision and Control

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In this paper we consider the problem of designing coding and decoding schemes to estimate the state of a scalar stable stochastic linear system in the presence of a wireless communication channel between the sensor and the estimator. In particular, we consider a communication channel which is prone to packet loss and includes quantization noise due to its limited capacity. We study two scenarios: the first with channel feedback and the second with no channel feedback. More specifically, in the first scenario the transmitter is aware of the quantization noise and the packet loss history of the channel, while in the second scenario the transmitter is aware of the quantization noise only. We show that in the first scenario, the optimal strategy among all possible linear encoders corresponds to the transmission of the Kalman filter innovation similarly to the differential pulse-code modulation (DPCM). In the second scenario, we show that there is a critical packet loss probability above which it is better to transmit the state rather than the innovation. We also propose a heuristic strategy based on the transmission of a convex combination of the state and the Kalman filter innovation which is shown to provide a performance close to the one obtained with channel feedback.

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Control of LTI plants over erasure channels

Cited by 35 publications

References 21 publications

Performance limitations for SISO LTI plants controlled over SNR constrained channels

Performance limitations for SISO LTI plants controlled over SNR constrained channels

An approach to stationary state estimation with missing data

Remote estimation subject to packet loss and quantization noise

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