2017 IEEE Energy Conversion Congress and Exposition (ECCE) 2017
DOI: 10.1109/ecce.2017.8095766
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Communication network latency compensation in modular multilevel converters

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Cited by 7 publications
(12 citation statements)
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“…Often, applications have a payload proportional to the number of nodes (P = κ • P Bytes/node ) or such dependency is a good approximation. If we neglect the protocol overhead (in an efficient protocol it should represent a small fraction of the payload) then the critical forwarding delay (T critical fw ), defined as the forwarding delay that equals the frame delay, becomes proportional to the communication bandwidth and payload per node Equation (5). Note that the number of nodes in the network becomes irrelevant.…”
Section: Link Technologymentioning
confidence: 99%
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“…Often, applications have a payload proportional to the number of nodes (P = κ • P Bytes/node ) or such dependency is a good approximation. If we neglect the protocol overhead (in an efficient protocol it should represent a small fraction of the payload) then the critical forwarding delay (T critical fw ), defined as the forwarding delay that equals the frame delay, becomes proportional to the communication bandwidth and payload per node Equation (5). Note that the number of nodes in the network becomes irrelevant.…”
Section: Link Technologymentioning
confidence: 99%
“…Another contribution of this work is the use of hardware accelerators to eliminate the node delay dependency on the packet size, a point often overlooked. This reduction is relevant, because it decreases the end-to-end delay that affects the application control performance [5], which is the sum of cycle time plus the node internal delays in transferring data to and from the network. Those accelerators can be easily implemented in Field Programmable Gate Array (FPGA) or Application Specific Integrated Circuit (ASIC) technologies.…”
Section: Introductionmentioning
confidence: 99%
“…Smith proposed what today is known as the Smith predictor [19]. Recently, Cortes et al adopted a similar approach to compensate for the delay introduced by Model Predictive Control calculations [20,21]. The main contributions of this work are: adoption of a model-based predictor for compensating the additional latency introduced by the communication network; description of modulation and balancing schemes pertinent to network controlled MMCs and its relation to the proposed estimation algorithm; assessment of parameter variations in the control performance; and validation of the concept in an experimental set-up.…”
Section: Starmentioning
confidence: 99%
“…It is possible to verify the system stability, study mismatches between plant and model or the effect of the controller tunning by calculating the eigenvalues of (14) in [21]. To exemplify, we discretized the plant (3) using a Zero-Order Hold and considered the closed-loop system with a delay of two samples (Figure 7).…”
Section: Parameters' Sensitivitymentioning
confidence: 99%
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