2011
DOI: 10.1109/tcst.2010.2056690
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Discrete-Time Sliding-Mode Congestion Control in Multisource Communication Networks With Time-Varying Delay

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Cited by 55 publications
(31 citation statements)
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“…Consequently, for k ≥ k 0 , the nonlinear controller (33) becomes equivalent to the linear control law (15), whose action influences the stock level for k ≥ n + k 0 . Since both controllers incorporate the order history in exactly the same way, then taking into account relation (25), the proposition is valid as a direct consequence of Theorem 3. This completes the proof.…”
Section: Theoremmentioning
confidence: 89%
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“…Consequently, for k ≥ k 0 , the nonlinear controller (33) becomes equivalent to the linear control law (15), whose action influences the stock level for k ≥ n + k 0 . Since both controllers incorporate the order history in exactly the same way, then taking into account relation (25), the proposition is valid as a direct consequence of Theorem 3. This completes the proof.…”
Section: Theoremmentioning
confidence: 89%
“…If policy (33) is applied to system (5)-(6), and the reference stock level satisfies inequality (25), then for any k ≥ n + k 0 the stock level is strictly positive and demand is entirely satisfied from the readily available resources.…”
Section: Theoremmentioning
confidence: 99%
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“…It is worth mentioning that, delays are mainly divided into the fixed communication delays and random communication delays, and various delay compensation schemes for fixed communication delays are compared in this paper, such as the neural network predictive control [96], weighted average predictive control [97,98], the gain scheduling [99][100][101][102][103][104][105][106] and synchronization schemes using multi-timer model [114]. Moreover, some compensation methods for random communication delays are also discussed, such as the generalized predictive control (GPC) [84,85], networked predictive control (NPC) [86][87][88][89], model predictive control (MPC) [90][91][92][93], Smith predictor (SP) [90,94,95], H ∞ control [107][108][109] and sliding mode control [110][111][112][113], etc. In addition, if one microgrid plugs in or plug out from the microgrid clusters, the topology and structure of the system will be inevitably different.…”
Section: Introductionmentioning
confidence: 99%
“…A dead-beat sliding mode controller for multi-source networks with a priori known round trip times is presented by Bartoszewicz and Zuk (2009), whereas in the work of Ignaciuk and Bartoszewicz (2008) an LQ optimal sliding mode controller for single-source networks is proposed. The same approach is then extended for multi-source networks by Ignaciuk and , who also design a similar optimal flow controller for multi-source networks with the round trip times which may change during the control process (Ignaciuk and Bartoszewicz, 2011).…”
mentioning
confidence: 99%