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Multi Agent Systems Platoon Control by Guo Xiang Gui (20 results)
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US$ 8.31
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Add to basketCondition: Very Good. 1735644309. 12/31/2024 11:25:09 AM.
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Add to basketCondition: Very Good. This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
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Add to basketCondition: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.
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Multi-Agent Systems: Platoon Control and Non-Fragile Quantized Consensus
Published by Taylor & Francis Ltd, 2022
ISBN 10: 1032338318 ISBN 13: 9781032338316
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 104.73
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Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 185.
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Multi-agent Systems : Platoon Control and Non-fragile Quantized Consensus
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 102.37
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Multi-agent Systems : Platoon Control and Non-fragile Quantized Consensus
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 104.71
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Multi-Agent Systems: Platoon Control and Non-Fragile Quantized Consensus (Automation and Control Engineering)
Published by Taylor & Francis Group, 2019
ISBN 10: 0367254328 ISBN 13: 9780367254322
Language: English
Condition: New. 1st edition NO-PA16APR2015-KAP.
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Multi-Agent Systems: Platoon Control and Non-Fragile Quantized Consensus (Automation and Control Engineering)
Published by Taylor & Francis Group, 2019
ISBN 10: 0367254328 ISBN 13: 9780367254322
Language: English
US$ 177.80
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Multi-Agent Systems: Platoon Control and Non-Fragile Quantized Consensus (Automation and Control Engineering)
Published by CRC Press 2019-08-02, 2019
ISBN 10: 0367254328 ISBN 13: 9780367254322
Language: English
US$ 185.87
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Add to basketHardcover. Condition: New.
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Condition: New.
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Multi-Agent Systems: Platoon Control and Non-Fragile Quantized Consensus (Automation and Control Engineering)
Published by Taylor & Francis Group, 2019
ISBN 10: 0367254328 ISBN 13: 9780367254322
Language: English
US$ 207.46
Convert currencyUS$ 11.55 shipping from Germany to U.S.A.Quantity: 4 available
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Multi-Agent Systems : Platoon Control and Non-Fragile Quantized Consensus
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US$ 224.77
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Add to basketHardcover. Condition: New. New. book.
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Multi-Agent Systems : Platoon Control and Non-Fragile Quantized Consensus
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 252.93
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US$ 289.70
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Add to basketHardcover. Condition: Brand New. 240 pages. 9.25x6.25x0.75 inches. In Stock.
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US$ 91.46
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Xiang-Gui Guo is an Associate Professor with the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China. Jian-Liang Wang is an Associate Professor with the Sc.
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US$ 122.17
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Multi-Agent Systems: Platoon Control and Non-Fragile Quantized Consensus aims to present recent research results in designing platoon control and non-fragile quantized consensus for multi-agent systems. The main feature of this book is that distributed adaptive sliding mode control (SMC) algorithms are proposed to guarantee strong string stability based on modified constant time headway (MCTH) policy. The MCTH policy is used to remove the unrealistic assumption in the most existing literature that initial spacing, velocity and acceleration errors are zero. This monograph investigates the platoon control issue by combining SMC technique with neural network and fuzzy logic system approximation methods.
