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Multi-Agent Systems: Automation and Control Engineering

Autor China. ) Guo, Xiang-Gui (University of Science and Technology Beijing, Singapore) Wang, Jian-Liang (Nanyang Technological University, Singapore) Liao, Fang (National University of Singapore, Singapore) Teo, Rodney Swee Huat (National University of Singapore
en Limba Engleză Hardback – 27 iun 2019
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.
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Specificații

ISBN-13: 9780367254322
ISBN-10: 0367254328
Pagini: 222
Ilustrații: 20 Tables, black and white; 64 Illustrations, black and white
Dimensiuni: 156 x 235 x 20 mm
Greutate: 0 kg
Editura: Taylor & Francis Ltd.
Colecția Automation and Control Engineering
Seria Automation and Control Engineering


Descriere

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.