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E-grāmata: Multi-Agent Systems: Platoon Control and Non-Fragile Quantized Consensus

(Nanyang Technological University, Singapore), (National University of Singapore, Singapore), (University of Science and Technology Beijing, China.), (National University of Singapore, Singapore)
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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.



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. It investigates the platoon control issue by combining SMC technique with neural network and fuzzy logic system approximation methods.

Introduction. Preliminaries. String Stability of Vehicle Platoons with External Disturbances. String Stability of Vehicle Platoons with Nonlinear Acceleration Uncertainties. CNN-Based Adaptive Control for Vehicle Platoon with Input Saturation. Adaptive Fuzzy Fault-Tolerant Control for Multiple High-Speed Trains. Collision Avoidance for Vehicle Platoon with Input Deadzone and Spacing Constraints. Neuro-Adaptive Quantized PID-Based SMC of Vehicular Platoon with Deadzone. Low-Complexity Control of Vehicular Platoon with Asymmetric Saturation. Non-Fragile Quantized Consensus for Multi-Agent Systems Based On Incidence Matrix. Non-Fragile H8 Consensus for Multi-Agent Systems With Interval-Bounded Variations. Quantized H8 Consensus for Multi-Agent Systems With Quantization Mismatch. Bibliography. Index
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 School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore.

Fang Liao is a Research Scientist with Temasek Laboratories, National University of Singapore, Singapore. Rodney Swee Huat Teo is a Principal Member of Technical Staff of the DSO National Laboratories, Singapore, and a Senior Research Scientist with Temasek Laboratories, National University of Singapore.