1st Edition

Multi-Agent Systems Platoon Control and Non-Fragile Quantized Consensus

    236 Pages 64 B/W Illustrations
    by CRC Press

    236 Pages 64 B/W Illustrations
    by CRC Press

    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.

    1 Introduction

    1.1 Platoon Control

    1.2 Non-Fragile Quantized Consensus

    1.3 Preview of Chapters

    2 Preliminaries

    2.1 Notations

    2.2 Acronyms

    2.3 String Stability Theory

    2.4 Basic Algebraic Graph Theory

    2.5 H8 Performance Index

    2.6 Some Other Definitions and Lemmas

    3 String Stability of Vehicle Platoons with External Disturbances

    3.1 Introduction

    3.2 Model Description And Problem Formulation

    3.3 Design of Distributed Adaptive Integrated Sliding Mode (ISM) Control

    3.4 Numerical Examples

    3.5 Conclusion

    4 String Stability of Vehicle Platoons with Nonlinear Acceleration Uncertainties

    4.1 Introduction

    4.2 Vehicle Platoon And Problem Formulation

    4.3 Distributed Adaptive Integrated Sliding Mode Control (ISMC) Strategy

    4.4 Simulation Study and Performance Results

    4.5 Conclusion

    5 CNN-Based Adaptive Control for Vehicle Platoon with Input Saturation

    5.1 Introduction

    5.2 Vehicle-Following Platoon Model and Preliminaries

    5.3 Distributed Adaptive NN Control Design and Stability Analysis

    5.4 Simulation Study and Performance Results

    5.5 Conclusion

    6 Adaptive Fuzzy Fault-Tolerant Control for Multiple High-Speed Trains

    6.1 Introduction

    6.2 High-Speed Train Dynamics and Preliminaries

    6.3 PI-Based Sliding Mode and Coupled Sliding Mode

    6.4 Adaptive Fuzzy Control Design and Stability Analysis

    6.5 Simulation Study and Performance Results

    6.6 Conclusion

    7 Collision Avoidance for Vehicle Platoon with Input Deadzone and Spacing Constraints

    7.1 Introduction

    7.2 Vehicular Platoon Model And Preliminaries

    7.3 Distributed Adaptive NN Control Design

    7.4 Simulation Study

    7.5 Conclusion

    8 Neuro-Adaptive Quantized PID-Based SMC of Vehicular Platoon with Deadzone

    8.1 Introduction

    8.2 Vehicle-Following Platoon Model And Preliminaries

    8.3 Neuro-Adaptive Quantized PIDSMC Design and Strong String Stability Analysis

    8.4 Simulation Study

    8.5 Conclusion

    9 Low-Complexity Control of Vehicular Platoon with Asymmetric Saturation

    9.1 Introduction

    9.2 Vehicular Platoon Description

    9.3 Adaptive PIDSMC Design and Strong String Stability Analysis

    9.4 Simulation Results

    9.5 Conclusion

    10 Non-Fragile Quantized Consensus for Multi-Agent Systems Based On Incidence Matrix

    10.1 Introduction

    10.2 Uniform Quantizer and Logarithmic Quantizer

    10.3 Problem Formulation

    10.4 Non-Fragile Quantized Controller Design

    10.5 Numerical Example

    10.6 Conclusion

    11 Non-Fragile H8 Consensus for Multi-Agent Systems With Interval-Bounded Variations

    11.1 Introduction

    11.2 Problem Formulation

    11.3 Non-Fragile H8 Consensus For Multi-Agent Systems

    11.4 Numerical Example

    11.5 Conclusions

    12 Quantized H8 Consensus for Multi-Agent Systems With Quantization Mismatch

    12.1 Introduction

    12.2 Quantized H8 Consensus for General Linear Dynamics

    12.3 Quantized H8 Consensus for Lipschitz Nonlinearity

    12.4 Numerical Examples

    12.4.1 Example 1

    12.4.2 Example 2

    12.5 Conclusion

    Bibliography

    Index

    Biography

    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.