Neural Adaptive Sliding-Mode Control of a Vehicle Platoon Using Output Feedback

This paper investigates the output feedback control problem of a vehicle platoon with a constant time headway (CTH) policy, where each vehicle can communicate with its consecutive vehicles. Firstly, based on the integrated-sliding-mode (ISM) technique, a neural adaptive sliding-mode control algorithm is developed to ensure that the vehicle platoon is moving with the CTH policy and full state measurement. Then, to further decrease the measurement complexity and reduce the communication load, an output feedback control protocol is proposed with only position information, in which a higher order sliding-mode observer is designed to estimate the other required information (velocities and accelerations). In order to avoid collisions among the vehicles, the string stability of the whole vehicle platoon is proven through the stability theorem. Finally, numerical simulation results are provided to verify its effectiveness and advantages over the traditional sliding-mode control method in vehicle platoons.

[1]  Yang Shi,et al.  Design and Implementation of Nonuniform Sampling Cooperative Control on A Group of Two-Wheeled Mobile Robots , 2017, IEEE Transactions on Industrial Electronics.

[2]  Clive Roberts,et al.  Cooperative adaptive bidirectional control of a train platoon for efficient utility and string stability , 2015 .

[3]  Le Yi Wang,et al.  Stability Margin Improvement of Vehicular Platoon Considering Undirected Topology and Asymmetric Control , 2016, IEEE Transactions on Control Systems Technology.

[4]  Jianqiang Wang,et al.  Stability and Scalability of Homogeneous Vehicular Platoon: Study on the Influence of Information Flow Topologies , 2016, IEEE Transactions on Intelligent Transportation Systems.

[5]  Xing-Gang Yan,et al.  Decentralised sliding mode control for a class of nonlinear interconnected systems , 2015, 2015 American Control Conference (ACC).

[6]  Shin Kato,et al.  An automated truck platoon for energy saving , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Huazhen Fang,et al.  Advanced Control in Marine Mechatronic Systems: A Survey , 2017, IEEE/ASME Transactions on Mechatronics.

[8]  Feng Gao,et al.  Practical String Stability of Platoon of Adaptive Cruise Control Vehicles , 2011, IEEE Transactions on Intelligent Transportation Systems.

[9]  Arie Levant,et al.  Higher-order sliding modes, differentiation and output-feedback control , 2003 .

[10]  Long Wang,et al.  Recent Advances in Consensus of Multi-Agent Systems: A Brief Survey , 2017, IEEE Transactions on Industrial Electronics.

[11]  Richard H. Middleton,et al.  Time headway requirements for string stability of homogeneous linear unidirectionally connected systems , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[12]  Karl Henrik Johansson,et al.  String Stability and a Delay-Based Spacing Policy for Vehicle Platoons Subject to Disturbances , 2017, IEEE Transactions on Automatic Control.

[13]  Sabina Jeschke,et al.  A Review of Truck Platooning Projects for Energy Savings , 2016, IEEE Transactions on Intelligent Vehicles.

[14]  Yang Zheng,et al.  Distributed sliding mode control for multi-vehicle systems with positive definite topologies , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[15]  Dongkyoung Chwa,et al.  Adaptive Bidirectional Platoon Control Using a Coupled Sliding Mode Control Method , 2014, IEEE Transactions on Intelligent Transportation Systems.

[16]  Prabir Barooah,et al.  On Achieving Size-Independent Stability Margin of Vehicular Lattice Formations With Distributed Control , 2012, IEEE Transactions on Automatic Control.

[17]  Yang Shi,et al.  Integral Sliding Mode Flight Controller Design for a Quadrotor and the Application in a Heterogeneous Multi-Agent System , 2017, IEEE Transactions on Industrial Electronics.

[18]  Mario di Bernardo,et al.  Design, Analysis, and Experimental Validation of a Distributed Protocol for Platooning in the Presence of Time-Varying Heterogeneous Delays , 2016, IEEE Transactions on Control Systems Technology.

[19]  Bingxian Mu,et al.  Cooperative control of quadrotors and mobile robots: controller design and experiments , 2017 .

[20]  Francesco Viti,et al.  Impact of different spacing policies for adaptive cruise control on traffic and energy consumption of electric vehicles , 2016, 2016 24th Mediterranean Conference on Control and Automation (MED).

[21]  Dan Martinec,et al.  Nonzero Bound on Fiedler Eigenvalue Causes Exponential Growth of H-Infinity Norm of Vehicular Platoon , 2014, IEEE Transactions on Automatic Control.

[22]  Huijun Gao,et al.  On Group Synchronization for Interacting Clusters of Heterogeneous Systems , 2017, IEEE Transactions on Cybernetics.

[23]  Vicente Milanés Montero,et al.  Cooperative Adaptive Cruise Control in Real Traffic Situations , 2014, IEEE Transactions on Intelligent Transportation Systems.

[24]  Prabir Barooah,et al.  Stability and robustness of large platoons of vehicles with double‐integrator models and nearest neighbor interaction , 2013 .

[25]  Karl Henrik Johansson,et al.  Guaranteeing safety for heavy duty vehicle platooning : Safe set computations and experimental evaluations , 2014 .

[26]  J. J. P. Veerman,et al.  Asymmetric Decentralized Flocks , 2012, IEEE Transactions on Automatic Control.

[27]  William B. Dunbar,et al.  Distributed Receding Horizon Control of Vehicle Platoons: Stability and String Stability , 2012, IEEE Transactions on Automatic Control.

[28]  Elham Semsar-Kazerooni,et al.  The Grand Cooperative Driving Challenge 2016: boosting the introduction of cooperative automated vehicles , 2016, IEEE Wireless Communications.

[29]  Ioannis Kanellakopoulos,et al.  Nonlinear spacing policies for automated heavy-duty vehicles , 1998 .

[30]  Jonas Fredriksson,et al.  A receding horizon approach to string stable cooperative adaptive cruise control , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[31]  Philippe Martinet,et al.  The Flatbed Platoon Towing Model for Safe and Dense Platooning on Highways , 2015, IEEE Intelligent Transportation Systems Magazine.

[32]  Nathan van de Wouw,et al.  Cooperative Adaptive Cruise Control: Network-Aware Analysis of String Stability , 2014, IEEE Transactions on Intelligent Transportation Systems.

[33]  A. Levant.  UNIVERSAL OUTPUT-FEEDBACK SISO CONTROLLER , 2002 .

[34]  Jianliang Wang,et al.  Distributed Adaptive Integrated-Sliding-Mode Controller Synthesis for String Stability of Vehicle Platoons , 2016, IEEE Transactions on Intelligent Transportation Systems.

[35]  Yury Orlov,et al.  Output feedback control synthesis for non-linear time-delay systems using a sliding-mode observer , 2014, IMA J. Math. Control. Inf..

[36]  Fu Lin,et al.  Algorithms for Leader Selection in Stochastically Forced Consensus Networks , 2013, IEEE Transactions on Automatic Control.

[37]  Jianliang Wang,et al.  Distributed Adaptive Sliding Mode Control Strategy for Vehicle-Following Systems With Nonlinear Acceleration Uncertainties , 2017, IEEE Transactions on Vehicular Technology.

[38]  Mario di Bernardo,et al.  Distributed Consensus Strategy for Platooning of Vehicles in the Presence of Time-Varying Heterogeneous Communication Delays , 2015, IEEE Transactions on Intelligent Transportation Systems.

[39]  Ge Guo,et al.  Autonomous Platoon Control Allowing Range-Limited Sensors , 2012, IEEE Transactions on Vehicular Technology.

[40]  Hairong Dong,et al.  Adaptive fault-tolerant automatic train operation using RBF neural networks , 2014, Neural Computing and Applications.

[41]  Nathan van de Wouw,et al.  Lp String Stability of Cascaded Systems: Application to Vehicle Platooning , 2014, IEEE Transactions on Control Systems Technology.