scholarly journals Scalable Platooning Based on Directed Information Flow Topology With Granulating Method

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 176634-176645
Author(s):  
Wei Gao ◽  
Yan Shi ◽  
Shanzhi Chen
Keyword(s):  
Information Flow ◽  
Flow Topology ◽  
Directed Information

Smooth-Switching Control-Based Cooperative Adaptive Cruise Control by Considering Dynamic Information Flow Topology

2020 ◽  
Vol 2674 (4) ◽  
pp. 444-458
Author(s):  
Anye Zhou ◽  
Siyuan Gong ◽  
Chaojie Wang ◽  
Srinivas Peeta
Keyword(s):  
Information Flow ◽  
Adaptive Cruise Control ◽  
Switching Control ◽  
Cruise Control ◽  
Flow Topology ◽  
Dynamic Information ◽  
String Stability ◽  
Kalman Predictor ◽  
Cooperative Adaptive Cruise Control ◽  
Smooth Switching

Vehicle-to-vehicle communications can be unreliable because of interference and information congestion, which leads to the dynamic information flow topology (IFT) in a platoon of connected and autonomous vehicles. Some existing studies adaptively switch the controller of cooperative adaptive cruise control (CACC) to optimize string stability when IFT varies. However, the difference of transient response between controllers can induce uncomfortable jerks at switching instances, significantly affecting riding comfort and jeopardizing vehicle powertrain. To improve riding comfort while maintaining string stability, the authors introduce a smooth-switching control-based CACC scheme with IFT optimization (CACC-SOIFT) by implementing a bi-layer optimization model and a Kalman predictor. The first optimization layer balances the probability of communication failure and control performance optimally, generating a robust IFT to reduce controller switching. The second optimization layer adjusts the controller parameters to minimize tracking error and the undesired jerk. Further, a Kalman predictor is applied to predict vehicle acceleration if communication failures occur. It is also used to estimate the states of preceding vehicles to suppress the measurement noise and the acceleration disturbance. The effectiveness of the proposed CACC-SOIFT is validated through numerical experiments based on NGSIM field data. Results indicate that the CACC-SOIFT framework can guarantee string stability and riding comfort in the environment of dynamic IFT.

scholarly journals Directed information flow—A model free measure to analyze causal interactions in event related EEG-MEG-experiments

2008 ◽  
Vol 29 (2) ◽  
pp. 193-206 ◽  
Author(s):  
Hermann Hinrichs ◽  
Toemme Noesselt ◽  
Hans-Jochen Heinze
Keyword(s):  
Information Flow ◽  
Model Free ◽  
Directed Information

scholarly journals Stochastic given-time H∞ consensus over Markov jump networks with disturbance constraint

2016 ◽  
Vol 39 (8) ◽  
pp. 1253-1261 ◽  
Author(s):  
Xiaoli Luan ◽  
Yang Min ◽  
Zhengtao Ding ◽  
Fei Liu
Keyword(s):  
Information Flow ◽  
Disturbance Rejection ◽  
Model Transformation ◽  
Fixed Time ◽  
Time Interval ◽  
Markov Jump ◽  
Fixed Time Interval ◽  
Directed Information ◽  
Simulation Results ◽  
The Given

In this study, the given-time H∞ consensus problem over networks with directed information flow and Markov jump topologies is addressed. Our focus is on keeping the disagreement dynamics of networks confined within the prescribed bound in the fixed time interval. Compared with the asymptotical consensus in infinite settling time, the proposed algorithm is less conservative. In addition, a new model transformation approach is presented to make the design results more advantageous in commonality. Simulation results show the effectiveness of the proposed controller, and reveal that the prescribed boundary of the disagreement trajectory has an effect on disturbance rejection performance.

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