Ye Ren
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Author Swipe
View article: Performance Comparison of RANSAC and Other Model Estimation Methods in Panoramic Image Mosaic
Performance Comparison of RANSAC and Other Model Estimation Methods in Panoramic Image Mosaic Open
As computer vision technology advances, the significance of outlier processing algorithms increases across various applications. Despite this, there is a lack of comprehensive comparisons to assess the performance of these algorithms. This…
View article: Data-Driven Bus Trajectory Tracking Based on Feedforward–Feedback Model-Free Adaptive Iterative Learning Control
Data-Driven Bus Trajectory Tracking Based on Feedforward–Feedback Model-Free Adaptive Iterative Learning Control Open
This paper presents a scheme for the feedforward–feedback longitudinal trajectory tracking control of buses. The scheme is specifically designed to address the periodic and repetitive nature of bus operations. First, the vehicle’s longitud…
View article: Model-free adaptive consensus design for a class of unknown heterogeneous nonlinear multi-agent systems with packet dropouts
Model-free adaptive consensus design for a class of unknown heterogeneous nonlinear multi-agent systems with packet dropouts Open
This paper studies the consensus problem for a class of unknown heterogeneous nonlinear multi-agent systems via a network with random packet dropouts. Based on the dynamic linearization technique, novel model-free adaptive consensus protoc…
View article: Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach
Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach Open
This paper studies the containment control problem of heterogeneous multi-agent systems (MASs) with multiple leaders. The follower agent dynamics are assumed to be unknown and nonlinear. First, each follower is transformed into an incremen…
View article: Feedforward–feedback-enhanced model-free adaptive iterative learning control with measurement disturbance and data dropout for an autonomous bus trajectory tracking system
Feedforward–feedback-enhanced model-free adaptive iterative learning control with measurement disturbance and data dropout for an autonomous bus trajectory tracking system Open
This article presents an innovative enhanced model-free adaptive iterative learning control approach suited for autonomous bus trajectory tracking systems that may experience measurement disruptions and random data dropouts. Data loss can …
View article: Data-Driven Kalman Consensus Filtering for Connected Vehicle Speed Estimation in a Multi-Sensor Network
Data-Driven Kalman Consensus Filtering for Connected Vehicle Speed Estimation in a Multi-Sensor Network Open
The autonomous traffic system has imposed higher requirements on the speed estimation of connected vehicles, where the speed of connected vehicles, as one of the control conditions for refined traffic management, plays a crucial role in th…
View article: Data-Driven RBFNN-Enhanced Model-Free Adaptive Traffic Symmetrical Signal Control for a Multi-Phase Intersection with Fast-Changing Traffic Flow
Data-Driven RBFNN-Enhanced Model-Free Adaptive Traffic Symmetrical Signal Control for a Multi-Phase Intersection with Fast-Changing Traffic Flow Open
Fast-changing demand in real traffic systems always leads to asymmetrical traffic flow and queues, which aggravates congestion and energy waste. In this paper, the traffic signal control problem of multi-phase intersections was studied wit…
View article: On the Urban Link Fundamental Diagram Based on Velocity-Weighted Flow and Queue Length
On the Urban Link Fundamental Diagram Based on Velocity-Weighted Flow and Queue Length Open
For uninterrupted traffic flow, it is well-known that the fundamental diagram (FD) describes the relationship between traffic flow and density under steady state. To study the characteristics of interrupted traffic flow on a signalized lin…
View article: Data driven model free adaptive iterative learning perimeter control for large-scale urban road networks
Data driven model free adaptive iterative learning perimeter control for large-scale urban road networks Open
View article: A Data-Driven Distributed Adaptive Control Approach for Nonlinear Multi-Agent Systems
A Data-Driven Distributed Adaptive Control Approach for Nonlinear Multi-Agent Systems Open
In this paper the distributed leader-follower consensus tracking problem is investigated for unknown nonlinear non-affine discrete-time multi-agent systems. Via a dynamic linearization method both for the agent system and the local ideal d…
View article: Robust model‐free adaptive iterative learning formation for unknown heterogeneous non‐linear multi‐agent systems
Robust model‐free adaptive iterative learning formation for unknown heterogeneous non‐linear multi‐agent systems Open
The formation problem for a class of non‐linear multi‐agent systems (MASs) is considered under bounded disturbance and repetitive environment. The agent dynamics here is unknown and heterogeneous, and the disturbances are both time‐varying…