Asset Details
Do you wish to reserve the book?
Dual‐Observer Based Resilient Control for Vehicle Trajectory Tracking Under Tri‐Modal Cyber Attacks
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Dual‐Observer Based Resilient Control for Vehicle Trajectory Tracking Under Tri‐Modal Cyber Attacks
Do you wish to request the book?
Dual‐Observer Based Resilient Control for Vehicle Trajectory Tracking Under Tri‐Modal Cyber Attacks
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Dual‐Observer Based Resilient Control for Vehicle Trajectory Tracking Under Tri‐Modal Cyber Attacks
2025
Overview
This study addresses vehicle trajectory tracking control under tri‐modal cyber attacks, encompassing fixed sensor‐to‐controller/controller‐to‐actuator channel attacks in lateral dynamics and sparse multi‐sensor attacks in position tracking. A hybrid fuzzy modeling framework is developed, integrating fuzzy logic inference with Takagi‐Sugeno fuzzy techniques to approximate vehicle dynamics with time‐varying velocity, payload‐dependent mass, and unmeasurable cornering stiffness avoiding the conservatism inherent in conventional linear fractional transformation approaches for cornering stiffness parameterization. A dual‐observer architecture combining an extended state observer and a supervisory fuzzy reduced‐order observer (ESO‐SFRO) is proposed for simultaneous system state reconstruction and tri‐modal attack signal estimation. Based on the estimated states, a cyber‐resilient controller is designed to ensure lateral stability and trajectory tracking accuracy. Experimental validation via CarSim/Simulink co‐simulation demonstrates the proposed ESO‐SFRO based controller exhibits superior dynamic stability and trajectory tracking performance under coupled cyber‐physical disturbances. This study proposes a hybrid fuzzy modeling framework for vehicle trajectory tracking under tri‐modal cyber attacks, integrating Takagi‐Sugeno techniques to handle time‐varying dynamics and unmeasurable cornering stiffness. A dual‐observer architecture (ESO‐SFRO) simultaneously reconstructs system states and estimates attack signals, enabling a cyber‐resilient controller that ensures lateral stability and tracking accuracy. CarSim/Simulink co‐simulation validates the controller's robustness against coupled cyber‐physical disturbances.
Publisher
John Wiley & Sons, Inc
