Model-Free H Prescribed Performance Control of Adaptive Cruise Control Systems via Policy Learning

• Published in: IEEE transactions on intelligent transportation systems pp. 1 - 11
• Main Authors: Zhao, Jun, Jia, Bingyi, Zhao, Ziliang
• Format: Journal Article
• Language: English
• Published: IEEE 2024
• Subjects: <inline-formula xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <tex-math notation="LaTeX"> H_{\infty}</tex-math> </inline-formula> control; Adaptation models; adaptive cruise control system; Computational modeling; Cruise control; cyber-physical system; Heuristic algorithms; Mathematical models; model-free control; Policy learning; reinforcement learning; Safety; System dynamics; Uncertainty; Vehicle dynamics; Vehicles

Model-free control does not require precise system dynamic information, but rather meets performance requirements by directly designing a control law. This method is particularly suitable for adaptive cruise control (ACC) systems in cyber-physical system (CPS) environments, as it can effectively han...