Ansei Yonezawa

Model-Based Assisted Domain-Randomized Reinforcement Learning for Robust Powertrain Vibration Control

Automotive powertrain systems exhibit strong nonlinearities and parametric variations that limit the performance of controllers designed from nominal models. While deep reinforcement learning (DRL) can address such complexities, policies trained in simulation often lack robustness under real-world uncertainties, especi...