AI RESEARCH
Control of a Twin Rotor using Twin Delayed Deep Deterministic Policy Gradient (TD3)
arXiv CS.AI
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ArXi:2512.13356v2 Announce Type: replace-cross This paper proposes a reinforcement learning (RL) framework for controlling and stabilizing the Twin Rotor Aerodynamic System (TRAS) at specific pitch and azimuth angles and tracking a given trajectory. The complex dynamics and non-linear characteristics of the TRAS make it challenging to control using traditional control algorithms. However, recent developments in RL have attracted interest due to their potential applications in the control of multirotors.