Online-estimation-based Backstepping Control of Bridge Crane

To deal with the uncertainty of bridge crane models, we developed an online-estimation-based backstepping control design method. Compared with conventional bridge-crane controls, the proposed method does not require a system-specific mathematical model, nor does it need to decouple or linearize the system. The proposed method uses only the real-time measurement data of the system and online estimation by the model to implement backstepping control by separating the system into fully-actuated and under-actuated subsystems. The proposed design method can handle model uncertainty due to varying crane loads, internal friction, and dynamic coupling. We confirm the stability of the closed-loop system using the Lyapunov method. The numerical simulation and experimental results demonstrate the feasibility and effectiveness of the proposed method.