System parametric independent structure for robust vibration suppression and tracking control of tower cranes
Abstract
This paper presents a new non-recursive robust adaptive control method, utilizing a non-recursive finite-time state observer, designed to minimize payload oscillations and accurately track payload trajectories for 3D tower cranes despite parameter uncertainties and external disturbances during lifting and transportation. This model-independent state observer is designed to estimate states, such as the payload’s swing angle velocity, which are challenging or impossible to measure directly with sensors. To bypass the complexities of parameter estimation and handle model uncertainties, the novel non-recursive robust adaptive controller is designed to function without prior model knowledge, using only a time-varying control gain that adapts online. Lyapunov stability theory is utilized to analyze and validate the closed-loop control system’s stability. The control law, known for its computational efficiency and strong sway suppression, guarantees that the payload trajectory tracking error and all closed-loop system parameters remain bounded and ultimately converge to zero. The feasibility and effectiveness of the proposed controller are validated through a quasi-physical simulation. The results are qualitatively compared with those of (i) a second-order sliding mode control using an adaptive finite-time extended state observer and (ii) an adaptive sliding mode control based on time-delay estimation utilizing a non-recursive finite-time state observer.