Overhead crane systems require precise control to ensure safety and optimize performance. To accomplish this, a hybrid adaptive control scheme is proposed. Two separate active disturbance rejection controls (ADRCs) are employed to accurately regulate the movement of the trolley and the payload, as well as effectively counteract internal disturbances caused by the payload vibration. In addition, radial basis function network-based input shaping (RBFN-IS) is utilized to minimize payload oscillations during operation. The RBFNs continuously update the parameters of the input shaping in real time based on the measurements of the cable length and payload mass. Furthermore, the particle swarm optimization (PSO) algorithm is employed to search for optimal parameters of the input shaping for specific cable length and payload mass, thereby aiming to improve the vibration suppression capability even in the case of varying cable length. The experimental results obtained successfully validate the proposed method.
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