Automatic parameter selection ZVD shaping algorithm for crane vibration suppression based on particle swarm optimisation

Abstract

This work introduces the foundation of a new class of input shaping algorithm, designed based on the particle swarm optimisation. This algorithm is utilised to control the residual vibrations in the crane system. The motivation is the development of simple algorithms and architecture for controlling the motion in under-actuated nonlinear systems with minimal modelling effort. By recording the payload swing signal of the crane only once, the approach can automatically calculate the optimisation amplitude and time locations of the impulses required by a common zero-vibration-derivative (ZVD) technique. In this work, we use this algorithm to design a ZVD shaper for controlling the motion of an under-actuated nonlinear crane model system. We validate the approach using experiments. If this algorithm is implanted into the embedded system and applied to the actual crane, which will solve the problem of the traditional ZVD parameter adjustment and improve the vibration suppression effect of the ZVD Algorithm.

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Seismic Inversion Problem Using a Multioperator Whale Optimization Algorithm

“…e Cauchy factor is introduced (see lines 13, 18, and 24 lines) to calculate the fitness together (see lines 33). e greedy strategy is used to compare the fitness of V(t) and X(t), and the smallest is selected as the fitness of the iteration (see lines [34][35][36][37][38][39]). e original three WOA operators are used in lines 11-12, 15-16, and 26-27, respectively.…”

“…end if (30) end if (31) end for (32) end for (33) Calculate the fitness values (34) if fit (V(t)) < fit (X(t)) then (35) Select the fitness fit (V(t)) (36) else then (37) Select the fitness fit (X(t)) (38) end if (39) end while ALGORITHM 1: MOWOA.…”

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