Abstract

One of the unsafe factors of heavy-duty crane ships is the load swing instability during the operation. A dynamic model of heavy-duty crane operation excitation based on the Lagrange equation was established in this paper to improve performance. This paper formed a luffing and slewing joint delay feedback control (L-S DFC) mechanism, established by controlling the boom's pitch and rotation motion. This paper also has given the real-time simulation of the controller carried out in time domain. The experimental results show that, compared with the existing control method based on slewing mechanism under the same condition, the given L-S DFC can restrain the swing of load in a shorter time, hence to ensure the safe operation of Heavy-duty crane ship.

Introduction

Marine cranes are the leading loading equipment for bulk carriers and other ships with heavy lift in different ports at sea-transportation. However, in loading and unloading large cargoes by cranes, the sea waves' interference would cause the ship to shake violently. Hence the acceleration of the crane would stimulate. It causes chaotic movement of the goods lifting, causing sudden changes in the sling's tension value and quickly causing accidents, e.g., sling breakage. Committed to solving the crane's swing movement and reducing the crane sling's tension value during the lifting process, it has always been a critical issue in the field of offshore manipulation. By applying joint delay feedback control to the crane's luffing and slewing mechanism, the L-S DFC was established, eliminating the swing of the goods being lifted in a shorter time and obtaining a better spatial distribution tension value.

In1960s, Lorenz (1963), a meteorologist at MIT, pointed the link between non-periodic and unpredictability called the chaotic system in theJournal of Atmospheric Sciences. At the same time, Pyragas (1992) proposed a time-delayed feedback control theory as an extension of chaotic systems. In 2001, Kimiaghalam, Homaifar, and Sayarrodsari (2001) aimed at the crane's highly nonlinear motion equation's analytical controller solution was too complicated and proposed a model prediction-based control (MPC) method of introducing feedforward control law. This method compensated for the lack of feedforward controller for load swings caused by measurement errors and other disturbance control. MPC method makes up for the deficiency of feedforward control, and Kimiaghalam et al. experiment also shows better control effect than feedforward control. It noted from 2001 to 2006 (Kimiaghalam, 2001; Nayfeh, 2002; Dadone, 2002; Kim, 2004; Daqaq, 2006;) that the feedback control theory based on the state observer continuously applied to the container handling control of gantry and other shore cranes.

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