Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol. 5, No. 1, March 2017, pp. 85~98 ISSN: 2089-3272, DOI: 10.11591/ijeei.v5i1.256  85 Received October 9, 2016; Revised January 23, 2017; Accepted February 15, 2017 Fuzzy Control of a Large Crane Structure Samir A. Farag 1* , Salah G. Foda 2 , and Ahmed Alenany 3 1 Department of Electrical and computer Engineering, Higher Technological Institute (H.T.I), 10th of Ramadan, Egypt. 2 Department of Mechanical Engineering, Future University (F.U.E), Egypt. 3 Department of Computers and Systems Engineering, Zagazig University, Egypt. e-mail: samir.harb22@yahoo.com*, salah.foda@fue.edu.eg, alenany102@hotmail.com Abstract The usage of tower cranes, one type of rotary cranes, is common in many industrial structures, e.g., shipyards, factories, etc. With the size of these cranes becoming larger and the motion expected to be faster and has no prescribed path, their manual operation becomes difficult and hence, automatic closed-loop control schemes are very important in the operation of rotary crane. In this paper, the plant of concern is a tower crane consists of a rotatable jib that carries a trolley which is capable of traveling over the length of the jib. There is a pendulum-like end line attached to the trolley through a cable of variable length. A fuzzy logic controller with various types of membership functions is implemented for controlling the position of the trolley and damping the load oscillations. It consists of two main types of controllers radial and rotational each of two fuzzy inference engines (FIEs). The radial controller is used to control the trolley position and the rotational is used for damping the load oscillations. Computer simulations are used to verify the performance of the controller. The results from the simulations show the effectiveness of the method in the control of tower crane keeping load swings small at the end of motion. Keywords: fuzzy control, crane structure, controller, fuzzy inference engines (FIEs). 1. Introduction A crane is a specific machine that is equipped with chains or wires, and sheaves and used for transportation of heavy loads and hazardous materials in factories, shipyards, high- building construction, and nuclear installations. The main task of crane in industry is to move a load from one point to another without swinging (minimum swing as possible) in the minimum time. Doing this task needs a skillful operator using his/her experience to immediately stop the swing at the right position and the operator has to wait until the load stops swinging. The failure in controlling crane might also cause accident and harm people. During the crane operation, the load - held by crane - is free to swing in a pendulum-like pattern. The nonlinear properties of crane bring about undesired swings, especially at take-off and arrival. Such uncontrolled swings cause both stability and safety problems. If these swings exceed the allowable limits, there will be two options; which are damping the swings or stopping the operation until the swings die out. Either of the two options consumes time, and hence reduces the facility availability [1]. The aforementioned problems have motivated many researchers to develop control approaches to automate cranes. However, two problems arise in automation of crane operations. Firstly, cranes belong to a class of under-actuated/under-constrained mechanical systems, i.e., in which the number of control input/outputs is fewer than degrees of freedom. In other words, a limited number of inputs control more outputs. Secondly, the unstructured nature of the crane environment in factory floors, shipyards...etc. So, the control algorithm should be able to cope with these problems. Enormous controlling approaches were implemented for controlling cranes systems based on open-loop and closed-loop control systems [3, 6, 10, 14]. Approaches to control the crane operations can be summarized as follows. 1.1. Open-loop controllers An early used approach of open loop controller utilizes the natural frequency of the suspended object in presenting an open-loop-optimal-programmed control strategy. This means damping vibrations with the aid of a specific case from a general control technique involving shaping of inputs [2, 8].