Payload Oscillations Minimization via Open Loop Control.

The results of tests of payload oscillations, forced by linear control function which allows to minimize payload sway after acceleration phase and after overhead crane stopping are presented in this paper. The analysis of solution of this problem has been carried out. The algorithm of operation for real drive system which takes into account the possibilities of driving of an overhead crane is also presented. The impact of inaccuracies of measurement of the ropes length on minimizing a displacements of payload during the duty cycle is shown as well. The correctness of the method is confirmed by results both simulation and experimental tests

ADVANCED ANTI-SWAY CONTROL FOR OVERHEAD CRANES

This particular project focuses on a complex system whose dynamics are not very well understood and hence control designs are not straightforward. The project deals with the control of industrial overhead cranes. The project has the potential of bringing many rewards to industries, which are concerned with optimising lifting equipment performance. Such a system will allow these industries to save time and consequently costs as the volume of loaded and unloaded goods increases. Part of this project is to model the system surrounding the crane system and then design a suitable algorithm for load anti-sway purposes. The objective of this project is to design and implement an intelligent based controller that can be used to assist a crane operator in the difficult parts of the operation. The designed controller should give the appropriate control signal to the crane system such that the time taken to reach the target position is minimised with a zero sway angle at the destination. Earlier part of the project consisting of analysing and improving if required the existing 3-D mathematical linear and non-linear crane models. Two different models have been investigated: one with a constant cable length and the other with a variable cable length. The implementation of the controller is based on Fuzzy Logic Control (FLC). Two types of FLC have been used and compared the Fixed FLC and the FLC based on Adaptive Neuro Fuzzy Inference System (ANFIS). Heuristic approaches have been used for tuning the Fixed FLC. Data obtained from the Fixed FLC are then used for training ANFIS FLC. The results prove that it is possible to model an off-line expert fuzzy logic controller for an overhead crane. The controller achieved satisfactorily results for a constant and a variable rope length with minimal tuning than the fixed fuzzy method. Proposals for further work are also briefly discussed

Fuzzy sliding mode control of an offshore container crane

© 2017 A fuzzy sliding mode control strategy for offshore container cranes is investigated in this study. The offshore operations of loading and unloading containers are performed between a mega container ship, called the mother ship, and a smaller ship, called the mobile harbor (MH), which is equipped with a container crane. The MH is used to transfer the containers, in the open sea, and deliver them to a conventional stevedoring port, thereby minimizing the port congestion and also eliminating the need of expanding outwards. The control objective during the loading and unloading process is to keep the payload in a desired tolerance in harsh conditions of the MH motion. The proposed control strategy combines a fuzzy sliding mode control law and a prediction algorithm based on Kalman filtering for the MH roll angle. Here, the sliding surface is designed to incorporate the desired trolley trajectory while suppressing the sway motion of the payload. To improve the control performance, the discontinuous gain of the sliding control is adjusted with fuzzy logic tuning schemes with respect to the sliding function and its rate of change. Chattering is further reduced by a saturation function. Simulation and experimental results are provided to verify the effectiveness of the proposed control system for offshore container cranes

LMI based antiswing adaptive controller for uncertain overhead cranes

This paper proposes an adaptive anti-sway controller for uncertain overhead cranes. The state-space model of the 2D overhead crane with the system parameter uncertainties is shown firstly. Next, the adaptive controller which can adapt with the system uncertainties and input disturbances is established. The proposed controller has ability to move the trolley to the destination in short time and with small oscillation of the load despite the effect of the uncertainties and disturbances. Moreover, the controller has simple structure so it is easy to execute. Also, the stability of the closed-loop system is analytically proven. The proposed algorithm is verified by using Matlab/Simulink simulation tool. The simulation results show that the presented controller gives better performances (i.e., fast transient response, position tracking, and low swing angle) than the state feedback controller when there exist system parameter variations as well as input disturbances

An Efficient Adaptive Hierarchical Sliding Mode Control Strategy Using Neural Networks for 3D Overhead Cranes

© 2019, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Gmbh Germany, part of Springer Nature. In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and real-life systems, where the results obtained by our method are highly promising

Comparative Assessment of Feed-forward Schemes with NCTF for Sway and Trajectory Control of a DPTOC

This paper presents a comparative assessment of feed-forward schemes in hybrid control schemes for anti-swaying and trajectory tracking of a double-pendulum-type overhead crane (DPTOC) system. A nonlinear DPTOC system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. To study the effectiveness of the controllers, initially nominal characteristics following trajectory following (NCTF) is developed for position control of cart movement. The controller design, which is comprised of a nominal characteristic trajectory (NCT) and PI compensator, is used to make the cart motion follow the NCT. This is then extended to incorporate feed-forward schemes for anti-swaying control of the system. Feed-forward control schemes based on input shaper and filtering techniques are to be examined. The input shaper and filtering techniques with different orders were designed based on properties of the system. The results of the response with the controllers are presented in time and frequency domains. The performances of hybrid control schemes are examined in terms of level of input tracking capability, sway angle reduction and time response specifications in comparison to NCTF controller. Finally, a comparative assessment of the control techniques is discussed and presented