Optimal PID and fuzzy logic based position controller design of an overhead crane using the Bees Algorithm

Different industrial applications frequently use overhead cranes for moving and lifting huge loads. It applies to civil construction, metallurgical production, rivers, and seaports. The primary purpose of this paper is to control the motion/position of the overhead crane using a PID controller using Genetic Algorithms (GA) and Bee Algorithms (BA) as optimization tools. Moreover, Fuzzy Logic modified PID Controller is applied to obtain better controller parameters. The mathematical model uses an analytical method, and the PID model employs Simulink in MATLAB. The paper presents the PID parameters determination with a different approach. The development of membership functions, fuzzy rules employ the Fuzzy Logic toolbox. Both inputs and outputs use triangular membership functions. The result shows that the optimized value of the PID controller with the Ziegler-Nichols approach is time-consuming and will provide only the initial parameters. However, PID parameters obtained with the optimization method using GA and BA reached the target values. The results obtained with the fuzzy logic controller (0.227% overshoot) show improvement in overshoot than the conventional PID controller (0.271% overshoot).

[1]  A. Ferreira,et al.  3D active dynamic actuation model for offshore cranes , 2021, Comput. Aided Civ. Infrastructure Eng..

[2]  Ke Lu,et al.  Anti-swing Control Strategy Design of Container Crane Based on Fuzzy-Logic and LQR-PID Controller , 2017 .

[3]  Xiongxiong He,et al.  Partial feedback linearization control for 3-D underactuated overhead crane systems. , 2016, ISA transactions.

[4]  Soon-Geul Lee,et al.  Partial Feedback Linearization Double-loop Control for a Pseudo-2D Ridable Ballbot , 2020 .

[5]  Juing-Shian Chiou,et al.  Equivalence between Fuzzy PID Controllers and Conventional PID Controllers , 2017 .

[6]  Mustefa Jibril,et al.  Design & Control of a Gantry Crane System with Limited Payload Angle using Robust & State Feedback Controllers , 2020 .

[7]  Zhicheng Zhao,et al.  A novel anti-swing and position control method for overhead crane , 2019, Science progress.

[8]  Mahmoud Elsisi,et al.  Design of Optimal Model Predictive Controller for LFC of Nonlinear Multi-area Power System with Energy Storage Devices , 2018, Electric Power Components and Systems.

[9]  Menghua Zhang,et al.  Model-independent PD-SMC method with payload swing suppression for 3D overhead crane systems , 2019, Mechanical Systems and Signal Processing.

[10]  Arash Khatamianfar,et al.  Real-Time Robust and Optimized Control of a 3D Overhead Crane System , 2019, Sensors.

[11]  Auwalu M. Abdullahi,et al.  Control strategies for crane systems: A comprehensive review , 2017 .

[12]  Josep M. Guerrero,et al.  Energy management of controllable loads in multi-area power systems with wind power penetration based on new supervisor fuzzy nonlinear sliding mode control , 2021 .

[13]  Ming Zhang,et al.  Anti-swing control of the overhead crane system based on the harmony search radial basis function neural network algorithm , 2019 .

[14]  Mahmoud Elsisi,et al.  Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm , 2020, Int. J. Intell. Syst..

[15]  Mahmoud Elsisi,et al.  New variable structure control based on different meta‐heuristics algorithms for frequency regulation considering nonlinearities effects , 2020, International Transactions on Electrical Energy Systems.

[16]  Robert Seifried,et al.  Real-time trajectory control of an overhead crane using servo-constraints , 2017 .

[17]  Zhe Sun,et al.  An Adaptive DE Algorithm Based Fuzzy Logic Anti-swing Controller for Overhead Crane Systems , 2020, Int. J. Fuzzy Syst..

[18]  Mehmet Önder Efe,et al.  Efficient swing control of an overhead crane with simultaneous payload hoisting and external disturbances , 2020 .

[19]  Mohamed Hamdy,et al.  A hybrid partial feedback linearization and deadbeat control scheme for a nonlinear gantry crane , 2018, J. Frankl. Inst..

[20]  M. O. Tokhi,et al.  An optimal performance control scheme for a 3D crane , 2016 .

[21]  Yasutaka Tagawa,et al.  Vibration controller for overhead cranes considering limited horizontal acceleration , 2018 .

[22]  S. M. Radaideh,et al.  Fuzzy logic controller for overhead cranes , 2006 .

[23]  Jinggang Zhang,et al.  Takagi-Sugeno Fuzzy Modeling and PSO-Based Robust LQR Anti-Swing Control for Overhead Crane , 2019 .

[24]  Ho-Hoon Lee.  A new approach for the anti-swing control of overhead cranes with high-speed load hoisting , 2003 .

[25]  Guoping Wang,et al.  Dynamics analysis and fuzzy anti-swing control design of overhead crane system based on Riccati discrete time transfer matrix method , 2018 .

[26]  Bing Huang,et al.  Comparative Analysis of Neural-Network and Fuzzy Auto-Tuning Sliding Mode Controls for Overhead Cranes under Payload and Cable Variations , 2019, J. Control. Sci. Eng..