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).

Automated summary

This paper aims to improve the motion/position control of overhead cranes using a PID controller combined with optimization methods such as Genetic Algorithms and Bee Algorithms, as well as a Fuzzy Logic modified PID controller. The results show that the optimized PID parameters obtained using GA and BA reach the target values, and the fuzzy logic controller outperforms the conventional PID controller in terms of overshoot reduction.