Vision-based Fuzzy Proportional–Integral–Derivative Tracking Control Scheme for Gantry Crane System

Feijie Zheng,Gao Hao,Hai-Lian Hong,Kun-Chieh Wang,Chi-Hsin Yang

doi:10.18494/sam.2021.3403

Abstract

Vision-based Fuzzy Proportional–Integral–Derivative Tracking Control Scheme for Gantry Crane System

Highlights

Gantry crane systems have been widely used in container lifting, ship equipment transportation, hydropower stations, thermal power plants, and other industrial operations.[1]. Because of their wide operating range and the ability to lift heavy loads, gantry crane systems are usually applied to improve the efficiency of work, reduce physical labor, and ensure safety in production.[2] the safety and operational efficiency of a gantry crane system are affected by the hoisting of loads and the swing of the cable under external interferences.[3]. Gantry crane systems often rely on experienced operators to position the crane and perform antiswing measures
Fuzzy control scheme is that the controlled system is handled by a similar type of decisionmaking to that of humans owing to the elimination of detailed mathematical models.[18,19] by adding an extra layer of intelligence, a fuzzy control scheme can be combined with PID control to realize more useful and practical control schemes, such as fuzzy adaptive PID (FAPID) control[20] and variable universe fuzzy adaptive PID (VUFAPID)(21–24) control
Regarding the control of gantry crane systems in the literature, in Ref. 25, an intelligent control scheme combined with root locus and frequency domain methods was proposed for positioning and anti-swing control

Summary

Introduction

Gantry crane systems have been widely used in container lifting, ship equipment transportation, hydropower stations, thermal power plants, and other industrial operations.[1]. In Ref. 16, the use of vision-based control to extract both the trolley position and the load swing information for the effective tracking control of the gantry crane was demonstrated. The sensing system is combined with a vision system for detecting the position of the trolley and the length of the cable, and an angular sensor for measuring the swing angle of the load to sense the states of the 2DOF gantry crane. The dynamical equations of the 2DOF gantry crane model are derived using Lagrangian formalism by defining the generalized coordinates, such as the horizontal position of the trolley, q1, the length of the cable, q2, and the swing angle of the lifting load, η.(29) The following equations hold:. The control goal is to design the appropriate control inputs, u1 and u2, such that lim t→∞

Design of Four Types of Control

Experimental Results

Conclusion