Proportional–integral-derivative controller with inlet derivative filter fine-tuning of a double-pendulum gantry crane system by a multi-objective genetic algorithm. Issue 3 (3rd March 2020)

• Record Type: Journal Article
• Authors: Abdel-razak, Mahmoud H.; Ata, Atef A.; Mohamed, Khaled T.; Haraz, Eman H.
• Is Part Of: Engineering optimization. Volume 52:Issue 3(2020)
• Page Start: 527
• Page End: 548
• Publication Date: 2020-03-03
• Subjects: optimal Pareto solutions -- PID controller -- multi-objective genetic algorithm (NSGA-II) -- optimization -- gantry crane system; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2019.1603300
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: Overhead cranes are widely used in industry to move extremely heavy and bulky loads through the overhead space in a facility instead of through aisles or on the floor. Unfortunately, the natural sway of a crane's payload is a huge safety problem which needs more research by control engineers, as the sway of the payload affects both the safety and productivity of a factory. This article introduces an optimized mathematical model of a double-pendulum overhead crane with control schemes: scheme 1 uses three proportional -integral-derivative (PID) controllers with inlet derivative filters; scheme 2 uses one PID controller for accurate trolley positioning and two anti-swing proportional -derivative controllers to eliminate hooks and payload sway, all with inlet derivative filters. The controllers include up to nine gains which are tuned using the multi-objective non-dominated sorting genetic algorithm-II with five fitness functions and weighted function to choose a suitable solution from Pareto solutions.