Proportional–integral-derivative controller with inlet derivative filter fine-tuning of a double-pendulum gantry crane system by a multi-objective genetic algorithm

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.

KEYWORDS:

• optimal Pareto solutions
• PID controller
• multi-objective genetic algorithm (NSGA-II)
• optimization
• gantry crane system

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Atef A. Ata http://orcid.org/0000-0001-7802-8466

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.