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

Abstract

ABSTRACTOverhead 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.