Evidence map›Paper›PMID 31387276›Full record

ArticleSensors (Basel, Switzerland)2019

Real-Time Robust and Optimized Control of a 3D Overhead Crane System.

Arash Khatamianfar, Andrey V Savkin

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Arash KhatamianfarSchool of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW 2052, Australia.ORCID 0000-0002-6593-7502
Andrey V SavkinSchool of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW 2052, Australia. a.savkin@unsw.edu.au.ORCID 0000-0001-9390-6634

Funding

Australian Research Council DP190102501
6 · The paper itself

Abstract

A new and advanced control system for three-dimensional (3D) overhead cranes is proposed in this study using state feedback control in discrete time to deliver high performance trajectory tracking with minimum load swings in high-speed motions. By adopting the independent joint control strategy, a new and simplified model is developed where the overhead crane actuators are used to design the controller, with all the nonlinear equations of motions being viewed as disturbances affecting each actuator. A feedforward control is then designed to tackle these disturbances via computed torque control technique. A new load swing control is designed along with a new motion planning scheme to robustly minimize load swings as well as allowing fast load transportation without violating system's constraints through updating reference trolley accelerations. The stability and performance analysis of the proposed discrete-time control system are demonstrated and validated analytically and practically.

Indexed as

3D overhead cranecomputed torque controlfeedforward controlhigh-gain observers for robotic systemsmotion planningpassivity and ℒ2 stabilityposition sensorsrobot controlrobotic systems modelingtrajectory tacking

Identifiers

PMID31387276
PMCPMC6696119

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.