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Multi-Objective Motion Control Optimization for the Bridge Crane System

Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
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Appl. Sci. 2018, 8(3), 473; https://doi.org/10.3390/app8030473
Received: 19 February 2018 / Revised: 17 March 2018 / Accepted: 19 March 2018 / Published: 20 March 2018
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Abstract

A novel control algorithm combining the linear quadratic regulator (LQR) control and trajectory planning (TP) is proposed for the control of an underactuated crane system, targeting position adjustment and swing suppression. The TP is employed to control the swing angle within certain constraints, and the LQR is applied to achieve anti-disturbance. In order to improve the accuracy of the position control, a differential-integral control loop is applied. The weighted LQR matrices representing priorities of the state variables for the bridge crane motion are searched by the multi-objective genetic algorithm (MOGA). The stability proof is provided in order to validate the effectiveness of the proposed algorithm. Numerous simulation and experimental validations justify the feasibility of the proposed method. View Full-Text
Keywords: anti-disturbance; bridge crane system; linear quadratic regulator (LQR); multi-objective genetic optimization (MOGA); trajectory planning anti-disturbance; bridge crane system; linear quadratic regulator (LQR); multi-objective genetic optimization (MOGA); trajectory planning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Xiao, R.; Wang, Z.; Guo, N.; Wu, Y.; Shen, J.; Chen, Z. Multi-Objective Motion Control Optimization for the Bridge Crane System. Appl. Sci. 2018, 8, 473.

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