Improved Kalman-Filter-Based Model-Predictive Control Method for Trajectory Tracking of Automatic Straddle Carriers
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Published:2023-05-01
Issue:5
Volume:14
Page:118
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ISSN:2032-6653
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Container-title:World Electric Vehicle Journal
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language:en
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Short-container-title:WEVJ
Author:
Ding Zonghe1, Lin Shuang1, Gu Wei1, Zhang Yilian1
Affiliation:
1. Key Laboratory of Marine Technology and Control Engineering Ministry of Communications, Shanghai Maritime University, Shanghai 201306, China
Abstract
This paper considers the trajectory tracking problem for a class of automatic straddle carriers (ASCs) with external interferences and the overturning constraints. First, the steering and the dynamics of the ASC are analyzed and the mathematical model of the ASC is established. Then, considering the impact of external interferences on the trajectory tracking accuracy, an improved dynamic Kalman filter is designed in order to obtain the state estimation of the ASC. Based on the obtained state estimation, a model-predictive control method is proposed which takes the anti-overturning constraints into account. In addition, the improved Kalman-filter-based model-predictive control (iKFMPC) algorithm is summarized for the considered ASC to travel smoothly along the given trajectory while meeting the overturning resistance. Finally, simulation analyses demonstrate the effectiveness and superiority of the proposed method.
Funder
Shanghai Municipal Commission of Science and Technology National Natural Science Foundation of China
Subject
Automotive Engineering
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