Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
Special Issue Paper
Design of Database-Driven Model Predictive Control System for Digging of an Autonomous Excavator
Tomofumi OkadaToru YamamotoTakayuki DoiKazushige KoiwaiKoji Yamashita
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2022 Volume 35 Issue 6 Pages 145-152

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Abstract

The initiative of Digital Transformation (DX) for the purpose of productivity improvement and reforming work style has been more and more active in the construction industry. In particular, research and development of autonomous construction machinery has been carried out with the aim of improving productivity through autonomous construction. On the other hand, Internal Model Control (IMC) system based on Database-Driven Modeling for an autonomous excavator is developed by authors. However, the control performance of this control system may deteriorate by the sudden change of the control target property. In addition, the control system can't deal with constraints explicitly in the case of the limitation of the hardware such as actuators. This paper presents a method of Database-Driven Model Predictive Control (DD-MPC) system which has also good control performance during the change of the control target property and deals with constraints explicitly. The effectiveness of the proposed method is verified by the numerical simulations and the experiment using a radio-controlled (RC) excavator.

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© 2022 The Institute of Systems, Control and Information Engineers
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