Design of Database-Driven Model Predictive Control System for Digging of an Autonomous Excavator

Transactions of the Institute of Systems, Control and Information Engineers Pub Date : 2022-06-15 DOI:10.5687/iscie.35.145

Tomofumi Okada, Toru Yamamoto, Takayuki Doi, K. Koiwai, K. Yamashita

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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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自主挖掘机挖掘数据库驱动模型预测控制系统设计

以提高生产力和改革工作方式为目的的数字化转型(DX)倡议在建筑行业中越来越活跃。特别是自主施工机械的研究和开发，旨在通过自主施工提高生产率。另一方面，作者开发了基于数据库驱动建模的自主挖掘机内模控制(IMC)系统。然而，由于控制目标特性的突然变化，该控制系统的控制性能可能会下降。此外，由于执行器等硬件的限制，控制系统不能明确地处理约束。本文提出了一种数据库驱动模型预测控制(DD-MPC)系统的控制方法，该方法在控制目标属性变化时具有良好的控制性能，并对约束进行了明确的处理。数值仿真和遥控挖掘机实验验证了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Transactions of the Institute of Systems, Control and Information Engineers

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