Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Research on LHD (Scraper) Path Tracking Control Based on LQR and Predict Pose Information

Version 1 : Received: 18 June 2021 / Approved: 21 June 2021 / Online: 21 June 2021 (15:28:45 CEST)

How to cite: Zhang, Y.; Zhao, C.; Wang, Z.; Yu, H. Research on LHD (Scraper) Path Tracking Control Based on LQR and Predict Pose Information. Preprints 2021, 2021060523 (doi: 10.20944/preprints202106.0523.v1). Zhang, Y.; Zhao, C.; Wang, Z.; Yu, H. Research on LHD (Scraper) Path Tracking Control Based on LQR and Predict Pose Information. Preprints 2021, 2021060523 (doi: 10.20944/preprints202106.0523.v1).

Abstract

With the depletion of shallow surface resources, the future mining work will develop towards the deep surface, and the objective conditions such as the mining environment will be more complex and dangerous than now, and the requirements for personnel and equipment will be higher and higher. The efficient exploitation of deep space cannot be separated from such mobile and flexible production and transportation equipment as scraper. In the new era, intelligence is the development trend of the LHD, and path tracking control technology is the key to the intelligent LHD, and it is also an urgent problem to be solved for its unmanned driving. This paper describes the realization of the automatic operation function of articulated LHD from two aspects of mathematical model and trajectory tracking control method, and focuses on the research of the path tracking control scheme in the field of unmanned driving, that is, LQR controller. On this basis, the parameters of the LQR controller are optimized by combining different intelligent cluster algorithms to find the optimal solution of the LQR controller.

Subject Areas

LHD (Scraper); Artificial intelligence; Path tracking; The optimal control.

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