NDLI: A fuzzy-behavior-based approach for controlling mining excavator bucket/rock interactions

Content Provider	IEEE Xplore Digital Library
Author	Lever, P.J.A. Fei-Yue Wang Xiaobo Shi Deqian Chen
Copyright Year	1994
Description	Author affiliation: Dept. of Min. & Geol. Eng., Arizona Univ., Tucson, AZ, USA (Lever, P.J.A.)
Abstract	Successful control of an autonomous mining excavator requires sensor feedback from the excavation tool to control unpredictable tool/rock interactions. Conventional control approaches cannot deal effectively with uncertainties in the dynamic and unstructured mining environment. This paper presents a new intelligent control approach that utilizes fuzzy behaviors with fuzzy strategies to control bucket motions for autonomous excavation tasks. In this approach, the control system uses feedback from a bucket mounted force/torque sensor to control excavation motions by sensing and reacting to interactions with rock particles during excavation. A behaviour coordination configuration is developed to improve the controllers effectiveness in reaching its overall excavation goals. It uses fuzzy logic rules to adjust control system output variables and performs goal-driven behaviour selection. This technique is a first step towards realistic control of complex machine/environment interactions in difficult and unpredictable environments, where traditional control approaches are either impossible or computationally excessive. The discussion here focuses on: (a) development of a new control architecture; (b) the individual components of the architecture; and (c) experiments with a simulated excavator using a PUMA 560 robotic arm.<>
Starting Page	2126
Ending Page	2133
File Size	934216
Page Count	8
File Format	PDF
ISBN	0780319931
DOI	10.1109/IAS.1994.377724
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-10-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy control Uncertainty Torque control Force feedback Computer architecture Control systems Motion control Force control Intelligent sensors Intelligent control
Content Type	Text
Resource Type	Article

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