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A Novel Approach Using a Neural Network Based Adaptive Filter for Performing Real-Time, On-line Qualitative System Design

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Pp. 288-296 in Automation Technology for Off-Road Equipment, Proceedings of the July 26-27, 2002 Conference (Chicago, Illinois, USA)  701P0502.(doi:10.13031/2013.10018)
Authors:   William R. Norris, Ramavarapu Sreenivas, Qin Zhang
Keywords:   Automatic Steering Control and Guidance, Controllers, Decision Making, Off Road Vehicles, Electro-Hydraulics, Neural Networks, Software Support for Vehicle Automation

The objective of this paper is to demonstrate the development of a tool used in a design framework for performing real time human-in-the-loop system design using virtual environments. The design framework, known as virtual design tools, requires a component that performs on-line adaptation of a design based on human operator performance characteristics. The on-line adaptive component was successfully applied to a four degree of freedom articulated wheel loader electrohydraulic steering design problem. A parameterized input to output map, known as a virtual modulation curve (VMC), with boundary conditions, was introduced as a novel adaptive component between the operator’s control signal and the electrohydraulic system. One possible application was explored involving the application of a neural network emulator that predicted future position and orientation errors, a parabolic minimization function, and an averaging filter, the performance of a consistent operator model was improved significantly while operating under real time constraints. The success of this technique demonstrates that it is applicable to a wide range of human-in-the-loop problems.

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