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TECHNICAL PAPERS: Joint/Whole Body

An Intelligent Control Method Based on Fuzzy Logic for a Robotic Testing System for the Human Spine

[+] Author and Article Information
Lianfang Tian

Spine Tissue Engineering Laboratory, Musculoskeletal Research Center, Department of Orthopedic Surgery, School of Medicine,  University of Pittsburgh, Pittsburgh, PA 15213 USA

J Biomech Eng 127(5), 807-812 (May 31, 2005) (6 pages) doi:10.1115/1.1992520 History: Received April 08, 2003; Revised March 30, 2005; Accepted May 31, 2005

In previous biomechanical studies of the human spine, we implemented a hybrid controller to investigate load-displacement characteristics. We found that measurement errors in both position and force caused the controller to be less accurate than predicted. As an alternative to hybrid control, a fuzzy logic controller (FLC) has been developed and implemented in a robotic testing system for the human spine. An FLC is a real-time expert system that can emulate part of a human operator’s knowledge by using a set of action rules. The FLC provides simple but robust solutions that cover a wide range of system parameters and can cope with significant disturbances. It can be viewed as a heuristic and modular way of defining a nonlinear, table-based control system. In this study, an FLC is developed which uses the force difference and the change in force difference as the input parameters, and the displacement as the output parameter. A rule-table based on these parameters is designed for the controller. Experiments on a physical model composed of springs demonstrate the improved performance of the proposed method.

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Copyright © 2005 by American Society of Mechanical Engineers
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Figures

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Figure 1

(Color online) Computer-controlled robotic testing system.

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Figure 2

(Color online) Block diagram of the robotic testing system.

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Figure 3

(Color online) Architecture of the fuzzy logic controller.

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Figure 4

(Color online) Membership function of the normalized fuzzy sets associated with NE.

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Figure 5

Comparison between the hybrid controller and the FLC.

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Figure 6

(Color online) The process of force minimization. The mark ★ is the initial force after each rotation increment, the mark  ☆  is the final force after minimization, the minimization process is from mark ★ to mark  ☆  for each rotation increment. — ★ — ★ —represents the minimized force for each rotation increment and ☆ represents the path to minimize the produced force in one rotation increment. (a) z direction. (b) y direction.

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Figure 7

(Color online) Controller iterations for each rotation increment.

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Figure 8

(Color online) The total work done in the force minimization process.

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