Skip Nav Destination
ASME Press Select Proceedings
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
By
ISBN:
9780791859902
No. of Pages:
1400
Publisher:
ASME Press
Publication date:
2011
eBook Chapter
319 Design of Hopfield Neural Network Controller for an Inchworm Miniature Robot Locomotion
By
Lianzhi Yu
,
Lianzhi Yu
College of Optoelectric Information and Computer Engineering,
University of Shanghai for Science and Technology
, Shanghai, 200093
, P.R. China
; [email protected]
Search for other works by this author on:
Zhouying Hu
Zhouying Hu
College of Optoelectric Information and Computer Engineering,
University of Shanghai for Science and Technology
, Shanghai, 200093
, P.R. China
; [email protected]
Search for other works by this author on:
Page Count:
4
-
Published:2011
Citation
Yu, L, & Hu, Z. "Design of Hopfield Neural Network Controller for an Inchworm Miniature Robot Locomotion." International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011). Ed. Ming, C. ASME Press, 2011.
Download citation file:
This paper described the structure of a flexible miniature robotic system which can move in small pipes, it makes inchworm-like movement driven by a 3-DOF pneumatic rubber actuator and holds its positions by air chambers, the mechanics and the moving modes of the robot were analyzed, and according to the inchworm locomotive modes and time control orders in one cycle, the Hopfield neural network model was designed for the control of robot locomotion. Results prove the Hopfield neural network controller has good control performance for the robot locomotion process.
Abstract
Keywords:
Introduction
Robot System
Hopfield Neural Network Controller for Inchworm Robot Locomotion
Conclusion
Acknowledgments
References
This content is only available via PDF.
You do not currently have access to this chapter.
Email alerts
Related Chapters
Designing an Artificial Muscle Based on PID Controller and Tuned by Neural Network with a NN Identification of the Plant
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
A Novel Approach for LFC and AVR of an Autonomous Power Generating System
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
A Semi-Adaptive Fractional Order PID Control Strategy for a Certain Gun Control Equipment
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Estimating Resilient Modulus Using Neural Network Models
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Related Articles
Optimizing 3D Laser Foil Printing Parameters for AA 6061: Numerical and Experimental Analysis
J. Manuf. Sci. Eng (March,2025)
Motion Characteristic Analysis of a Floating Structure in the South China Sea Based on Prototype Monitoring
J. Offshore Mech. Arct. Eng (April,2019)