Introducing MIT Rule Toward Improvement of Adaptive Mechanical Prosthetic Arm Control Model
The article represents MRAC strategies for controlling a mechanical prosthetic arm utilizing gradient method MIT rule. Depending on the uncertainty parameters like mass of the mechanical arm, friction constant and spring constant, an adaptive controller is designed and outlined. MIT rule has been applied to this second-order system, and simulation is done in MATLAB-Simulink for various estimation of adaptation gain. With the changes in adaptation gain, the adaptation mechanisms are changed and results are analyzed. Variation in the parameters should be in the specified range for MIT rule. Further Lyapunov stability approach has been applied to the closed-loop dynamics to ensure global stability on variation of plant parameters.
KeywordsProsthetic arm Model reference adaptive control Gradient method MIT rule Lyapunov rule
Authors are grateful to TEQIP-II Scheme of JIS College of Engineering for funding this research.
- 1.P.M. Rossini et.al., The Italian Tribune Newspaper, July 21, 2010. http://theitaliantribune.com/?p=119.
- 2.Neogi B., Ghosal S., Ghosh S., Bose T.K., Das. A., “Dynamic modeling and optimizations of mechanical prosthetic arm by simulation technique” Recent Advances in Information Technology (RAIT), IEEE Xplore, pp. 883–888, March 2012.Google Scholar
- 3.Astrom, K.J., and B. Wittenmark; Adaptive control; 2nd Edition: Prentice-Hall, 1994.Google Scholar
- 4.S. Coman, and Cr. Boldisor, “Adaptive PI controller design to control a mass-damper-spring process.” Bulletin of the Transilvania University of Braşov • Series I • Vol. 7 (56) No. 2 – 2014.Google Scholar