Adaptive dynamic programming as a theory of sensorimotor control

Author

Yu Jiang ; Zhong-Ping Jiang

Author_Institution

Dept. of Electr. & Comput. Eng., Polytech. Inst. of New York Univ., Brooklyn, NY, USA

fYear

2012

fDate

1-1 Dec. 2012

Firstpage

1

Lastpage

4

Abstract

This paper studies the control mechanism in human arm movements from a perspective of approximate/adaptive dynamic programming (ADP). The control scheme is developed by incorporating Itô calculus with the ADP method for continuous-time stochastic linear systems. An online learning technique is presented to find a robust optimal control policy without knowing the system dynamics. Finally, the proposed method is applied to a single-joint movement control problem and is validated by computer simulations.

Keywords

approximation theory; biomechanics; calculus; continuous time systems; dynamic programming; learning systems; medical control systems; motion control; optimal control; stochastic systems; Itô calculus; approximate-adaptive dynamic programming; computer simulations; continuous-time stochastic linear systems; control mechanism; human arm movements; online learning technique; robust optimal control policy; sensorimotor control; single-joint movement control problem; Adaptation models; Brain models; Humans; Noise; Optimal control; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing in Medicine and Biology Symposium (SPMB), 2012 IEEE

Conference_Location

New York, NY

Print_ISBN

978-1-4673-5665-7

Type

conf

DOI

10.1109/SPMB.2012.6469455

Filename

6469455