Title :
PDF control of tracking error of robotic systems with any bounded stochastic disturbances
Author :
Chen, Haiyong ; He, Guanchen ; Xing, Jia ; Wang, Hong ; Chen, Lingling
Author_Institution :
Dept. of Autom., Hebei Univ. of Technol., Tianjin
Abstract :
In this paper, the probability density function (PDF) control strategy has been employed to drive the PDF of the random tracking error for a class of robotic manipulator to approach the desired PDF, where the tracking error may be subjected to noises that follow non-Gaussian probability distribution. The ILC frame about PDF control approach has been proposed and a recursive optimization solution of parameters tuning batch-by-batch has also been given. Then, the convergence condition of the recursive optimization algorithm has been analyzed. Finally, a simulation shows the efficiency of the proposed scheme.
Keywords :
manipulators; optimisation; recursive estimation; nonGaussian probability distribution; probability density function control strategy; random tracking error; recursive optimization algorithm; robotic manipulator; Algorithm design and analysis; Control systems; Drives; Error correction; Manipulators; Probability density function; Probability distribution; Robots; Stochastic resonance; Stochastic systems; iterative learning control; probability density function control; stochastic control; stochastic optimization;
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
DOI :
10.1109/ICIEA.2009.5138472
