Title :
A Neural Network-based Learning Controller for Micro-sized Object Micromanipulation
Author :
Shahini, Mohsen ; Melek, William W. ; Yeow, John T W
Author_Institution :
Waterloo Univ., Waterloo
Abstract :
In this paper, automated micro-sized objects manipulation is investigated. The novelty of the proposed method lies on the compensation of all the nonlinear scaling forces which are dominant over gravitational force. A dynamic neural network has been added to a PD conventional controller for automated micromanipulation control. Weight-updating rules have been obtained in such a way that the system is uniformly ultimately bounded (UUB) in the sense of Lyapunov. Simulation results for controlled pushing of a micro-object have been illustrated and the efficiency of the method has been shown by comparing its result with that of a linear controller.
Keywords :
Lyapunov methods; PD control; compensation; force control; intelligent robots; learning systems; micromanipulators; neurocontrollers; nonlinear control systems; Lyapunov function; PD controller; dynamic neural network; gravitational force; learning controller; microsized object micromanipulation; nonlinear scaling forces compensation; pushing control; weight-updating rules; Artificial neural networks; Automatic control; Electronic mail; Gravity; Insects; Intelligent robots; Mechanical engineering; Neural networks; Nonlinear dynamical systems; PD control;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371444
