Title :
Predictive control with neural network model for flexible link robot
Author :
Shipitko, Ilya A. ; Zmeu, Konstantin V.
Author_Institution :
Far Eastern State Tech. Univ., Vladivostok, Russia
Abstract :
This paper proposes the use of predictive control systems coupled with artificial neural networks (ANN) to control the dynamic behavior of a single-link flexible manipulator rotating in a horizontal plane. For systems with unessential nonlinearity and without non-minimum phase properties, it is quite enough to use one-step ahead predictive models to achieve efficient control, although they do not ensure sufficient robustness. For systems with more complicated dynamics, the application of extended predictive control algorithms with neural network model is desirable.
Keywords :
flexible manipulators; neurocontrollers; nonlinear control systems; position control; predictive control; stability; artificial neural network model; dynamic behavior; flexible link robot manipulator; nonlinear system control; position control; predictive control systems; robustness; Artificial neural networks; Control systems; Manipulator dynamics; Neural networks; Nonlinear control systems; Prediction algorithms; Predictive control; Predictive models; Robots; Robust control;
Conference_Titel :
Modern Techniques and Technologies, 2003. MTT 2003. Proceedings of the 9th International Scientific and Practical Conference of Students, Post-graduates and Young Scientists
Conference_Location :
Tomsk
Print_ISBN :
0-7803-7669-2
DOI :
10.1109/SPCMTT.2003.1438151