Remarks on an adaptive type self-tuning controller using neural networks
- 9 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1389-1394
- https://doi.org/10.1109/iecon.1991.239065
Abstract
The authors propose an adaptive type of self-tuning controller which offers the possibility of enhanced robustness. This controller does not use a desired feedback gain predetermined by conventional control theories as a teaching signal. Simulated results using a second-order plant show the nonlinear neural network effect for the nonlinear plant. They also show that a controller using a linear neural network is better than one using a nonlinear neural network in the region of small nonlinear and parasite terms. Experimental results using a force confirmed that the controller is useful for an actual system.<>Keywords
This publication has 8 references indexed in Scilit:
- On the characteristics of the robot manipulator controller using neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Possibility of neural networks controller for robot manipulatorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- An extension of neural network direct controllerPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Some Remarks on Characteristics of Direct Neuro-Controller with Regard to Adaptive ControlTransactions of the Society of Instrument and Control Engineers, 1991
- Approximate realization of identity mappings by three‐layer neural networksElectronics and Communications in Japan (Part III: Fundamental Electronic Science), 1990
- Force control of robot manipulator by neural network. (Control of one degree-of-freedom manipulator).Journal of the Robotics Society of Japan, 1989
- Generic constraints on underspecified target trajectoriesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989
- A multilayered neural network controllerIEEE Control Systems Magazine, 1988