Learning control of an inverted pendulum using neural networks
- 24 August 2005
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2734-2739
- https://doi.org/10.1109/cdc.1992.371321
Abstract
Several problems in control using neural networks are pointed out, and a method for using some knowledge about the properties of the controlled object is indicated. As an example, a hierarchical control system of an inverted pendulum using a neural network is proposed. The controller consists of a pendulum part driven by the neural network and a cart part generating the virtual signal. As a result, the neurocontroller can be constructed easily and can be learned rapidly. The effectiveness of the control system has been confirmed by simulation and experimental results.<>Keywords
This publication has 5 references indexed in Scilit:
- Learning control of an inverted pendulum using neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Learning control of an inverted pendulum using a neural networkPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Alternative Approaches for Fuzzyness : Focussed on Measurement and Control EngineeringJournal of Japan Society for Fuzzy Theory and Systems, 1991
- Learning Control for Stabilization of an Inverted Pendulum Using a Multi-layered Neural NetworkTransactions of the Institute of Systems, Control and Information Engineers, 1990
- Learning to control an inverted pendulum using neural networksIEEE Control Systems Magazine, 1989