Integration of Artificial Neural Networks and Linear Systems for the Output Feedback Control of Nonlinear Vibration Systems
2014 (English)In: CCC 2014, the 33rd Chinese Control Conference, IEEE Press, 2014, 1850-1855 p.Conference paper (Refereed)
This paper analyzes the integration of neural networks and linear systems for the identification, state estimation and output feedback control of weakly nonlinear systems. Considering previous knowledge about the system given by approximated linear state-space models, linear observers and linear controllers, training algorithms for the neuro-identification, state neuro-estimation and output feedback neuro-control were derived considering the dynamics of the nonlinear system. It was found that the integrated linear-neuro model can identify the dynamics of the system much more accurately than a purely linear model or a purely neuro model. It was also found that the state estimation and vibration isolation performance of the system with integrated linear-neuro output feedback control is better than the system with linear control or neuro-control.
Place, publisher, year, edition, pages
IEEE Press, 2014. 1850-1855 p.
Artificial Neural Networks, Linear Systems, Control Theory, Neuro-Control
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-111007DOI: 10.1109/ChiCC.2014.6896911OAI: oai:DiVA.org:su-111007DiVA: diva2:773781
CCC 2014, the 33rd Chinese Control Conference,28-30 July 2014, Nanjing