TY - GEN
T1 - Control of nonlinear dynamic systems using neural networks with incremental learning
AU - Moran, Antonio
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/13
Y1 - 2018/6/13
N2 - Nonlinear dynamic systems present complex behavior that is not easy to control using conventional techniques. Even more, neural networks cannot always be trained in a straightforward learning scheme for solving dynamic control problems. This paper proposes incremental learning methods for training neural networks for the control of nonlinear dynamic systems using the Dynamic Back Propagation algorithm. By analyzing the complexity of the control problem, learning strategies are formulated in an incremental scheme similar to human learning: starting from easy and simple tasks and continuing with increasingly complex and difficult tasks. The results obtained in the control of highly unstable nonlinear systems, and the positioning control of mobile robots verify the effectiveness of the proposed incremental learning strategies.
AB - Nonlinear dynamic systems present complex behavior that is not easy to control using conventional techniques. Even more, neural networks cannot always be trained in a straightforward learning scheme for solving dynamic control problems. This paper proposes incremental learning methods for training neural networks for the control of nonlinear dynamic systems using the Dynamic Back Propagation algorithm. By analyzing the complexity of the control problem, learning strategies are formulated in an incremental scheme similar to human learning: starting from easy and simple tasks and continuing with increasingly complex and difficult tasks. The results obtained in the control of highly unstable nonlinear systems, and the positioning control of mobile robots verify the effectiveness of the proposed incremental learning strategies.
KW - dynamic back propagation
KW - incremental learning
KW - mobile robots
KW - neuro-control
KW - recurrent neural networks
UR - http://www.scopus.com/inward/record.url?scp=85049917986&partnerID=8YFLogxK
U2 - 10.1109/ICCAR.2018.8384667
DO - 10.1109/ICCAR.2018.8384667
M3 - Conference contribution
AN - SCOPUS:85049917986
T3 - Proceedings - 2018 4th International Conference on Control, Automation and Robotics, ICCAR 2018
SP - 182
EP - 189
BT - Proceedings - 2018 4th International Conference on Control, Automation and Robotics, ICCAR 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Control, Automation and Robotics, ICCAR 2018
Y2 - 20 April 2018 through 23 April 2018
ER -