TY - GEN
T1 - Integral reinforcement learning with explorations for continuous-time nonlinear systems
AU - Lee, Jae Young
AU - Park, Jin Bae
AU - Choi, Yoon Ho
PY - 2012
Y1 - 2012
N2 - This paper focuses on the integral reinforcement learning (I-RL) for input-affine continuous-time (CT) nonlinear systems where a known time-varying signal called an exploration is injected through the control input. First, we propose a modified I-RL method which effectively eliminates the effects of the explorations on the algorithm. Next, based on the result, an actor-critic I-RL technique is presented for the same nonlinear systems with completely unknown dynamics. Finally, the least-squares implementation method with the exact parameterizations is presented for each proposed one which can be solved under the given persistently exciting (PE) conditions. A simulation example is given to verify the effectiveness of the proposed methods.
AB - This paper focuses on the integral reinforcement learning (I-RL) for input-affine continuous-time (CT) nonlinear systems where a known time-varying signal called an exploration is injected through the control input. First, we propose a modified I-RL method which effectively eliminates the effects of the explorations on the algorithm. Next, based on the result, an actor-critic I-RL technique is presented for the same nonlinear systems with completely unknown dynamics. Finally, the least-squares implementation method with the exact parameterizations is presented for each proposed one which can be solved under the given persistently exciting (PE) conditions. A simulation example is given to verify the effectiveness of the proposed methods.
UR - http://www.scopus.com/inward/record.url?scp=84865092901&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84865092901&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2012.6252508
DO - 10.1109/IJCNN.2012.6252508
M3 - Conference contribution
AN - SCOPUS:84865092901
SN - 9781467314909
T3 - Proceedings of the International Joint Conference on Neural Networks
BT - 2012 International Joint Conference on Neural Networks, IJCNN 2012
T2 - 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
Y2 - 10 June 2012 through 15 June 2012
ER -