Robert G. Farrell, Catalina M. Danis, et al.
RecSys 2012
Stable indirect and direct adaptive controllers are presented for a class of input-output feedback linearizable time-varying non-linear systems. The radial basis function neural networks are used as on-line approximators to learn the time-varying characteristics of system parameters. Stability results are given in the paper, and the performance of the indirect and direct adaptive schemes is demonstrated through a fault-tolerant engine control problem where the faults are naturally time-varying.
Robert G. Farrell, Catalina M. Danis, et al.
RecSys 2012
Frank R. Libsch, S.C. Lien
IBM J. Res. Dev
Anupam Gupta, Viswanath Nagarajan, et al.
Operations Research
Elena Cabrio, Philipp Cimiano, et al.
CLEF 2013