Several extensions in methods for adaptive output feedback control.
Several extensions to neural network (NN)-based adaptive output feedback control of nonlinear systems are developed. An extension from linearly to nonlinearly parameterized NNs is given for a direct adaptive output feedback approach. An extension that permits the introduction of e-modification in both the direct adaptive approach and an error-observer-based approach is also given. Finally, for the case of nonaffine systems, we eliminate a fixed-point assumption that has appeared in earlier work.
Kim
Nakwan
N
Department of Aerospace Engineering, Chungnam National University, Daejeon 305-764, South Korea. nkim@cnu.ac.kr
Calise
Anthony J
AJ
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D005246:Feedback; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*