DocumentCode :
358957
Title :
Observer-based backstepping control using online approximation
Author :
Choi, Jin Young ; Farrell, Jay
Author_Institution :
Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
Volume :
5
fYear :
2000
fDate :
2000
Firstpage :
3646
Abstract :
This paper extends the applications of neurocontrol approaches to a new class of nonlinear systems diffeomorphic to output feedback nonlinear systems with unmeasured states. A neural-based adaptive observer is introduced for state estimation as well as system identification using only output measurements during online operation. The controller is designed by using the backstepping control design procedure. Nonlinear damping terms are introduced to prevent the instability arising from the state estimation error. The stability analysis for the proposed approach is provided, and the feasibility is investigated by an illustrative example through a numerical simulation
Keywords :
adaptive control; control system synthesis; feedback; neurocontrollers; nonlinear systems; observers; stability; adaptive control; identification; neural networks; neurocontrol; nonlinear systems; observer; online approximation; output feedback; stability; state estimation; Backstepping; Control design; Damping; Nonlinear systems; Numerical simulation; Observers; Output feedback; Stability analysis; State estimation; System identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2000. Proceedings of the 2000
Conference_Location :
Chicago, IL
ISSN :
0743-1619
Print_ISBN :
0-7803-5519-9
Type :
conf
DOI :
10.1109/ACC.2000.879250
Filename :
879250
Link To Document :
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