국내 최대 기계 및 로봇 연구정보

기술보고서

기술보고서 게시판 내용
타이틀	IDENTIFICATION OF DYNAMIC SYSTEMS, THEORY AND FORMULATION
저자	R. E. Maine and K. W. Iliff
Keyword	Maximum likelihood estimates; Optimization; Parameter identification; Probability theory; System identification.
URL	http://www.dfrc.nasa.gov/DTRS/1985/PDF/H-1255.pdf
보고서번호	NASA-RP-1138
발행년도	1985
출처	NASA Dryden Flight Research Center
ABSTRACT	The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.