이산형 시스템에서의 최소차수의 관측자를 이용한 최적 레귤레이터의 개발
 Alternative Title
 A Design for ReducedOrder Observer Based Optimal Regulator in the Discrete System
 Abstract
 지금까지 단지 제한된 출력 즉 측정된 출력 값만을 사용하여 원하는 목표치에 도달하도록 하는 제어 문제를 푸는 데 많은 연구가 진행되어 왔다. 차수가 줄여진 필터 알고리즘은 백색 잡음에 의하여 영향을 받은 선형 시스템의 상태를 추정하기 위하여 개발되었다. 추정자는 상태의 무편향성을 가정하고 또 추정자의 편차는 관측자 및 추정상태와 공통되는 상태의 모든 관측의 subspace에 수직이 된다. 특히 reducedorder에서의 필터 성능은 fullorder에서의 필터 성능에 대해 suboptimal 이지만 상응한 Riccati equation을 푸는데 계산시간을 줄이고 memory를 덜 소요하는 이점이 있다. 본 논문에서는 Kronecker Algebra와 선택행렬을 이용하여 Non Linear Two Point Boundary Value Problem을 Linear Two Point Boundary Value Problem 으로 변환시켜 부수적으로 수반되는 algebraic Riccati equation을 유도함으로써 문제를 쉽게 해결할 수 있다.
Researchers are often in solving control problems which are constrained to use only the available outputs. Unfortunately the desing of such controllers ofthen leads to a difficult Non Linear Two Point Boundary Value Problem. A reducedorder filter algorithm is developed for estimation of the complementary states of a linear system driven by white noise. The estimator gives an unbiased estimate of those states that are common to the observations and the estimated states. The filter performance is suboptimal relative to the fullorder optimal linear filter, but benefits are reaped from computational savings in the filtering and assocated Riccati equation. In this paper we are able to avoid such a design difficulty by solving the algebraic Riccati equation which is produced by converting a Non Linear Two Point Boundary Value Problem to Linear Two Point Boundary Value Problem with selecting matrix and Kronecker algebra. This paper extends the continuous version of feedforward gain control considered in ［2］ to a discrete setting.
Researchers are often in solving control problems which are constrained to use only the available outputs. Unfortunately the desing of such controllers ofthen leads to a difficult Non Linear Two Point Boundary Value Problem. A reducedorder filter algorithm is developed for estimation of the complementary states of a linear system driven by white noise. The estimator gives an unbiased estimate of those states that are common to the observations and the estimated states. The filter performance is suboptimal relative to the fullorder optimal linear filter, but benefits are reaped from computational savings in the filtering and assocated Riccati equation. In this paper we are able to avoid such a design difficulty by solving the algebraic Riccati equation which is produced by converting a Non Linear Two Point Boundary Value Problem to Linear Two Point Boundary Value Problem with selecting matrix and Kronecker algebra. This paper extends the continuous version of feedforward gain control considered in ［2］ to a discrete setting.
 Author(s)
 김한실
 Issued Date
 1998
 Type
 Research Laboratory
 URI
 https://oak.ulsan.ac.kr/handle/2021.oak/3913
http://ulsan.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002024604
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