|제목(국문)||비선형 시스템의 상태변수 추정기법 동향|
|제목(영문)||A Survey on State Estimation of Nonlinear Systems|
,Chemical & Biomolecular Engineering, Korea Advanced Institute of Science and Technology
최수항 (Su-hang Choi ,Chemical & Biomolecular Engineering, Korea Advanced Institute of Science and Technology ) ▷공저자네트워크등록하기
이재형 (Lee, Jae-Hyung ,기초과학지원연구소 연구원 ) ▷공저자네트워크등록하기
This article reviews various state estimation methods for nonlinear systems, particularly with a perspective of a process control engineer. Nonlinear state estimation methods can be classified into the following two categories: stochastic approaches and deterministic approaches. The current review compares the Bayesian approach, which is mainly a stochastic approach, and the MHE (Moving Horizon Estimation) approach, which is mainly a deterministic approach. Though both methods are reviewed, emphasis is given to the latter as it is particularly well-suited to highly nonlinear systems with slow sampling rates, which are common in chemical process applications. Recent developments in underlying theories and supporting numerical algorithms for MHE are reviewed. Thanks to these developments，applications to large-scale and complex chemical processes are beginning to show up but they are still limited at this point owing to the high numerical complexity of the method.
|keyword||review, state estimation method, nonlinear system, optimization approach, bayesian approach|