Academic Journal

Challenges and Opportunities on Nonlinear State Estimation of Chemical and Biochemical Processes

التفاصيل البيبلوغرافية
العنوان: Challenges and Opportunities on Nonlinear State Estimation of Chemical and Biochemical Processes
المؤلفون: Ronald Alexander, Gilson Campani, San Dinh, Fernando V. Lima
المصدر: Processes; Volume 8; Issue 11; Pages: 1462
بيانات النشر: Multidisciplinary Digital Publishing Institute
سنة النشر: 2020
المجموعة: MDPI Open Access Publishing
مصطلحات موضوعية: state estimation, nonlinear system, extended Kalman filter, moving horizon estimation
جغرافية الموضوع: agris
الوصف: This paper provides an overview of nonlinear state estimation techniques along with a discussion on the challenges and opportunities for future work in the field. Emphasis is given on Bayesian methods such as moving horizon estimation (MHE) and extended Kalman filter (EKF). A discussion on Bayesian, deterministic, and hybrid methods is provided and examples of each of these methods are listed. An approach for nonlinear state estimation design is included to guide the selection of the nonlinear estimator by the user/practitioner. Some of the current challenges in the field are discussed involving covariance estimation, uncertainty quantification, time-scale multiplicity, bioprocess monitoring, and online implementation. A case study in which MHE and EKF are applied to a batch reactor system is addressed to highlight the challenges of these technologies in terms of performance and computational time. This case study is followed by some possible opportunities for state estimation in the future including the incorporation of more efficient optimization techniques and development of heuristics to streamline the further adoption of MHE.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
Relation: https://dx.doi.org/10.3390/pr8111462
DOI: 10.3390/pr8111462
الاتاحة: https://doi.org/10.3390/pr8111462
Rights: https://creativecommons.org/licenses/by/4.0/
رقم الانضمام: edsbas.73159B8B
قاعدة البيانات: BASE