Industrial & Engineering Chemistry Research
Industrial & Engineering Chemistry Research
3 years ago

A Moving Horizon Estimation Algorithm Based on Carleman Approximation: Design and Stability Analysis

A Moving Horizon Estimation Algorithm Based on Carleman Approximation: Design and Stability Analysis
Negar Hashemian, Antonios Armaou
The moving horizon estimation (MHE) method is an optimization-based technique to estimate the unmeasurable state variables of a nonlinear dynamic system with noise in transition and measurement. One of the advantages of MHE over extended Kalman filter, the alternative approach in this area, is that it considers the physical constraints in its formulation. However, to offer this feature, MHE needs to solve a constrained nonlinear dynamic optimization problem which slows down the estimation process. In this paper, we introduce and employ the Carleman approximation method in the MHE design to accelerate the solution of the optimization problem. The Carleman method approximates the nonlinear system with a polynomial system at a desired accuracy level and recasts it in a bilinear form. By making this approximation, the Karush–Kuhn–Tucker (KKT) matrix required to solve the optimization problem becomes analytically available. Additionally, we perform a stability analysis for the proposed MHE design. As a result of this analysis, we derive a criterion for choosing an order of Carleman approximation procedure that ensures convergence of the scheme. Finally, some simulation results are included that show a significant reduction in the estimation time when the proposed method is employed.

Publisher URL: http://dx.doi.org/10.1021/acs.iecr.6b03044

DOI: 10.1021/acs.iecr.6b03044

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.