Constrained Nonlinear State Estimation --- A Differential Evolution Based Moving Horizon Approach

  • Authors:

  • Yudong Wang;Jingchun Wang;Bo Liu

  • Affiliations:

  • Department of Automation, Tsinghua University, Beijing,100084, China;Department of Automation, Tsinghua University, Beijing,100084, China;Department of Automation, Tsinghua University, Beijing,100084, China

  • Venue:
  • ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
  • Year:
  • 2009

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Abstract

A solution is proposed to estimate the states in the nonlinear discrete time system. Moving Horizon Estimation (MHE) is used to obtain the approximated states by minimizing a criterion that is the Euclidean form of the difference between the estimated outputs and the measured ones over a finite time horizon. The differential evolution (DE) algorithm is incorporated into the implementation of MHE in order to solve the optimization problem which is presented as a nonlinear programming problem due to the constraints. The effectiveness of the approach is illustrated in simulated systems that have appeared in the moving horizon estimation literature.