Optimal Experiment Design for Identifying Dynamical Takagi-Sugeno Models with Minimal Parameter Uncertainty
Optimal Experiment Design for Identifying Dynamical Takagi-Sugeno Models with Minimal Parameter Uncertainty is a scholarly work, published in 2018 in ''IFAC Proceedings Volumes''. The main subjects of the publication include computer science, uncertainty quantification, mathematical optimization, fault detection and isolation, particle filter, mathematics, and control theory. The general functionality of the presented method is demonstrated on a case study.