Weighted Recursive Least Square for Parameter Identification of Nonlinear Wiener–Hammerstein Systems

Ruiguang Lan; Xuemei Ren; Linwei Li

doi:10.1007/978-981-16-6328-4_47

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Weighted Recursive Least Square for Parameter Identification of Nonlinear Wiener–Hammerstein Systems

Ruiguang Lan Xuemei Ren Linwei Li

Year: 2021 Lecture notes in electrical engineering Pages: 447-455 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-16-6328-4_47

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Keywords:

Nonlinear system Parametric statistics Mathematics Square (algebra) Control theory (sociology) System identification Function (biology) Applied mathematics Term (time) Identification (biology) MATLAB Mathematical optimization Computer science Measure (data warehouse) Artificial intelligence Statistics

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Control Systems and Identification

Physical Sciences → Engineering → Control and Systems Engineering

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Iterative Learning Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Weighted Recursive Least Square for Parameter Identification of Nonlinear Wiener–Hammerstein Systems

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