A neural network approach to control performance assessment

DOI10.1108/17563780810919159zbMath1157.93525OpenAlexW1969966082MaRDI QIDQ3613742

Feng Wan, Yunfeng Zhou

Publication date: 12 March 2009

Published in: International Journal of Intelligent Computing and Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1108/17563780810919159

zbMATH Keywords

analysis of varianceperformance appraisalcorrelation analysiscontrol technology

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)

Cites Work

• Good, bar or optimal? Performance assessment of multivariable processes
• Controller performance benchmarking and tuning using generalised minimum variance control
• Performance monitoring of control systems using likelihood methods
• Practical identification of NARMAX models using radial basis functions
• Delay‐dependent robust control design for uncertain multi‐time‐delayed linear systems
• Orthogonal least squares methods and their application to non-linear system identification
• A fast nonlinear model identification method

This page was built for publication: A neural network approach to control performance assessment