Comparative study of parametric and intelligent unstructured uncertainties for robust controller design

• Main Authors: M. Raafat, Safanah, Martono, Wahyudi, Akmeliawati, Rini
• Format: Conference or Workshop Item
• Language: English
• Published: 2009
• Subjects: TJ212 Control engineering
• Online Access: http://irep.iium.edu.my/5396/1/isiea2009_safanah.pdf; http://irep.iium.edu.my/5396/; http://dx.doi.org/10.1109/ISIEA.2009.5356444

This paper describes the design, analysis and comparison of two ∞ H controllers that use two different uncertainty model representations; unstructured and structured (parametric) uncertainties. The later is usually considered as less conservative. However, the application of intelligent techniques like Adaptive Neural Fuzzy Inference System (ANFIS) in the identification of unstructured uncertainty bounds provides considerable improvements in reduction of conservatism and guaranteed robust stability and performance, as illustrated in the results of practical implementation to a servo motion system .