✦ LIBER ✦

Transient performance enhancement of direct adaptive control of nonlinear systems using multiple models and switching

✍ Scribed by Cezayirli, A.; Ciliz, M.K.

Book ID: 117811160
Publisher: The Institution of Engineering and Technology
Year: 2007
Tongue: English
Weight: 803 KB
Volume: 1
Category: Article
ISSN: 1751-8644
DOI: 10.1049/iet-cta:20060494

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Improving transient response of adaptive

Improving transient response of adaptive control systems using multiple models and switching

✍ Narendra, K.S.; Balakrishnan, J. 📂 Article 📅 1994 🏛 IEEE 🌐 English ⚖ 584 KB

Adaptive switching control of discrete t

Adaptive switching control of discrete time nonlinear systems based on multiple models

✍ Rui Kan 📂 Article 📅 2004 🏛 South China University of Technology and Academy o 🌐 English ⚖ 590 KB

Robust adaptive control using multiple m

Robust adaptive control using multiple models, switching and tuning

✍ Giovanini, L. 📂 Article 📅 2011 🏛 The Institution of Engineering and Technology 🌐 English ⚖ 518 KB

Nonlinear excitation and phase shifter c

Nonlinear excitation and phase shifter controller for transient stability enhancement of power systems using adaptive control law

✍ Y.L. Tan; Y. Wang 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 801 KB

Control design approaches for nonlinear

Control design approaches for nonlinear systems using multiple models

✍ Junyong Zhai; Shumin Fei; Feipeng Da 📂 Article 📅 2007 🏛 South China University of Technology and Academy o 🌐 English ⚖ 167 KB

Design and performance analysis of a dir

Design and performance analysis of a direct adaptive controller for nonlinear systems

✍ T. Zhang; S.S. Ge; C.C. Hang 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 275 KB

In this paper, a direct adaptive controller is developed based on multilayer neural networks (MNNs) for a class of nonlinear systems. The proposed scheme avoids the possible singularity problem of the controller usually met in adaptive control design. The system tracking error is proven to converge