✦ LIBER ✦

Control-affine fuzzy neural network approach for nonlinear process control

✍ Scribed by Atsushi Aoyama; Francis J. Doyle III; Venkat Venkatasubramanian

Book ID: 118415092
Publisher: Elsevier Science
Year: 1995
Tongue: English
Weight: 994 KB
Volume: 5
Category: Article
ISSN: 0959-1524
DOI: 10.1016/0959-1524(95)00010-n

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Control-affine neural network approach f

Control-affine neural network approach for nonminimum-phase nonlinear process control

✍ Atsushi Aoyama; Francis J. Doyle III; Venkat Venkatasubramanian 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 858 KB

The design of controllers for nonlinear, nonminimum-phase processes is very challenging and remains as one of the more difficult control research problems. Most currently available control algorithms rely implicitly or explicitly upon an inverse of the process. Linear control methods For nonminimum-

Neural network-based optimal iterative c

Neural network-based optimal iterative controller for nonlinear processes

✍ Furong Gao; Fuli Wang; Mingzhong Li 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 618 KB

HPSO-based fuzzy neural network control

HPSO-based fuzzy neural network control for AUV

✍ Lei Zhang; Yongjie Pang; Yumin Su; Yannan Liang 📂 Article 📅 2008 🏛 South China University of Technology and Academy o 🌐 English ⚖ 334 KB

Generalized predictive control using rec

Generalized predictive control using recurrent fuzzy neural networks for industrial processes

✍ Chi-Huang Lu; Ching-Chih Tsai 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 263 KB

Synthetic neural networks for process co

Synthetic neural networks for process control

✍ G.Allen Pugh 📂 Article 📅 1989 🏛 Elsevier Science 🌐 English ⚖ 176 KB

An approach to inverse nonlinear control

An approach to inverse nonlinear control using neural networks

✍ T.H. Lee; C.C. Hang; L.L. Lian; B.C. Lim 📂 Article 📅 1992 🏛 Elsevier Science 🌐 English ⚖ 892 KB