Adaptive feedback linearization using efficient neural networks

Yesildirek A., LEWIS F.

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, cilt.31, ss.253-281, 2001 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 31
  • Basım Tarihi: 2001
  • Doi Numarası: 10.1023/a:1012011226385
  • Dergi Adı: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.253-281
  • Yıldız Teknik Üniversitesi Adresli: Hayır

Özet

For a class of single-input, single-output, continuous-time nonlinear systems, a feedback linearizing neural network (NN) controller is presented. Control action is used to achieve tracking performance. The controller is composed of a robustifying term and two neural networks adapted on-line to linearize the system by approximating two nonlinear functions. A stability proof is given in the sense of Lyapunov. No off-line weight learning phase is needed and initialization of the network weights is straightforward. The NN controller is tested on a standard benchmark problem.