NEURAL-NET ROBOT CONTROLLER - STRUCTURE AND STABILITY PROOFS

LEWIS F., YESILDIREK A., LIU K.

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, cilt.12, sa.3, ss.277-299, 1995 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 3
  • Basım Tarihi: 1995
  • Doi Numarası: 10.1007/bf01262965
  • Dergi Adı: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.277-299
  • Yıldız Teknik Üniversitesi Adresli: Hayır

Özet

A multilayer neural net (NN) controller for a general serial-link robot arm is developed. The structure of the NN controller is derived using a filtered error approach. It is argued that standard backpropagation tuning, when used for real-time closed-loop control, can yield unbounded NN weights if: (1) the net can not exactly reconstruct a certain required control function, (2) there are bounded unknown disturbances in the robot dynamics, or (3) the robot arm has more than one link (i.e. nonlinear case). On-line weight tuning algorithms including correction terms to backpropagation, plus an added robustifying signal, guarantee tracking as well as bounded weights. The correction terms involve a second-order forward-propagated wave in the backprop network.