MULTI-LAYER FEEDBACK-ERROR-LEARNING FOR CONTROL OF FLEXIBLE LINK

1. ABSTRACT In this paper two neural networks using one control approach using Feedback-Error-Learning are combined. The approach is used for neural control of a one arm flexible link robot in order to acquire the inverse dynamic model of the plant. Such systems are characterized as a non-minimum phase system, which is difficult to be controlled by most techniques and by only one neural network, hence this difficulty is overcome by the combination of two neural networks using the Input Delayed approach discussed here.