Nonlinear System Control for DNP

동적 신경망에 의한 비선형 시스템 제어

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are demonstrate the effectiveness of the Proposed learning using the DNP.