TMS320C3x 칩을 이용한 로보트 매뉴퓰레이터의 실시간 신경 제어기 실현

Implementation of a real-time neural controller for robotic manipulator using TMS 320C3x chip

Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. The TMS32OC31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the, network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time, control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.