标题: CMAC类神经网路之ASIC研制及其在控制上的应用
The ASIC Design Of The CMAC Neural Network And Its Application In Control
作者: 陈建斌
Chen, Chang-Been
陈福川
Chen, Fu-Chuang
电控工程研究所
关键字: CMAC类神经网路;连结量;weight
公开日期: 1994
摘要: 本论文之主要目的在建立一套独立于PC之外的CMAC控制系统,此系统平行地结合传统的PD控制器与CMAC类神经网路控制器,用以改善传统的PD控制器于非线性系统的控制精度。
由于VLSI技术的进步,我们藉由硬体上的设计来提高CMAC类神经网路的运算能力,并使得PD控制器与CMAC类神经网路控制器能平行地进行计算。首先,我们必须先修改CMAC类神经网路中的计算形式,并订定其规格,以降低CMAC类神经网路于电路设计时的难度。接着,我们以两颗Xilin公司的FPGA晶片及两颗32k×8的SRAM来实现CMAC类神经网路控制器,FPGA晶片负责CMAC类神经网路的计算,而SRAM则储存神经元间的连结量(weight)。其次,我们以8051 单晶片实现PD控制器,且平行地结合以FPGA晶惩实现的CMAC控制器,再辅以HP公司的HCTL-2016回授马达的位置至8051单晶片,AD7541A将数位的控制输出讯号转换成类比的电压讯号,架构成完整的CMAC控制系统。最后,将CMAC控制系统应用于A 型臂上第五轴马达的控制,以验证我们所设计的CMAC控制系统。
The object of this paper is to build a stand-alone CMAC control system which combine parallelly the tranditional PD controller and the CMAC controller. We use the control system to improve existing nonlinear control systems.
Because of the great progress in VLSI technology, we can raise the computation speed of the CMAC neural network if it is implemented as a chip. The CMAC chip will function parallelly with the PD controller which is implemented via 8051. First, we modify some computation and determine the specifications and parameters in order to reduce the complexity of hardware design in the CMAC neural network. Then we implement CMAC by two Xilinx's FPGA chips and two 32k×8 SRAMs. The FPGA chips implement the computation n the CMAC neural network. The SRAMs store the weights of the CMAC neural network. Secondly, we implement the PD controller in 8051 single chip which reads the motor position feedback from HCTL-2016. Then, we integrate the PD controller, the CMAC, the HCTL-2016 and the AD7541A to implement the overall CMAC control system. Finally we apply the CMAC control system to conrol the fifth motor of the A-type robot to verify our hardware design.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT833327014
http://hdl.handle.net/11536/59858
显示于类别:Thesis