摘要
文章介绍了自动水下航行体(AUV)的国内外发展基本概况,着重介绍了水下自航行观测平台相关技术发展现状和发展趋势。文章按照功能结构、硬件结构和软件结构的顺序,在分析了分布式与集中式控制体系性能的基础上,重点讨论了布式网络结构中开放式多任务实时数据采集系统的设计与实现。
以“863”重大项目“小型自主航行观测技术”为应用背景介绍了观测平台全局网络的设计与构成,阐述了测量子系统在此网络结构中的工作原理。
基于开放式、面向任务、模块化设计思想,研究了布式网络结构中实时数据采集系统的硬件结构和软件系统。文章阐述了在分布式体系结构下实时多任务操作系统在测量子系统的应用技术,完成了作为分布式网络节点的测量子系统与上层控制节点的CAN协议通信,并将CAN收发程序嵌入到操作系统中。以CMX-RTOS嵌入式操作系统为基础设计并验证了分布式体系结构下实时多任务测量子系统。讨论了实时多任务测量系统中任务的划分与任务间的协调、调度机制。研究并实现了基于I~2C总线的多路RS-232/485智能转换接口的开放式协议通信控制。实现了多传感器测量任务并发执行,保证了各个传感器测量数据的实时性和有效性。
At first the thesis presents the general situation of autonomous underwater vehicle (AUV) development throughout the world and gives an introduction to the actuality and trend of autonomous underwater observation platform technology. As the sequence of functional architecture, hardware architecture, software architecture, the thesis discusses the design and implementation of measure subsystem after analysing the space-time decomposition architecture and intelligence step-down architecture. The measure subsystem performs a real-time, multi-channel data collection on a AUV platform.
The entire architecture of an AUV platform is described. The platform is an important item of National 863 plans projects and its measure subsystem is explained particularly in this paper.
Using the idea of open, task-oriented and modularization the hardware and software structure are researched. A real-time multitask operating system is deployed successfully on the measure subsystem which is a portion of a distributed AUV control architecture. The measure subsystem and the other nodes of the platform are connected by CAN bus. The CAN receiving and transmitting programs are embedded into the RTOS. With a CMX-RTOS the real-time multitask measure software used in a distributed architecture is designed. Task decomposition, coordination and schedule mechanism of the task modules are discussed in detail. The communication protocol and software of the multi-channel interface between I~2C bus and RS232/485 are researched and implemented. Parallel sampling of multi-sensor is achieved and the validity of the data is improved.
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