青霉素发酵过程的智能优化控制

本文在分析青霉素发酵补糖工艺的要求和存在的问题基础上,设计出智能控制算法,采用集散系统实现在线优化控制,经实际应用,效果明显。     

一类专家模型参考自适应控制

本文将专家系统技术和模型参考自适应控制相结合，提出了一种新的基于专家系统模型参考自适应控制，该系统集智能控制思想与专家技术于一身，从而得到很强的控制律，为验证其有效性，以两关节机器人为对象进行仿真，在有负载扰动情况下，该系统能使机器人跟踪上希望轨迹，其系统响应和鲁棒性优于常规的控制算法。     

基于信息的智能控制理论研究

本文介绍的基于信息的智能控制理论的发展过程，主要分为智能控制的信息指标和智能控制的信息结构分析两部分，文中在最后对这套理论可能的发展方向进行了探讨。     

一个面向CAD／CAM的演绎数据库管理系统

演绎数据库管理系统ＤＥＤＢＭＳ是工程数据库管理系统ＥＤＢＭＳ／２中的一个子系统。本文着重介绍其产生式语言用户界面、工作流程及功能特点。ＤＥＤＢＭＳ系统的开发，使ＥＤＢＭＳ／２不仅具有工程数据据管理功能，而且具有数据演绎和知识处理能力，从而成为ＣＡＤ／ＣＡＭ系统集成化和智能化的有力支撑工具。     

单片机在管道强制输球清蜡装置中的应用

用AT89C2051单片机作控制核心，接口部分采用少量集成电路，使投球机除具有手动投球功能外，又能依据管道温度、自动改变投球间隔时间，具有一定的智能性，可靠性和实用性。     

IMPACCT: Methodology and Tools for Power-Aware Embedded Systems

Power-aware systems are those that must exploit a widerange of power/performance trade-offs in order to adapt to the power availabilityand application requirements. They require the integration of many novel powermanagement techniques, ranging from voltage scaling to subsystem shutdown.However, those techniques do not always compose synergistically with eachother; in fact, they can combine subtractively and often yield counterintuitive,and sometimes incorrect, results in the context of a complete system. Thiscan become a serious problem as more of these power aware systems are beingdeployed in mission critical applications.To address the problem of technique integration for power-aware embedded systems, we propose a new design tool framework called IMPACCT and the associated design methodology. The system modeling methodology includes application model for capturing timing/powerconstraints and mode dependencies at the system level. The tool performs power-awarescheduling and mode selection to ensure that all timing/power constraintsare satisfied and that all overhead is taken into account. IMPACCT then synthesizesthe implementation targeting a symmetric multiprocessor platform. Experimentalresults show that the increased dynamic range of power/performance settingsenabled a Mars rover to achieve significant acceleration while using lessenergy. More importantly, our tool correctly combines the state-of-the-arttechniques at the system level, thereby saving even experienced designersfrom many pitfalls of system-level power management.     

采用BP神经网络记忆模糊规则的控制

本文提供了一种比模糊推理更为自然的方式使用人们的经验知识,通过一组神经元不同 程度的兴奋表达一个抽象的概念值,由此将抽象的经验规则转化成多层神经网络的输入一输 出样本.通过Back-Propagation学习算法使得网络记忆这些样本.控制器以"联想记忆"方 式使用这些经验.本文介绍了控制器的构造方法,给出了控制仿真结果,并讨论了这种控制器 的特点和发展前途.     

An analog circuit design environment based on cooperating blackboard systems

A novel approach to design automation for analog circuits is presented. The prototype implementation-OASE-has been realized as a set of cooperating expert systems with blackboard architecture. The circuit specific knowledge bases use hybrid representation schemes and are strictly separated from an execution engine containing the necessary control knowledge. This alleviates the knowledge acquisition process as well as the extension and maintenance of existing knowledge. OASE has been developed as a design assistant, featuring different levels of interactivity, a hierarchical design style and fully embedded algorithmic standard tools. In its current version it is able to design a broad range of different CMOS operational amplifiers.     

基于MFQ的补丁优先算法的研究与实现

目前采用的视频流调度算法，没有充分利用补丁流满足服务率高而占用系统资源少的优势，系统效率较低．为了提高效率，提出了一种基于MFQ的补丁优先算法，并给出了该算法的系统流程。通过对实验结果的比较，该算法在用户请求撤销率、节目调度不公平性和用户等待时间方面有明显的优越性．     

RanGen: A Random Network Generator for Activity-on-the-Node Networks

In this paper, we describe RanGen, a random network generator for generating activity-on-the-node networks and accompanying data for different classes of project scheduling problems. The objective is to construct random networks which satisfy preset values of the parameters used to control the hardness of a problem instance. Both parameters which are related to the network topology and resource-related parameters are implemented. The network generator meets the shortcomings of former network generators since it employs a wide range of different parameters which have been shown to serve as possible predictors of the hardness of different project scheduling problems. Some of them have been implemented in former network generators while others have not.