Communications in Embedded Control Systems

嵌入式控制系统中的通信-项目摘要本项目研究不同的嵌入式软件和硬件组件应该如何相互通信，以便使整个全球系统以令人满意的方式运行。研究的主要领域是传输信号的信息理论内容，即研究为了使物理系统满足其规范，需要在不同组件之间传输多少位信息。例如，自主机器人系统通常依赖于各种各样的传感器，那么问题就变成了，哪些传感器是需要的？此外，是否有可能以系统的方式压缩数据，例如使用虚拟传感器，以便丢弃对当前任务或操作模式不重要的信息？由于完成某一任务所需的传感数据取决于控制律、系统的动力学和任务的复杂性，信息理论为统一处理传感器和执行器的选择和控制模式设计等问题提供了工具。该项目侧重于以下两个有利的研究领域：1。用于控制连续的机械装置的符号的、计算机生成的输入的信息理论内容的建模。多智能体机器人系统中嵌入式传感器和执行器的选择。这种选择是为了使控制系统在带宽限制的情况下满足其规格，即使机器人在避免环境中的障碍物的同时保持队形。在这个项目中，计算机生成的或语言控制命令被建模为可由基于触发器的混合系统读取的模式描述字符串。换句话说，建立基于软件的物理连续装置控制模型，使实际控制信号在编码长度方面具有明确的信息论内容，从而将多模态控制领域与信息论领域联系起来。该模型支持对组件集成问题进行调查。由于每个传感器或执行器都对编码控制信号所需的总比特数做出了贡献，因此，在系统应以令人满意的方式运行的约束下，通过最小化代码长度，可以推导出当前操作模式中所需组件的自然度量。此外，对码长的明确关注对编码理论有直接的影响，即：关于不同嵌入式组件之间共享的信息应该如何表示的理论是本研究的直接结果。在这个项目中研究的控制理论的信息理论方法在嵌入式控制领域之外有许多潜在的应用。例如，在遥控机器人中，控制信号通过通信信道传输，其中信道噪声的存在使得传输尽可能短的指令更为可取。相关的问题出现在最小注意控制领域，注意功能被定义为控制可变性的度量。

Egerstedt, MagnusCCR-0207411Communications in Embedded Control Systems - Project SummaryThis project investigates how different embedded software and hardwarecomponents should communicate with each other in order for the overall, globalsystem to behave in a satisfactory way. The main area of investigation is theinformation theoretic content of the transmitted signals, i.e. a study of howmany bits of information need to be transmitted between the different componentsin order to make the physical system meet its specifications. For instance,autonomous robotic systems are normally relaying on a variety of heterogeneoussensors, and the question then becomes, which of the sensors are needed? Andfurthermore, is it possible to compress the data in a systematic way, e.g. usingvirtual sensors, so that information that is not essential to the current task,or mode of operation, can be discarded?Since the sensory data needed for accomplishing a certain task depends both onthe control law, the dynamics of the system, and the complexity of the task,information theory provides a tool for treating questions concerning sensor andactuator selection and control mode design in a unified way. This project isfocused on the following two enabling areas of research:1. Modeling of the information theoretic content of the symbolic, computergenerated inputs used for controlling continuous, mechanical devices.2. Selection of embedded sensors and actuators for a multi-agent, roboticsystem. This selection is done so that the control system meets itsspecifications in the presence of bandwidth constraints, i.e. so the robotsmaintain formation while avoiding obstacles in the environment.In this project computer generated, or linguistic control commands are modeledas strings of mode descriptions that can be read by trigger based hybridsystems. In other words, models for software based control of physical,continuous devices are developed in such a way that the actual control signalshave a clear information theoretic content in terms of code lengths, thusconnecting the field of multi-modal control with that of information theory.This model enables the investigation of component integration issues. Since eachsensor or actuator contributes to the total number of bits needed for coding thecontrol signals, by minimizing the code lengths subject to the constraint thatthe system should behave in a satisfactory way, a natural measure of whatcomponents are needed in the current mode of operation is derived. Furthermore,the explicit focus on code lengths has immediate implication on coding theory,i.e. a theory for how the information shared between different embeddedcomponents should be represented is a direct consequence of this research.The information theoretic approach to control theory under investigation in thisproject has a number of potential applications outside the field of embeddedcontrol. For instance, in teleoperated robotics the control signals aretransmitted over communication channels in which the presence of channel noisemakes it preferable to transmit instructions that are as short as possible. Arelated problem arises in the area of minimum attention control, where anattention functional is defined as a measure of the control variability.