Hardware Development for Cyber-Physical Systems adaptive control algorithms

信息物理系统自适应控制算法的硬件开发

基本信息

批准号：
1922711
负责人：
金额：
--
依托单位：
University of Southampton
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1922711
关键词：
Hardware Development Cyber Physical Systems

项目摘要

Cyber-Physical Systems (CPS) are integrations of computation with physical processes.Embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical process affect computations and vice versa. CPS gained a lot of importance from last decade because of its self-adaptive control nature.To this end, there are several challenges need to be addressed for providing accurate self adaptive control to CPS, including physical model identification in real time when the system subjected to external disturbances and in the presence of uncertainty. Recently proposed estimation based multiple model switched adaptive control (EMMSAC) are shown that the best performance in the presence of uncertainty and external disturbances over the state-of-the-art algorithms for controlling physical system adaptively.These algorithms have been implanting on the Digital Signal Processing (DSP) platform. In general, these algorithms need a lot of computing resources and reduced execution time. To cope with all these challenges, designers can rely on more and more mature digital electronics technologies. Further state-of-the-art implementations are limited by speed. Moreover in cyber-physical system if we desired to control physical system adaptively, EMMSAC should perform operations in micro or nanoseconds thereby physical system will able to adapt the controller instructions within the scheduled time. To achieve aforementioned characteristics we are intended to develop these EMMSAC algorithms on field programmable gate array (FPGA). This will help to build an efficient, stable, accurate and reliable cyber-physical system. In the initial stage of work, we developed a 2x2 kalman filter on Virtex ultra-scale FPGA, which is the fundamental block in the EMMSAC algorithm. We have also developed a case study for controlling the velocity of the car by adapting the road conditions.In future, we are intended to apply these algorithms for boost converter which we can develop in our lab environment under different load conditions. Also we are intended to increase number models 50-400. The next future challenge is to implement the dynamiconline refinement strategy for EMMSAC.

网络物理系统（CPS）是计算与物理过程的集成。安装的计算机和网络监视和控制物理过程，通常使用反馈循环，物理过程会影响计算，反之亦然。由于其自适应控制性质，CPS从过去十年开始变得非常重要。为此，为了为CP提供准确的自适应控制，需要解决一些挑战，包括实时识别系统时的物理模型识别。外部干扰和不确定性的存在。最近提出的基于估计的多个模型转换自适应控制（EMMSAC）表明，在存在不确定性和外部干扰的情况下，最佳性能是针对最先进的算法，用于控制物理系统的最新算法。这些算法已植入数字上信号处理（DSP）平台。通常，这些算法需要大量计算资源并减少执行时间。为了应对所有这些挑战，设计师可以依靠越来越成熟的数字电子技术。进一步的最先进的实现受速度的限制。此外，在网络物理系统中，如果我们希望自适应地控制物理系统，则EMMSAC应在微型或纳秒中执行操作，从而可以在计划的时间内调整控制器指令。为了实现上述特征，我们旨在在现场可编程栅极阵列（FPGA）上开发这些EMMSAC算法。这将有助于建立一个高效，稳定，准确和可靠的网络物理系统。在工作的初始阶段，我们在Virtex超级FPGA上开发了一个2x2 Kalman滤波器，这是EMMSAC算法中的基本块。我们还开发了一项案例研究，用于通过调整道路条件来控制汽车的速度。将来，我们旨在将这些算法应用于升压转换器，我们可以在不同的负载条件下在实验室环境中开发这些算法。另外，我们旨在增加数字模型50-400。下一个将来的挑战是为EMMSAC实施DynamiconLine改进策略。