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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/modeling-of-autonomous-systems
课程评论：没有评论
课程名称：自主系统建模 课程概述：本课程将讲解任何自主系统的核心结构，包括传感器、执行器以及可能的通信网络。课程还将涵盖用于自主系统的不同正式建模框架，包括状态空间表示（差分或微分方程）、定时自动机、混合自动机以及一般的转换系统。它将描述系统的解决方案和行为以及系统之间的不同连接。 课程大纲： 1. **课程介绍**：在这一模块中，我们将深入探讨自主系统和网络物理系统的世界，了解其重要性、结构和应用。通过研究如阿里安5号火箭失效、自适应巡航控制和自动驾驶汽车等实际案例，我们将掌握建模在自主系统中的重要基础。此外，讨论这些系统的关键组件、硬件与软件之间的紧密互动以及自主系统在各个领域的普遍性。 2. **自主系统建模基础**：在第二模块中，我们深入探讨系统建模的细微差别。通过教学视频，学生将理解系统定义、状态图和转换系统。相关的作业进一步巩固这些知识。2003年东北大停电等实际案例强调了精确建模的重要性，而饮料自动售货机和检票口等实际系统则阐述了核心概念。这里将展开一场真正的学术旅程，深入系统建模的本质。 3. **物理系统与混合系统建模**：第三模块让学生接触动态系统建模的基本原理，重点关注平移机械系统、旋转机械系统和模拟电路。强调这些系统背后的数学关系，课程接着深入定时和混合自动机的具体示例，为理解时间在系统建模中的作用提供全面视角。 4. **系统的行为与组成**：第四模块深入探讨系统解决方案、行为及各种组成形式。学习者将接触系统及其行为的数学表示。通过一系列引人入胜的视频内容，学习者将探索并行、串行和反馈组成。此外，该模块提供实际作业以增强理解，并对系统建模进行详细研究。 该课程旨在为学生提供在自主系统建模方面的扎实理论基础与实践应用，适合所有对该领域感兴趣的学习者。
Name:Course Introduction
Description:In this introductory module, we delve into the world of autonomous and cyber-physical systems, their significance, structure, and applications. By studying real-world examples, such as the Ariane 5 rocket failure, adaptive cruise control, and self-driving cars, we will grasp the foundational understanding of the importance of modeling in autonomous systems. Moreover, we'll discuss key components of these systems, the tight interaction between hardware and software, and the ubiquity of autonomous systems in various sectors.
Name:Foundations of Autonomous Systems Modeling
Description:In Module 2, we delve into the nuances of system modeling. Through instructional videos, students grapple with system definitions, state diagrams, and transition systems. Relevant assignments further solidify this knowledge. Real-world examples, like the Northeast Blackout of 2003, underscore the importance of precise modeling, while practical systems such as a Beverage Vending Machine and Turnstile illustrate core concepts. A truly academic journey into the essence of system modeling awaits.
Name:Modeling Physical Systems and Hybrid Systems
Description:Module 3 introduces students to the fundamental principles of modeling dynamic systems, focusing on translational mechanical systems, rotational mechanical systems, and analog circuits. Emphasizing the mathematical relationships underlying these systems, the course progresses into more specific examples and dives deep into timed and hybrid automata, providing a comprehensive understanding of the role of timing in systems modeling.
Name:Systems' Behaviors and Composition
Description:Module 4 dives deep into understanding system solutions, behaviors, and various compositions. Learners will be introduced to the mathematical representations of systems and their behaviors. Through a series of engaging video content, learners will explore parallel, serial, and feedback compositions. Additionally, the module provides practical assignments to enhance comprehension and a detailed study of system modeling.
This course will explain the core structure in any autonomous system which includes sensors, actuators, and potentially communication networks. Then, it will cover different formal modeling frameworks used for autonomous systems including state-space representations (difference or differential equations), timed automata, hybrid automata, and in general transition systems. It will describe solutions and behaviors of systems and different interconnections between systems. This course can be taken
