|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/modeling-feedback-systems
课程评论：没有评论
课程名称：控制系统分析：动态系统建模 课程概述：本课程将探讨动态系统的建模及反馈控制。课程首先介绍控制理论和拉普拉斯变换在求解微分方程中的应用，提供线性、时间不变性和动态系统建模的坚实基础。接下来的内容将深入研究动态系统建模的基本法则，重点从牛顿定律和基尔霍夫定律等基本原理推导微分方程。 课程大纲： 1. **控制系统与拉普拉斯变换简介** - 本周将结合控制系统和微分方程的基本概念。学员将深入了解控制理论的基础，反馈控制的重要性，及拉普拉斯变换在求解常微分方程中的应用。到此周结束时，学员将掌握线性、时间不变、建模方法及控制系统的实际应用。 2. **物理系统建模** - 第二周将探讨用于建模反馈系统的基本法则。学员将学习如何应用这些法则建模简单的机械、电气和电机系统，通过牛顿运动定律、基尔霍夫定律和电动机/发电机法则推导微分方程。此外，学员将掌握如何使用拉普拉斯变换及反拉普拉斯变换来表示这些系统的传递函数，以分析和理解其频域行为。 3. **块图分析与动态响应** - 第三周将深入应用拉普拉斯变换。学员将学习如何利用初始/最终值定理根据拉普拉斯域的表示计算时域信号的值。此外，将发展操控互连系统的块图表示的技能，以分析复杂系统并理解其整体行为。还将探索1阶和2阶系统的动态响应，了解其瞬态与稳态特性。 4. **瞬态阶跃响应规范** - 第四周将专注于使用瞬态阶跃响应规范进行系统性能分析。学员将学习如何计算和评估关键性能指标，如上升时间、稳态时间和超调，通过系统的阶跃响应来实现。同时，学员将理解极点位置与阶跃响应性能规格之间的关系，并学习如何利用瞬态阶跃响应数据估计2阶传递函数的近似。 5. **从瞬态响应数据建模与稳定性** - 祝贺你完成了本课程的最后一周。本周将深入探讨有界输入有界输出（BIBO）稳定性及其在分析线性时间不变（LTI）系统中的应用。学员将学习BIBO稳定性的必要和充分条件，并应用这些条件来评估动态系统的稳定性。此外，将探讨Routh稳定性准则，以帮助确定系统的稳定性，并学习如何设计稳定的比例反馈系统。 通过本课程，学员将获得分析、评估和设计稳定系统的知识和技能，确保实现理想的系统性能。
Name:Introduction to Control Systems and Laplace Transforms
Description:Welcome to Modeling Feedback Systems. This first week combines the essential concepts of control systems and differential equations. You will explore the foundations of control theory, understand the significance of feedback control, and master the application of Laplace transforms in solving ordinary differential equations. By the end of this week, you will possess a solid understanding of linearity, time-invariance, modeling approaches, and the practical uses of control systems.
Name:Modeling of Physical Systems
Description:During the second week of this course, you will delve into the foundational laws used in modeling feedback systems. You will explore how these laws are applied to model simple mechanical, electrical, and electromechanical systems by deriving differential equations from fundamental principles such as Newton's laws of motion, Kirchhoff's laws, and the Motor/Generator laws. Additionally, you will gain proficiency in representing these systems as transfer functions using Laplace and inverse Laplace transforms, which will enable you to analyze and understand their behavior in the frequency domain. By the end of this week, you will have acquired the essential knowledge and skills to effectively model and analyze a wide range of dynamic systems.
Name:Block Diagram Analysis and Dynamic Response
Description:In the third week of this course, you will dive deeper into the application of Laplace transforms. You will start by learning how to use the initial/final value theorems to calculate the values of time-domain signals using their Laplace-domain representation. Additionally, you will develop the skills to manipulate block diagram representations of interconnected systems, enabling you to analyze complex systems and understand their overall behavior. You will also explore the dynamic response of 1st- and 2nd-order systems, gaining insights into their transient and steady-state characteristics. Lastly, you will discover techniques to approximate higher-order systems reasonably well by utilizing the impulse and step responses of lower-order systems. By the end of this week, you will have acquired advanced tools and techniques to analyze and model a wide range of dynamic systems with precision and accuracy.
Name:Transient Step Response Specifications
Description:In the fourth week of this course, you will focus on system performance analysis using transient step response specifications. You will learn how to calculate and evaluate key performance metrics such as rise time, settling time, and overshoot using the step response of a system. By understanding the relationship between pole locations and step response performance specifications, you will gain insights into how system dynamics affect the overall performance. Furthermore, you will utilize transient step response data to estimate the 2nd-order transfer function approximation, enabling you to model and analyze complex systems accurately. Lastly, you will compare the impact of zeros and additional poles on the step responses of systems, deepening your understanding of how system components influence the overall behavior. By the end of this week, you will be equipped with the skills to assess and optimize system performance based on transient step response characteristics.
Name:Modeling From Transient Response Data and Stability
Description:Congratulations on making it to the 5th and final week of this course. This week you will delve into the concept of Bounded-Input Bounded-Output (BIBO) stability and its application in analyzing Linear Time-Invariant (LTI) systems. You will learn the necessary and sufficient conditions for BIBO stability and apply them to assess the stability of dynamic systems. Additionally, you will explore Routh's stability criterion, which allows you to determine system stability. Furthermore, you will discover how to design stable proportional-feedback systems using Routh's stability criterion, enabling you to create control systems that exhibit desirable behavior. By the end of this week, you will have acquired the knowledge and skills to analyze, assess, and design stable systems using BIBO stability and Routh's stability criterion.
In this course, you'll explore modeling of dynamic systems and feedback control. The course begins with an introduction of control theory and the application of Laplace transforms in solving differential equations, providing a strong foundation in linearity, time-invariance, and dynamic system modeling. The following week will delve into the laws governing the modeling of dynamic systems, with a focus on deriving differential equations from fundamental principles like Newton's laws and Kirchhoff
