Octave 序言

Octave原本是一款同伴软件,用于James B. Rawlings(来自威斯康辛麦迪逊大学)和 John G. Ekerdt(来自德克萨斯大学)编写的关于化学反应器设计的本科级别的教材

显然,Octave现在不仅仅是一个课外用处有限的 “教学软件”包。虽然我们最初的目标是有些模糊,但是我们知道我们想创造出一些东西,能让学生解决实际问题,并且他们可以用于许多其他的东西而不仅仅是化学反应器设计。我们发现大多数的学生迅速掌握Octave的基本知识,并且能够在短短几个小时之内自信地使用它,

虽然它原本是用来教反应堆设计,但是它已经应用于其他几个德州大学化学工程系的本科生和研究生课程,并且德州大学数学系,已在微分方程和线性代数教学等领域使用它。最近,Octave已经作为斯坦福的Andrew Ng教授在线机器学习课教学的主要计算工具。

如果你找到程有用,请让我们知道。我们总是有兴趣发现Octave是如何被使用的。

几乎每个人都认为Octave是与音乐相关的,但它实际上是一个教授的名称,他写了一篇著名的教科书化学反应工程,另外众所周知的,他有能力做do quick ‘back of the envelope’ calculations (不知道什么意思),我们希望这种软件将使许多人一样做更多的计算。

根据gnu通用公共许可的条款,每个人都被鼓励与他人共享该软件,你还可以通过编写额外的功能来帮助Octave变得更加出色,并且通知我们它的一些问题。





Model Predictive Control:Theory, Computation, and Design,2nd Edition. James B. Rawlings, David Q. Mayne, Moritz M. Diehl. Chapter 1 is introductory. It is intended for graduate students in engineering who have not yet had a systems course. But it serves a second purpose for those who have already taken the first graduate systems course. It derives all the results of the linear quadratic regulator and optimal Kalman filter using only those arguments that extend to the nonlinear and constrained cases to be covered in the later chapters. Instructors may find that this tailored treatment of the introductory systems material serves both as a review and a preview of arguments to come in the later chapters. Chapters 2-4 are foundational and should probably be covered in any graduate level MPC course. Chapter 2 covers regulation to the origin for nonlinear and constrained systems. This material presents in a unified fashion many of the major research advances in MPC that took place during the last 20 years. It also includes more recent topics such as regulation to an unreachable setpoint that are only now appearing in the research literature. Chapter 3 addresses MPC design for robustness, with a focus on MPC using tubes or bundles of trajectories in place of the single nominal trajectory. This chapter again unifies a large body of research literature concerned with robust MPC. Chapter 4 covers state estimation with an emphasis on moving horizon estimation, but also covers extended and unscented Kalman filtering, and particle filtering. Chapters 5-7 present more specialized topics. Chapter 5 addressesthe special requirements of MPC based on output measurement instead of state measurement. Chapter 6 discusses how to design distributed MPC controllers for large-scale systems that are decomposed into many smaller, interacting subsystems. Chapter 7 covers the explicit optimal control of constrained linear systems. The choice of coverage of these three chapters may vary depending on the instructor's or student's own research interests. Three appendices are included, again, so that the reader is not sent off to search a large research literature for the fundamental arguments used in the text. Appendix A covers the required mathematical background. Appendix B summarizes the results used for stability analysis including the various types of stability and Lyapunov function theory. Since MPC is an optimization-based controller, Appendix C covers the relevant results from optimization theory.
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值