推荐一个求解最优控制问题的软件包—TOMLAB

zygsq

最近做一些有关最优控制的工作，发现一个较好的工具软件包TOMLAB-GPOCS，利用高斯- 伪谱法(GAUSS Pseudo Spectral Method)/SQP非线性规划方法(NLP)对最优控制问题（Optimal Control）进行求解。

在http://tomopt.com/tomlab/注册后可以下载，但是还需要和相关技术人员联系，取得有效期为21天的注册文件，方可使用。

Tomlab本身是个基于matlab的大型优化工具包，GPOCS只是其中的一小部分。

鉴于本人尚未发现有其他的可以解决最优控制问题的软件，姑且认为GPOCS还是不错的，推荐给有需要的朋友。

附：tomlab的英文简介

TOMLAB is a general purpose development environment in Matlab for research, teaching and practical solution of optimization problems.

TOMLAB has grown out of the need for advanced, robust and reliable tools to be used in the development of algorithms and software for the solution of many different types of applied optimization problems.


There are many good tools available in the area of numerical analysis, operations research and optimization, but because of the different languages and systems, as well as a lack of standardization, it is a time consuming and complicated task to use these tools. Often one has to rewrite the problem formulation, rewrite the function specifications, or make some new interface routine to make everything work. Therefore the first obvious and basic design principle in TOMLAB is: Define your problem once, run all available solvers. The system takes care of all interface problems, whether between languages or due to different demands on the problem specification.


In the process of optimization one sometimes wants to graphically view the problem and the solution process, especially for ill-conditioned nonlinear problems. Sometimes it is not clear what solver is best for the particular type of problem and tests on different solvers can be of use. In teaching one wants to view the details of the algorithms and look more carefully at the different algorithmic steps. An unexperienced user or a student might want some very easy way to solve the problem, and would like to use a menu system or a graphical user interface (GUI). Using a GUI or a menu system also makes it very easy to change parameters influencing the solution process. When developing new algorithms tests on thousands of problems are necessary to fully access the pros and cons of the new algorithm. One might want to solve a practical problem very many times, with slightly different conditions for the run. Or solve a control problem looping in real-time and solving the optimization problem each time slot.


All these issues and many more are addressed with the TOMLAB optimization environment. TOMLAB gives easy access to a large set of standard test problems, optimization solvers and utilities.  

Furthermore, it is easy to define new problems in the TOMLAB format, and try to solve them using any solver. To access the user problem in the GUI or menu system, routines converting the problem into the TOMLAB Init File and adding the problems to the GUI data base are available and simple to use. To use TOMLAB in real-time control, the efficient MEX-file interfaces calling fast Fortran solvers are of great importance.

[ 本帖最后由 zygsq 于 2007-12-10 21:58 编辑 ]

jimmin

xiexie!

[ 本帖最后由 jimmin 于 2008-8-5 00:06 编辑 ]

zygsq

好的，我会给你发邮件，请注意查收。
ps:你说的这个问题，我周围也有人注意到了，不知是不是被老外给撤下来了

zygsq

现在该网站提供的是一个类似的软件包，GPOCS(Gauss Pseudospectral Optimal Control Softawre)

ygjzdh

楼主你好，我也没有找到dido这个模块，麻烦你给我一个拷贝，谢谢！
我的邮箱是：ygjzdh@163.com。多谢！

windwill

楼主，也给我传一份吧，非常感谢！
我的邮箱 shjtan.cn@gmail.com
谢谢

tanlvgang

楼主  能发给我吗?
我现在很需要它.
我的邮箱是tanlvgang@163.com
谢谢！

tanlvgang

发给我求解最优控制问题的软件包—TOMLAB好吗？
我的邮箱是tanlvgang@163.com

mdeng1985

楼主也给我发一份吧，谢谢
mdeng1985@163.com
呵呵！

zeroburn

请楼主也给我发一份吧
mars_legend@163.com
谢谢！

xxlion2005

我想用DIDO求解航天最优控制问题
请楼主给我发一份，谢谢
是装上就可以用，还需要TOMLAB的许可吗？
xxlion2005@126.com

tongkewei

DIDO已经被GPOCS取代了，GPOCS无论从精度或是速度上都优于DIDO.可以看GPOCS的作者和他的学生的论文。此外LGL点在求解最优控制时，本身就有约束条件互相不满足的限制，而LG点没有这些互相不符合的情况（可以看GPOCS作者学生的论文），所以才出来这个GPOCS.我自己也作了一个基于Matlab优化工具箱的LG点拟谱最优控制计算软件，领略了一把LG点拟谱最优控制的优点，很强大哦，大家可以自己做一个。版权问题，我不能把他开源，很遗憾！

zygsq

楼上强人啊 国内（伪）谱方法这块的资料也真还不多

ps：你把pseudo 译作 拟吗？翻译的问题 哈哈

另外想咨询下 你自编的程序 用的什么nlp方法？也是自编的？要是那样 那就更强悍了

[ 本帖最后由 zygsq 于 2007-12-22 17:38 编辑 ]

iutam

DIDO的新网页：http://www.didosolver.com/
不过使用限制比GPOCS严得多，所以可能还是不好用 不知道大家的感觉怎么样。。。。

GPOCS相对于DIDO的优点主要是,由于没有在端点处施加微分（方程）约束，因而NLP乘子与离散的协态存在真正的一对一映射(Covector Mapping)，而DIDO只有在一些条件（Closure Conditions）下才可以。因而GPOCS解经常要精确一些，特别是协态值。但通过实际使用发现，在有的情况下GPOCS解出的控制量在端点处易出现跳变，而且控制量端点约束无法施加。现在一些文章讨论高阶的伪谱方法，这种情况再想找到像GPOCS那样漂亮的协态映射就有些难了 还有就是有的文章说Matlab的NLP solver提供的协态值不太准，不过也没有验证过。SNOPT可能还是最佳选择：）要是免费的，就用IPOPT吧。

pseudospectral

Here is how you can get a free DIDO Demo version.
1. go to www.elissar.biz
2. click Free DIDO Test Version
3. fill in a simple form, remember to put in your MATLAB license number (use ver command)
4. A free version of DIDO will be send out to your email address.

The Demo version can solve problems with 4 states, 2 controls and 3 path constraints.
 

pseudospectral

究竟哪个好？只要google一下有哪些人在用，有多少文章引用就清楚了。
就我所知，GPOCS 只发过一篇 journal 。从发表过的文章看，使用DIDO的至少有：NASA，Stanford， MIT，GIT， Texas A&M, ..., 

所谓的 Covector Mapping Principle 并不是GPOCS 独有的。Pseudspectral based solvers like DIDO, and many Runge-Kutta mathods all have CMP. 

任何收敛的最优控制算法都必须有Covectort Mapping. 但是有Covectort Mapping不一定保证收敛性。GPOCS 用的算法我从未看到任何收敛性的证明。DIDO算法收敛性的证明可在IEEE Trans. on Automatic Control 2006上查到。 

iutam

好象看到过关于Mayer型目标函数LG点收敛性的证明。Bolza型的没有看到过。
试用GPOCS后发现，Bolza型或Lagrange型问题解得有些问题。
比如bryson应用最优控制上的x的二阶导数等于u的那个最小能量问题。

pseudospectral

1. 我很确信没有人证明Legendre Gauss PS optimal control methods 的收敛性，even for Mayer type of problems。

2 对于pseudospectral optimal control， 现在只有LGL Pseudospectral 的收敛性被证明了。

3. iutam, you are right.  GPOCS的算法是有很多问题的。例如control在端点处会发散，对aerospace control 中经常会遇到的singular problems更是有大问题的。

iutam

：）收敛性问题挺困难的。pseudospectral 真是专家。。。。曾在NPS做过LGL算法的研究吗？有机会多交流。不过GPOCS在处理Mayer型问题时，我们还没有发现大问题。
L. T. Biegler领导的小组也做了些这方面的工作，集中在LGR点上，见他综述。
http://dynopt.cheme.cmu.edu/papers/papers.html#Preprints

pseudospectral

Discussion on convergence issues seems off the topic. If anybody interested, we can start a new discussion.

I know Biegler's work. He has some really good results. But on his convergence result of LGR, his algorithms are not really pseudospectral. They are more closed to Runge-Kutta.

I don't really want to talk about GPOCS, cause I don't want to bad-mouth others.