登录
首页 » Python » MPCPy

MPCPy

于 2020-11-23 发布 文件大小:14783KB
0 232
下载积分: 1 下载次数: 17

代码说明:

  MPCPY是一个Python程序包,它有助于测试和实现用于构建系统的乘员集成模型预测控制(MPC)。该软件包侧重于使用数据驱动的、简化的物理或统计模型来预测建筑性能和优化控制。四个主要模块包含对象类来导入数据,与真实的或仿真的系统交互,估计和验证数据驱动的模型,并优化控制输入。(MPCPy is a python package that facilitates the testing and implementation of occupant-integrated model predictive control (MPC) for building systems. The package focuses on the use of data-driven, simplified physical or statistical models to predict building performance and optimize control. Four main modules contain object classes to import data, interact with real or emulated systems, estimate and validate data-driven models, and optimize control input.)

文件列表:

MPCPy-master, 0 , 2018-05-04
MPCPy-master\.gitignore, 967 , 2018-05-04
MPCPy-master\README.md, 3305 , 2018-05-04
MPCPy-master\bin, 0 , 2018-05-04
MPCPy-master\bin\README.md, 716 , 2018-05-04
MPCPy-master\bin\runUnitTests.py, 4245 , 2018-05-04
MPCPy-master\doc, 0 , 2018-05-04
MPCPy-master\doc\README.md, 641 , 2018-05-04
MPCPy-master\doc\__init__.py, 1 , 2018-05-04
MPCPy-master\doc\uml, 0 , 2018-05-04
MPCPy-master\doc\uml\PlantUMLs.txt, 1898 , 2018-05-04
MPCPy-master\doc\userGuide, 0 , 2018-05-04
MPCPy-master\doc\userGuide\MPCPyUserGuide.pdf, 311952 , 2018-05-04
MPCPy-master\doc\userGuide\Makefile, 4111 , 2018-05-04
MPCPy-master\doc\userGuide\__init__.py, 1 , 2018-05-04
MPCPy-master\doc\userGuide\make.bat, 7270 , 2018-05-04
MPCPy-master\doc\userGuide\source, 0 , 2018-05-04
MPCPy-master\doc\userGuide\source\acknowledgements.rst, 751 , 2018-05-04
MPCPy-master\doc\userGuide\source\conf.py, 9601 , 2018-05-04
MPCPy-master\doc\userGuide\source\disclaimers.rst, 1089 , 2018-05-04
MPCPy-master\doc\userGuide\source\exodata.rst, 54 , 2018-05-04
MPCPy-master\doc\userGuide\source\gettingStarted.rst, 3968 , 2018-05-04
MPCPy-master\doc\userGuide\source\images, 0 , 2018-05-04
MPCPy-master\doc\userGuide\source\images\SoftwareArchitecture.png, 90478 , 2018-05-04
MPCPy-master\doc\userGuide\source\images\logo.png, 6540 , 2018-05-04
MPCPy-master\doc\userGuide\source\index.rst, 220 , 2018-05-04
MPCPy-master\doc\userGuide\source\introduction.rst, 4027 , 2018-05-04
MPCPy-master\doc\userGuide\source\license.rst, 3327 , 2018-05-04
MPCPy-master\doc\userGuide\source\models.rst, 50 , 2018-05-04
MPCPy-master\doc\userGuide\source\optimization.rst, 74 , 2018-05-04
MPCPy-master\doc\userGuide\source\systems.rst, 54 , 2018-05-04
MPCPy-master\doc\userGuide\source\testing.rst, 58 , 2018-05-04
MPCPy-master\doc\userGuide\source\units.rst, 46 , 2018-05-04
MPCPy-master\doc\userGuide\source\utility.rst, 54 , 2018-05-04
MPCPy-master\doc\userGuide\source\variables.rst, 92 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial, 0 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial\Constraints.csv, 1556 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial\ControlSignal.csv, 1142 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial\Parameters.csv, 152 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial\Tutorial.mo, 2284 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial\USA_IL_Chicago-OHare.Intl.AP.725300_TMY3.epw, 1648753 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial\__init__.py, 1 , 2018-05-04
MPCPy-master\doc\userGuide\tutorial\introductory.py, 22244 , 2018-05-04
MPCPy-master\legal.txt, 893 , 2018-05-04
MPCPy-master\license.txt, 2433 , 2018-05-04
MPCPy-master\mpcpy, 0 , 2018-05-04
MPCPy-master\mpcpy\__init__.py, 1 , 2018-05-04
MPCPy-master\mpcpy\exodata.py, 69292 , 2018-05-04
MPCPy-master\mpcpy\models.py, 42818 , 2018-05-04
MPCPy-master\mpcpy\optimization.py, 34980 , 2018-05-04
MPCPy-master\mpcpy\systems.py, 9484 , 2018-05-04
MPCPy-master\mpcpy\units.py, 34106 , 2018-05-04
MPCPy-master\mpcpy\utility.py, 34084 , 2018-05-04
MPCPy-master\mpcpy\variables.py, 15008 , 2018-05-04
MPCPy-master\occupant, 0 , 2018-05-04
MPCPy-master\occupant\__init__.py, 424 , 2018-05-04
MPCPy-master\occupant\adaptive, 0 , 2018-05-04
MPCPy-master\occupant\adaptive\__init__.py, 268 , 2018-05-04
MPCPy-master\occupant\occupancy, 0 , 2018-05-04
MPCPy-master\occupant\occupancy\__init__.py, 234 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing, 0 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\README.md, 250 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\__init__.py, 187 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\adaptive_breakpoint_placement.py, 6942 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\interp1.py, 690 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\occupancy_prediction.py, 4932 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\parameter_inference.py, 782 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\parameter_inference_given_segments.py, 574 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\simulate_queue.py, 4333 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\temp.npy, 240 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\test_functions.py, 2917 , 2018-05-04
MPCPy-master\occupant\occupancy\queueing\unique_last.py, 532 , 2018-05-04
MPCPy-master\resources, 0 , 2018-05-04
MPCPy-master\resources\weather, 0 , 2018-05-04
MPCPy-master\resources\weather\BuildingsEPWReader.fmu, 791026 , 2018-05-04
MPCPy-master\resources\weather\WeatherProcessor_Dymola_v1.fmu, 1711019 , 2018-05-04
MPCPy-master\resources\weather\WeatherProcessor_JModelica_v2.fmu, 612063 , 2018-05-04
MPCPy-master\unittests, 0 , 2018-05-04
MPCPy-master\unittests\.err, 84 , 2018-05-04
MPCPy-master\unittests\__init__.py, 1 , 2018-05-04
MPCPy-master\unittests\outputs, 0 , 2018-05-04
MPCPy-master\unittests\outputs\model_parameters.txt, 2005 , 2018-05-04
MPCPy-master\unittests\references, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ConstraintFromCSV, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ConstraintFromCSV\collect_data.csv, 1127 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ConstraintFromDF, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ConstraintFromDF\collect_data.csv, 1127 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ConstraintFromOccupancyModel, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ConstraintFromOccupancyModel\collect_data.csv, 34691 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ControlFromCSV, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ControlFromCSV\collect_data.csv, 497 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ControlFromDF, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\ControlFromDF\collect_data.csv, 497 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\InternalFromCSV, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\InternalFromCSV\collect_data.csv, 1654 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\InternalFromOccupancyModel, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\InternalFromOccupancyModel\collect_data.csv, 38632 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\OtherInputFromCSV, 0 , 2018-05-04
MPCPy-master\unittests\references\test_exodata\OtherInputFromCSV\collect_data.csv, 134 , 2018-05-04

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • AdaptiveGPC
    自适应广义预测控制S函数程序,能够直接用于SIMULINK中,进行预测控制研究(Adaptive Generalized Predictive Control S function process for SIMULINK in directly for Predictive Control of)
    2008-12-10 15:25:00下载
    积分:1
  • bianyaqi
    变压器设计软件,采用CAD技术改造变压器传统设计(Transformer design software, the use of CAD technology traditional transformer design)
    2008-02-26 08:45:16下载
    积分:1
  • Perl_Script_Repository
    Perl Script Repository资料库Perl脚本!这里是众多作者根据工作的应用而编写的脚本~非常值得学习!(There are many Perl programmers in the world. So many, in fact, that there is probably someone who has already written a script which identifies a solution to a problem you may have. In an ideal world it would be easy to locate these individuals so that you could ask them how they solved your particular problem. Since this world is far from ideal we are attempting to make it just a bit nicer with this scripts page. Here one can find a plethora of Perl scripts with descriptions on how they work as well as information about the author of the script. )
    2009-06-04 04:06:20下载
    积分:1
  • 6apsk信噪比与误码率的关系曲线 星座图
    说明:  16apsk信噪比与误码率的关系曲线 星座图(Constellation diagram of the relationship between signal-to-noise ratio (SNR) and bit error rate (BER) of 16APSK)
    2019-06-01 18:37:21下载
    积分:1
  • mcmc
    说明:  MCMC方法是一种重要的模拟计算方法,马尔可夫链蒙特卡尔理论(Markov chain Monte Carlo:MCMC)的研究对建立可实际应用的统计模型开辟了广阔的前景。90年代以来,很多应用问题都存在着分析对象比较复杂与正确识别模型结构的困难。现在根据MCMC理论,通过使用专用统计软件进行MCMC模拟,可解决许多复杂性问题。此外,得益于MCMC理论的运用,使得贝叶斯(Bayes)统计得到了再度复兴,以往被认为不可能实施计算的统计方法变得是很轻而易举了。(The MCMC method is an important simulation method. The research of Markov chain Monte Carlo:MCMC (Markov) has opened up a broad prospect for the establishment of a practically applicable statistical model. Since 90s, many application problems have been difficult to analyze the complexity of the analysis objects and to identify the structure of the model correctly. Now, according to the MCMC theory, MCMC simulation can be done by using special statistical software to solve many complex problems. In addition, thanks to the application of MCMC theory, Bias's (Bayes) statistics has been revived again, and the statistical method which was previously considered impossible to carry out the calculation became very easy.)
    2018-01-22 20:07:07下载
    积分:1
  • C语言实现的python里面的filtfilt函数
    说明:  使用C语言实现了零相滤波器算法程序,优化了资源(Zero phase filter program realized by C program)
    2021-03-18 17:29:19下载
    积分:1
  • 模拟网站登陆,极小型数据库系统
    模拟网站登陆,极小型数据库系统-simulated landing site, a very small database system
    2022-02-02 06:06:57下载
    积分:1
  • 参数辨识
    可以做到电池参数识别,特别是二阶rc电路的参数识别,(Can do battery parameter identification,In particular,parameter identification of second-order rc circuits.)
    2019-04-08 10:26:28下载
    积分:1
  • 下垂控制器
    多分布式电源的下垂控制器和PQ控制器设计(Design of droop controller and PQ controller for multi - distributed power supply)
    2017-07-19 14:46:46下载
    积分:1
  • 077404
    改进的粒子群算法--自适应粒子群算法,在普通的粒子群算法里面加入了熵和(Improved particle swarm optimization (pso) algorithm, adaptive particle swarm optimization (pso) algorithm, in the ordinary course of joined the entropy and particle swarm optimization (pso) algorithm)
    2017-08-13 07:11:54下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载