Cybernetica CENITCybernetica
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Related Products
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About
Cybernetica delivers Nonlinear Model Predictive Control (NMPC) based on mechanistic models. Our software product, Cybernetica CENIT, offers a flexible architecture that can meet any industrial challenge with optimal solutions. Multivariable optimal control, predictive control, intelligent feed forward, optimal constraint handling. Adaptive control through state and parameter estimation, and feedback from indirect measurements through the process model. Nonlinear models are valid over larger operating ranges. Improved control of nonlinear processes. Less need for step-response experiments and improved state and parameter estimates. Control of batch and semi-batch processes, control of nonlinear processes operated under varying conditions. Optimal grade transition in continuous processes. Safe control of exothermal processes and control of unmeasured variables, such as conversion rates and product quality. Reduced energy consumption and carbon footprint.
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About
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. While MPCPy provides an integration platform, it relies on free, open-source, third-party software packages for model implementation, simulators, parameter estimation algorithms, and optimization solvers. This includes Python packages for scripting and data manipulation as well as other more comprehensive software packages for specific purposes. In particular, modeling and optimization for physical systems currently rely on the Modelica language specification.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Industrial companies and plants requiring a solution to improve their adaptive control through state and parameter estimation processes
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Audience
Plants and companies requiring an open-source platform to improve their Model Predictive Control (MPC) in their buildings
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationCybernetica
Norway
cybernetica.no/technology/model-predictive-control/
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Company InformationMPCPy
United States
github.com/lbl-srg/MPCPy
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Categories |
Categories |
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Integrations
Python
Ubuntu
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