Cybernetica CENIT

Cybernetica CENIT

Cybernetica
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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.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Industrial companies and plants requiring a solution to improve their adaptive control through state and parameter estimation processes

Audience

Plants and companies requiring an open-source platform to improve their Model Predictive Control (MPC) in their buildings

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Cybernetica
Norway
cybernetica.no/technology/model-predictive-control/

Company Information

MPCPy
United States
github.com/lbl-srg/MPCPy

Alternatives

Aspen DMC3

Aspen DMC3

Aspen Technology

Alternatives

Cybernetica CENIT

Cybernetica CENIT

Cybernetica
COLUMBO

COLUMBO

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AVEVA APC

AVEVA APC

AVEVA
INCA MPC

INCA MPC

Inca Tools
COLUMBO

COLUMBO

PiControl Solutions
AVEVA APC

AVEVA APC

AVEVA

Categories

Categories

Integrations

Python
Ubuntu

Integrations

Python
Ubuntu
Claim Cybernetica CENIT and update features and information
Claim Cybernetica CENIT and update features and information
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