INCA MPC

INCA MPC

Inca Tools
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About

Advanced Process Control (APC) is a very cost-effective way to optimize your plant performance without changing the hardware. An APC application stabilizes the operation and optimizes production and/or energy consumption. A very valuable side effect also results in a better understanding of your production process. Advanced process control (APC) refers to a broad range of techniques and technologies that interact with the base layer process control systems (built up with PID controls). Some APC technologies are e.g. LQR, LQC, H_infinity, Neural, fuzzy, and MPC (Model-Based Predictive Control). An APC application optimizes your plant every minute, over and over again, 24 hours per day, 7 days per week. MPC is the most popular APC technology used in the industry. The Model Predictive Control software uses a model of the process to predict the behavior of the plant in the foreseeable future. Typically a couple of minutes to even several hours ahead.

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

Enterprises interested in a solution to stabilizes their operations and optimize their plant performance

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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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

Inca Tools
Netherlands
www.incatools.com/advanced-process-control/

Company Information

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

Alternatives

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Cybernetica CENIT

Cybernetica

Alternatives

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Cybernetica CENIT

Cybernetica
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AVEVA APC

AVEVA
PlantPAx

PlantPAx

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COLUMBO

COLUMBO

PiControl Solutions
COLUMBO

COLUMBO

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INCA MPC

INCA MPC

Inca Tools
Pavilion8

Pavilion8

Rockwell Automation
AVEVA APC

AVEVA APC

AVEVA

Categories

Categories

Integrations

Python
Ubuntu

Integrations

Python
Ubuntu
Claim INCA MPC and update features and information
Claim INCA MPC and update features and information
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Claim MPCPy and update features and information