Model
predictive
control

The intelligent regulation of systems.

Optimize system management through automated control systems. This application is used to define in advance the effect that the variation of an input will have on the system, resulting in being able to stabilize its control, to increase its efficiency and productivity and to predict the future evolution of the system.

How it works

This technology integrates the technical-engineering know-how necessary to model the system, keeping under control the physic-chemical logic that governs it.

After the process of data preparation and analysis, different predictive models are tested, including all the variables influencing the system, in order to identify the model with the best forecasting performance and the maximum capability to describe the phenomenon.

Predictive control for purification systems

Optimize the control of purification systems automatically.

In systems subject to legal constraints, for example in the treatment of waste water, it is essential to respect the quality parameters imposed, in order to avoid incurring penalties and environmental risks. By exploiting the predictive logic of machine learning, the controller is able to understand the dynamic nature of the system and to automatically adjust the values of the variables in question, reducing the values of pollutants and also the energy consumption of the system.

Predictive control for purification systems

Optimize the control of purification systems automatically.

In systems subject to legal constraints, for example in the treatment of waste water, it is essential to respect the quality parameters imposed, in order to avoid incurring penalties and environmental risks. By exploiting the predictive logic of machine learning, the controller is able to understand the dynamic nature of the system and to automatically adjust the values of the variables in question, reducing the values of pollutants and also the energy consumption of the system.

Predictive control
of HVAC systems

With predictive regulation of HVAC systems, it is possible to improve the comfort and energy management of buildings.

The controller uses the variables of temperature, humidity and crowding to maximize comfort while minimizing energy consumption. The system predicts the daily trend and automatically adjusts the temperature set points and also the time of starting and stopping of the system.

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Case studies

Optimized control of purification systems

Management of the waste water purification system is regulated in advance to minimize the level of pollutants in outlet, while reducing energy consumption. The predictive logics are used to anticipate the variations of the system, reducing the environmental risks.

–8.1% of total nitrogen

+16% energy savings

Automatic regulation of HVAC systems for buildings

Reduction of energy consumption between 16% and 30%