Control System development is part of our core business and we count with an experienced team and many achievements with customers worldwide. We use advanced control system techniques and among them our “Model-based Predictive Control” technique, which we have been implemented in our software solutions. We have successful deployed more than 130 control-related projects since 2009.
Thanks to our methodologies, and the model-based predictive control in particular, we are able to manage different control activities:
- Control design of equipment such as valve, pump, compressor, etc.
- Control function: functional control (temperature, speed, throughput rate, etc), braking system, driver assistance function, etc.
- Control of a complex system (air conditioning system, fuel cell system, rolling mill, furnace, etc).
- System optimization with quality objectives and cost reduction. For instance, energy optimization for a vehicle or the management of a refining unit
At earliest stages of the product development:
- Feasibility study and specification of control system requirements
- Accurate control design by systemic modeling to define its software architecture
- Modeling and identification of the system to be controlled
- Control design including control algorithms, fault detection and the associated diagnostic system
- Development of the state chart for operating mode management
- Validation in simulation (Model In the Loop)
- Validation using rapid control prototyping solution (dSPACE, NI) to verify the control principles
Embedded system development
We adapt the control model to the industrial constraints:
- Code generation for the application and SIL validation
- Integration in the embedded system and HIL validation
- Final product verification
- Training to application users
- Application follow-up and maintenance
Methods and tools
Our expert team in control systems has contributed to the development of the Model Based Predictive Control methodology and in particular to the IDCOM-HIECON and PFC (Predictive Functional Control) techniques. This advanced control technique is robust enough to manage the majority of control problems: mono or multi-variable system, complex dynamic behavior, non-linearity, measured disturbances, known setpoint, constraints on the actuators and the state variables.
Cette technique de commande avancée permet de résoudre de façon performante et robuste la majorité des problèmes de commande : système mono ou multi-variables, comportement dynamique compliqué, non linéarités, perturbation mesurée, consigne connue dans le future, ou contraintes sur les actionneurs et sur les variables d’état du système.
We mostly work on a Simulink environment for the control system development and for this purpose we have developed our own product, PhiControl, a Simulink library for the design and simulation of model-based predictive control systems.
We propose the following training modules (for more information go to the training) :
|MPC1||Theory and applications of functional predictive control||2 days|
|MPC2||Introduction to multi-variable predictive control and practical exercises||3 days|
|CCS1||Control systems||3 days|
|DLA1||Dynamic linear system analysis||3 days|
Key commercial references
|2003-14||Constellium||Advanced control of thickness for single and multi-stand rolling mill||1 person|
|2006-09||PSA||Design and validation of a control system for a fuel cell system||28 person.month|
|2006-08||Valeo||Control of a valve of used to manage the cooling system||10 person.month|