Tuning is often a time consuming and complicated process. Even well identified systems may be hard to tune due to the complex subsystems and process requirements involved.


Good results in control optimization is the key to process excellence, allowing for ever more advanced and efficient control solutions.


At Netta Solutions we provide control optimization, including PID controller tuning and redesign of control structures.


We offer bespoke tuning services with a focus on performance and efficiency based on technological process subtleties and customer requirements.

Simulator and modelling


There are a number of ways how simulators can be beneficial for plant and process optimization:


  • Operator training – using “what if” scenarios in simulators increases plant availability and improves safety

  • Digital twin technology gives a better insight into the technological processes of the plant, enabling engineers to optimize performance and efficiency

  • Well built simulators provide a good testing ground for newly installed control systems and thus reduce the time spent on commissioning and startup.


Netta Solutions provides ISA compliant plant simulators which could be embedded into control systems or provided as third party application.

We have completed a number of successful simulation and modelling projects helping us to improve plant performance and deliver fully realized control systems on time.

Advanced Control Methods


Netta Solutions has developed several control applications for highly time dependent, non linear processes that involve complex systems such as foundry switchgear control and coal analysis from a lignite surface pit. We use expert analysis as a tool for statistical interpretation of historical data in order to develop a fuzzy or neural network based control system.


Netta Solutions is able to develop an expert system for a technological process where a profile of historical data is available. In cases whereby the expert system is to be installed on a new application, self learning algorithms can be implemented.