Advanced Process Control

Process Control

Advanced process control technology utilises smart software solutions to optimise process operations and maximise return on plant assets in real time. Based on our past experience, the benefits of increased production, reduced quality variability and lower energy consumption can result in a return on investment within months.

Recent Projects include:

  • Gold and Copper ball mill online optimal control
  • Gold and Copper flotation cells optimal recovery control
  • Train load out wagon weight optimal control

Model Predictive Control

Model predictive control aims to minimise the difference between the modelled projections of a process and the optimal trajectory which we want to maintain. This is achieved through complex predictive modelling, which then allow the control system to take corrective action in advance, to ensure the process remains within the optimal trajectory in the future.

Advanced regulatory control (ARC) refers to several proven advanced control techniques, such as feedforward, override or adaptive gain, interaction and decoupling as well as complex cascade loops.  Generally this level of control is maintained within a facility’s DCS or PLC system.

Expert systems are computer software systems that mimic the tasks routinely carried out by experts (process plant operators). Usually, the domain of expertise of these systems is restricted to a well-defined area. Expert systems can be thought of as a storehouse of knowledge with efficient ways of retrieving this knowledge to solve the problem at hand. Expert systems are valuable because they can serve as a permanent storehouse of knowledge that is widely accessible. Effectively it is programming your control system to take the same actions as your most experienced operators in an automated and consistent manner.

Controllers are designed to eliminate the need for continuous operator attention when controlling a process. In the automatic mode, the goal is to keep the controlled variable (or process variable) on set point. The controller tuning
parameters determine how well the controller achieves this goal when in automatic mode.

The team at Resources Optimisation are experts in tuning regulatory control loops as well as sequence control.