"Simplicity is a key objective in our solutions, providing performance criteria can be met."
We know control engineering inside out. An in-depth understanding of control technologies together with first-hand experience in diverse industrial applications uniquely positions us to deliver exceptional value to our clients.
Our control engineering services cover the following:
We help clients define and design effective control strategies from simple classical feedback or feedforward to advanced control.
A proper assessment of the process as a whole is undertaken, including effects on neighbouring/coupled systems and processes. Control objectives, disturbances, nonlinearities, uncertainties, robustness and noise immunity are all considered when a control strategy is developed.
Solutions can range from simple classical feedback or feedforward to advanced control, such as model-based methods like MPC or methods like Fuzzy Logic control. However, simplicity is a key objective in our solutions, providing performance criteria can be met.
Many of our control design projects involve the development of a nonlinear dynamic model to assess effectiveness in simulation. This allows the new control solution to be compared against the existing to quantify benefits, and then be deployed with confidence.
We have experience with a range of predictive and other advanced control algorithms and software packages, varying from the standard MATLAB Model Predictive Control Toolbox to our own advanced tools for nonlinear MPC (NMPC) and nonlinear generalised minimum variance (NGMV) control.
We provide clients with full implementation using the National Instruments series of hardware targets for LabVIEW (e.g. CompactRIO and FPGA, PXI).
Where full implementation is not required, we can offer implementation support to the client.
ISC developed a first principles model of this novel process for use on an offshore oil platform. This was to de-risk and refine the process design as it went through the design and factory testing phases, so that our client had much greater confidence of the system working properly as it moved to final commissioning and use.
The model was able to replicate system operation in all expected produced water flow rates and quality, and we were able to refine recommended operational procedures, control strategy and loop tuning.
ISC developed the control system for a very large pair of Gripper Arms for the jack-up vessel MPI Discovery, used to install the foundation piles for offshore wind turbines. Early simulations were used to assess the hydraulic and control designs prior to the main software development. Since this was for a working boat minimising commissioning time was critical, ISC developed a software-based emulator to allow the software to be fully tested before the mechanical build was available. The emulator has also helped validate minor software revisions now that the system is in-service.
This project won the Application of the Year prize at National Instruments Graphical System Design Achievement Awards.
Model-based predictive control (MPC) was used for Spark Injection (SI) engines to handle constraints and compensate for actuator, process and sensor delays. Nonlinear models were required to represent the nonlinearities and event-based dynamics inherent to automotive engine systems.
Linear Parameter-Varying (LPV) models were found to meet the requirements and were used within the Nonlinear MPC framework to control torque tracking, fuel economy, emissions and drivability.
Model-based design procedures were used to validate the algorithms in simulation and to optimise them for real-time implementation, prior to the successful tests on the engine itself.