Virtual Commissioning using Simulink – Part 2: Virtual Commissioning


Many industries are facing increasingly complex algorithms deployed in production systems to achieve greater productivity. In addition, the cost of downtime for implementing improvements in control software can be prohibitive. Today, companies are tuning to virtual commissioning to address these two issues. Mining companies can leverage virtual commissioning to ensure new control algorithms will be reliable, achieve desired results, and be implemented seamlessly with minimal downtime.

Virtual commissioning uses dynamic models to design and validate algorithms for improved productivity. After validation, these algorithms can be automatically deployed to a simulated PLC, where the code running on the PLC is tested against the plant model. 

This seminar focuses on two aspects of virtual commissioning: design with simulation, and implementation with code generation. You will see the workflow demonstrated using a common challenge across mining companies: a multi-tank level control problem.

Part 2: Virtual Commissioning 

After developing and validating a control strategy in simulation, the control algorithm is deployed to an embedded platform common in the mining industry: a Programmable Logic Controller (PLC). The generated code is validated by running the code on a simulated PLC that is connected to the Simulink plant model prior to implementation on the real system. This part of the seminar highlights the ease of generating PLC code from a designed algorithm to provide a short reliable path from design to production implementation. 

Go to Virtual Commissioning using Simulink – Part 1: Design with Simulation
Go to Mining Seminar Series Overview page

About the Presenter

Ruth-Anne Marchant
Ruth-Anne Marchant is a Senior Application Engineer specializing in Simulink, and Model-Based Design. Since joining MathWorks in 2015, her focus is on supporting customers adopt Model-Based Design with Simulink. Prior to joining MathWorks, Ruth-Anne worked in the Canadian aerospace industry as a control systems engineer. Ruth-Anne holds a BASc in computer engineering and an MASc in electrical and computer engineering, both from the University of Waterloo, Canada, specializing in control systems

Branko Dijkstra
Branko Dijkstra is a principal technical consultant specializing in Model-Based Design workflows for process industry optimization. Prior to joining MathWorks, Branko was an engineering manager for the development of automotive climate control and electric vehicle thermal management systems. Before that, he worked in the microlithography industry. Branko received his M.E. based on his work modeling a batch crystallization plant. He received his Ph.D. in control engineering (microlithography) from Delft University of Technology, the Netherlands based on his thesis Iterative Learning Control Applied to a Wafer Stage.

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