Hardware-in-the-loop simulation platform for supervisory control of mineral grinding process

•A HILS architecture approaching to industrial system is proposed.•A virtual actuator and sensor system is developed to bridge the actual controller and virtual plant.•A configurable software tool for the supervisory control is developed.•A flexible modular 3-D simulation environment for the MGP is provided.

Supervisory control technology is widely used to improve product quality in mineral grinding process (MGP). To ensure safety, new supervisory control method needs to be fully tested before practical application. However, conducting tests in a running process is costly and may put the process equipment in danger, which necessitates extensive simulations to ensure the stability and performance of supervisory controllers. Comparing with the field based test, the numerical simulation is more economic and safer. However, numerical simulations cannot capture all aspects of controlled object, such as sensors, actuators, process, control systems themselves and signal transmissions, which are important to evaluate the control performances. To solve this problem, this paper presents a novel hardware-in-the-loop simulation (HILS) platform for the supervisory control of MGP. By integrating a supervisory control system, a basic loop control system, a virtual actuator and sensor system, and a virtual plant system in to a coherent whole, the HILS platform provides a full-scope simulation environment for the supervisory control. The supervisory control system and the basic loop control system adopt real control systems. The detailed process dynamics are modeled and visualized by the virtual plant system. Further, as an interface between the physical controllers and virtual plant, the virtual actuator and sensor system is used to realize the signal conversion and to simulate the dynamics and faults of the actuators and sensors using data acquisition (DAQ) hardware and configuration software. Effectiveness of platform is demonstrated with a case study, where an intelligent supervisory control method for a typical one stage MGP is tested.

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