1.      Platform Introduction   

Industrial process control means automatic control of controlled variables, namely process parameters such as temperature, pressure, flow, liquid level, and components. Traditional industrial process control experiment devices use physical equipment such as water tanks, pumps, valves, and frequency converters as the basis to construct a simplified industrial process control device prototype. This kind of traditional experiment device can help students get a direct impression of pumps, valves, and other equipment, but it has limitations. The multifunction industrial process control experiment device that we introduce, based on real-time simulation equipment, can cover all kinds of experiment contents such as liquid level control, temperature control, virtual instrument monitoring, etc. while adapting to changes in simulation models.

2.      Platform Features   

1. Small-Sized: Traditional process control experiment devices are often large-sized. Our real-time simulation device can greatly reduce the space occupied by experiment equipment.
2. Rich Experiment Contents: By switching among different simulation models, users can switch among the water-tank liquid level control experiment device, boiler temperature control experiment device, virtual instrument experiment device, and so on flexibly.
3. Convenience For Secondary Development: The real-time simulation device supports multi-field modeling tools such as Matlab Simulink, AMESim, and SimulationX. Users can create industrial control experiment systems of their own characteristics very conveniently.
4. Capable of Simulating Complex Systems: Actual industrial production processes usually involve a series of production devices. During teaching experiments, due to various factors such as fund, place, and safety restrictions, usually industrial processes are only partially displayed, which is not very helpful in terms of helping students form the concept of full-production-line control. Our platform, based on real-time simulation equipment, can use virtual-actual methods to replace complex systems with digital models, while integrating some physical equipment, such as valves and PLC controllers, thus enabling HIL simulation experiments of large complex systems.

3.      Experiment Contents 

• Linear (single-tank/two-tank/three-tank) water tank control experiment;
• Non-linear water tank control experiment;
• Boiler/reaction still temperature/liquid level control experiment;
• Intelligent process control experiment (cascade neural network, BP neural network, fuzzy PID, etc).

4.      Model Selection and Configuration