Why a Virtual Plant Is Crucial for Process Control Improvement

The following tip is from the ISA book by Greg McMillan and Hunter Vegas titled 101 Tips for a Successful Automation Career, inspired by the ISA Mentor Program. This is Tip #99.

101 Tips for a Successful Automation CareerSimulators for system acceptance testing (SAT), operator training systems (OTS), and process control improvement (PCI) should be part of a virtual plant, where a virtual version of the actual control system configuration and graphics, including historian and advanced control tools, interfaced to the simulator are running in a personal computer. The use of a virtualized rather than an emulated control system is necessary to allow the operators, process engineers, and automation engineers and technicians to use the same graphics, trends, and configuration as the actual installation. This fidelity to the actual installation is essential. The emulation of a PID block is problematic because of the numerous and powerful proprietary features, such as anti-reset windup and external-reset feedback.

The simulation used to develop, test, and quantify the benefits of process control improvements can be used as an OTS to help increase onstream time by operator buy-in and understanding particularly for advanced process control (APC). The supportive participation of specialists in the control room is critical as the inevitable questions arise as to what the APC system is doing. An APC system may appear to be taking actions that seem wrong to the operators due to human limitations in understanding complex relationships, delayed effects, and trajectories.

The virtual plant’s processes must be able to be speeded up so that simulations for slow processes can be run within a reasonable time frame (e.g., 1 hour). The speedup can be obtained by increasing kinetics, mass transfer rates, and heat transfer rates and increasing the step size used in the integration of the differential equations for the mass and energy balances. For bioreactors, the speedup requirement is extraordinary because batch cycle times are 7 to 10 days. For bioreactors, the mass transfer rates, heat transfer rates, cell growth rate, and product formation rates are speeded up by a factor of 10. Material and energy balances are speeded up by increasing the integration step size by a factor of 50. The effect is multiplicative, so the total speedup is 500 times real time and a simulated 10 day batch is completed in less than an hour. The flow ranges for gases, nutrients, and reagents must be increased by the same factor as the transfer rate and kinetic speedup. The integrating process gains are increased and the process time constants are decreased by the same factor as the material and energy balance speedup factor. If the loop deadtime is not affected by speedup, the controller gains must be decreased by this same factor to account for the change in integrating process gains or time constants

Concept: The actual displays and trend charts files used in the control room must be copied and the actual configuration downloaded into the virtual plant to provide physical fidelity. The models are speeded up faster than real time to ensure scenarios don’t take too long. The corresponding flow measurement spans and final control element capacities are increased by the same factor as the kinetics and mass transfer rates and heat transfer rates factor. The controller gains are decreased by the same factor as the integration step size factor if the deadtimes are not affected by speedup. The controller gain remains unchanged for step response models where both the deadtime and time constant are speeded up. The controller reset time that is proportional to deadtime is speeded up.

Details: Use step response and first principle models to achieve the fidelity needed (Tip #98) in a virtual plant. Use the “Checklist for a Virtual Plant” in Appendix C. Use speedup factors as necessary so entire simulations take less than an hour. Increase the flow measurement span and final control element capacity by the same factor used to speed up kinetics, mass transfer rate, and heat transfer rate in first principle models. Increase the integration step sizes in these same models to speed up the process time constants and integrating process gains. Decrease the controller gains by the integration speedup factor, assuming that deadtime does not change with speedup. The controller gains are not affected by kinetics and transfer rate speedup if the flow measurement and final control elements are scaled up accordingly. The total model speedup is the kinetics and transfer rates speedup factor multiplied by the integration speedup factor. For step response models, decrease both the deadtime and the time constant so the controller gain does not change with speedup. For these step  response models, decrease the reset time with the speedup factor since the reset time is proportional to the deadtime. See the Control Talk blog “The ABCs of Controller Tuning” to better understand the implications of speedup on tuning.

Watch-outs: The proper simulation of deadtime is notoriously difficult. If the step response deadtime is speeded up, module execution times and measurement sensor responses must also be speeded up unless these are factored into the speedup of the deadtime.

Exceptions: The real-time simulation of momentum balances and water hammer may not be possible because these require exceptionally small integration step sizes. It may be possible to simulate surge by slowing down the dynamics by scaling down the integration step size and implementing the model in a module with an execution time of 0.1 sec.

Insight: A virtual plant provides a level of physical fidelity by the use of the actual plant’s control system and operator interface that is crucial for all types of training and all levels of process control improvement.

Rule of Thumb: Use the actual configuration, displays, and trends that will be in the control room in a virtual plant for the training of operators, maintenance engineers, process engineers, and control engineers and the development, testing, and prototyping of process control improvements.

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