For controls engineers developing machinery for factories or plants, simulations are invaluable tools for understanding and improving control systems, particularly with advanced regulatory control techniques such as cascade feedback or model predictive control.
Rather than relying solely on mathematical derivations or trial-and-error methods, Control wrote in a recent article, engineers can use dynamic simulators to represent their processes and evaluate various control strategies under realistic conditions.
Incorporating environmental effects like noise, drift and stiction into these simulations allows for a more accurate representation of real-world phenomena, which are essential when fine-tuning controllers for optimal performance. This approach enables engineers to anticipate the behavior of complex systems, assess process variability, and determine how well controllers perform across a range of operating conditions.
One of the key aspects to consider is distinguishing between deterministic and stochastic simulations. Deterministic simulations provide consistent results, while stochastic simulations account for natural fluctuations and randomness in the process, such as varying inlet humidity or noise in measurements. To learn more, read the full article from Control.
