Advanced PID architectures for tracking changing active constraints

The research explores Advanced Regulatory Control (ARC), also known as advanced PID architectures, as a robust and straightforward methodology for managing processes characterized by dynamic and potentially conflicting constraints. This approach challenges the conventional academic belief that only model-based solutions, such as Model Predictive Control (MPC), are effective for such complex scenarios. The efficacy of ARC is demonstrated through two distinct case studies. The first involves a gas-liquid separation process, where a combination of selectors and split-parallel control is employed to achieve bidirectional inventory control. This configuration enables the throughput manipulator to automatically adjust to the most optimal operational point. The second case study focuses on maintaining acceptable air quality,

specifically CO2 levels, and temperature within an enclosed environment, such as a barn. In this scenario, the CO2 and temperature constraints can be contradictory, necessitating a hierarchical switching network of PID controllers to manage these conflicting objectives effectively. The study provides simulation-based evidence supporting the practical application and performance of these advanced PID architectures in diverse industrial and environmental control challenges.

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