Background:
Chemical processes with delay are challenging to control due to the inherent phase lag, sluggish response, and stability issues. These challenges are further amplified when the process exhibits unstable or integrating dynamics, such as in the case of continuously stirred tank reactors (CSTRs). Conventional control techniques often struggle to achieve satisfactory performance and robust stability in such scenarios.
Methods:
To address these issues, this work proposes a generalized Internal Model Control (IMC)–based Proportional Derivative (PD) decoupled dual-loop control framework. The inner PD controller is designed using Routh–Hurwitz stability criteria to ensure closed-loop stability. The IMC filter parameter and PD controller gains are jointly fine-tuned through a stability-constrained Crayfish Optimization Algorithm, which is employed for the first time in this context. The optimization objective is to minimize the Integral Square Error (ISE), ensuring both performance and robustness.
Significant Findings:
The proposed control structure is validated using several benchmark chemical process models from the literature, demonstrating significant improvements in performance and robustness over existing methods. Furthermore, experimental validation is carried out to assess the practical applicability and effectiveness of the design in real-world conditions.
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