ArticleScientific reports2025
Quadratic interpolation optimization-based 2DoF-PID controller design for highly nonlinear continuous stirred-tank heater process.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Pressure Control of Centrifugal Fan Using Softsign-PI Controller Tuned by Hybrid Starfish Optimization Algorithm with Differential Evolution.Biomimetics (Basel, Switzerland) · 2026Article
- Predictive modeling of controlled drug release from polysaccharide-based systems using gradient boosting and metaheuristic optimization.Scientific reports · 2026Article
- A Biomimetic Gazelle Optimization Approach for Enhanced Temperature Regulation in Electric Furnaces.Biomimetics (Basel, Switzerland) · 2026Article
- Enhanced control of continuous stirred tank reactor with two-degree-of-freedom PID driven by Kirchhoff's law algorithm.Scientific reports · 2026Article
- A novel delay-affected two degree of freedom PID controller using physics-inspired optimization for robust control applications.Scientific reports · 2025Article
- Design of a novel and robust 2-DOF PIDA controller based on enzyme action optimizer for ball position regulation in magnetic levitation systems.Scientific reports · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
Temperature control in continuous stirred tank heater (CSTH) systems is essential for ensuring energy efficiency, safety, and product quality in industrial processes. However, the nonlinear dynamics and external disturbances make conventional proportional-integral-derivative (PID) control inadequate for reliable operation. This study presents a novel two-degrees-of-freedom PID (2DoF-PID) controller optimized using the quadratic interpolation optimization (QIO) algorithm to enhance CSTH temperature regulation. The QIO-based approach allows independent tuning for setpoint tracking and disturbance rejection, overcoming the limitations of classical PID controllers. Extensive nonlinear time-domain simulations, reference tracking, and disturbance rejection tests demonstrate the superior performance of the proposed controller in terms of reduced overshoot, faster settling time, and minimal steady-state error. Furthermore, comparative evaluations with traditional tuning methods (Murrill and Rovira) and several state-of-the-art metaheuristic optimizers (DE, PSO, FLA, MGO) validate the effectiveness and robustness of the QIO-optimized strategy. This work introduces a pioneering application of the QIO algorithm in industrial temperature control, offering a scalable and cost-efficient solution for complex nonlinear systems.
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