Quadratic interpolation optimization-based 2DoF-PID controller design for highly nonlinear continuous stirred-tank heater process
Status PubMed-not-MEDLINE Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
CZ.10.03.01/00/22_003/0000048
European Union
TN02000025
National Centre for Energy II
101139527
ExPEDite (European Union's Horizon Mission Programme)
PubMed
40348876
PubMed Central
PMC12065853
DOI
10.1038/s41598-025-01379-3
PII: 10.1038/s41598-025-01379-3
Knihovny.cz E-zdroje
- Klíčová slova
- Degrees, Freedom (2DoF, Of, PID) control scheme, continuous stirred, Quadratic interpolation optimization, two, Tank heater (CSTH), metaheuristic tuning methods, control of industrial processes,
- Publikační typ
- časopisecké články MeSH
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.
Applied Science Research Center Applied Science Private University Amman 11931 Jordan
Department of Computer Engineering Istanbul Gedik University Istanbul 34876 Turkey
Department of Electrical and Electronics Engineering Bursa Uludag University Bursa 16059 Turkey
Department of Electrical Engineering Graphic Era Dehradun 248002 India
Distance Education Application and Researcher Center Batman University Batman Turkey
ENET Centre CEET VSB Technical University of Ostrava 708 00 Ostrava Czech Republic
Graphic Era Hill University Dehradun 248002 India
Hourani Center for Applied Scientific Research Al Ahliyya Amman University Amman Jordan
Jadara University Research Center Jadara University Irbid Jordan
Zobrazit více v PubMed
Rojas, J. D., Arrieta, O. & Vilanova, R. Industrial PID controller tuning. DOI
Alfaro, V. M. & Vilanova, R.
Thornhill, N. F., Patwardhan, S. C. & Shah, S. L. A continuous stirred tank heater simulation model with applications. DOI
Sehgal, S., & Acharya, V. Design of PI controller for continuous stirred tank heater process. In
Sharma, M. K., & Kumar, A. Performance comparison of brain emotional learning-based intelligent controller (BELBIC) and PI controller for continually stirred tank heater (CSTH). In
Li, X. & Jiang, X. Teaching Process Control Using the CSTH Model. In
Gao, T., Luo, H., Yin, S. & Kaynak, O. A recursive modified partial least square aided data-driven predictive control with application to continuous stirred tank heater. DOI
Mahmood, Q. A. & Nawaf, A. T. Performance analysis of continuous stirred tank heater by using PID-cascade controller. DOI
Balaji, S., & Kadirvelu, T. Reinforcement Learning Based Adaptive PID Controller for a Continuous Stirred Tank Heater Process. 10.30492/ijcce.2024.2029225.6615 (2024).
Iqbal, J., Ullah, M., Khan, S. G., Khelifa, B. & Ćuković, S. Nonlinear control systems-A brief overview of historical and recent advances. DOI
Baños, A., Lamnabhi-Lagarrigue, F., & Montoya, F. J. (Eds.).
Stankovic, M., Ting, H. & Madonski, R. From PID to ADRC and back: Expressing error-based active disturbance rejection control schemes as standard industrial 1DOF and 2DOF controllers. DOI
Ghosh, A. et al. Design and implementation of a 2-DOF PID compensation for magnetic levitation systems. PubMed DOI
Sahu, R. K., Panda, S., Rout, U. K. & Sahoo, D. K. Teaching learning based optimization algorithm for automatic generation control of power system using 2-DOF PID controller. DOI
Roy, R. et al. Investigation of 2DoF-PID controller for physio-therapeutic application for elbow rehabilitation. DOI
Yuan, Y., Lv, H. & Zhang, Q. DNA strand displacement reactions to accomplish a two-degree-of-freedom PID controller and its application in subtraction gate. PubMed DOI
Dong, S., Hao, L., Shao, Y., Liu, J., & Han, L. (2023, October). Two-Degrees-of-Freedom PID Control with Kalman Filter for Engraving Machine System. In
Dhanasekar, R. & Vijayachitra, S. Modeling and Control of Non-Linear CSTH Process using Hybrid Optimized Technique: Optimal Control of The CSTH Process. DOI
Wu, X., Yang, X. & Qiu, J. A Novel Adaptive Subspace Predictive Control Approach With Application to Continuous Stirred Tank Heater. DOI
Oyelade, O. N., Ezugwu, A. E. S., Mohamed, T. I. & Abualigah, L. Ebola optimization search algorithm: A new nature-inspired metaheuristic optimization algorithm. DOI
Hashim, F. A. & Hussien, A. G. Snake Optimizer: A novel meta-heuristic optimization algorithm. DOI
Abualigah, L. et al. Aquila optimizer: a novel meta-heuristic optimization algorithm. DOI
Joshi, A. S., Kulkarni, O., Kakandikar, G. M. & Nandedkar, V. M. Cuckoo search optimization-a review. DOI
Qu, S. et al. Application of spiral enhanced whale optimization algorithm in solving optimization problems. PubMed DOI PMC
Storn, R. & Price, K. Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. DOI
Wang, D., Tan, D. & Liu, L. Particle swarm optimization algorithm: an overview. DOI
Ghasemi, M. et al. Flood algorithm (FLA): an efficient inspired meta-heuristic for engineering optimization. DOI
Abdollahzadeh, B., Gharehchopogh, F. S., Khodadadi, N. & Mirjalili, S. Mountain gazelle optimizer: a new nature-inspired metaheuristic algorithm for global optimization problems. DOI
Zhao, W. et al. Quadratic Interpolation Optimization (QIO): A new optimization algorithm based on generalized quadratic interpolation and its applications to real-world engineering problems. DOI
Izci, D. et al. Dynamic load frequency control in Power systems using a hybrid simulated annealing based Quadratic Interpolation Optimizer. PubMed DOI PMC
Izci, D. & Ekinci, S. An improved RUN optimizer based real PID plus second-order derivative controller design as a novel method to enhance transient response and robustness of an automatic voltage regulator. DOI
Jabari, M. et al. A novel artificial intelligence based multistage controller for load frequency control in power systems. PubMed DOI PMC
Izci, D., Ekinci, S. & Hussien, A. G. An elite approach to re-design Aquila optimizer for efficient AFR system control. PubMed DOI PMC