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A novel auto-tuning PID control mechanism for nonlinear systems.
ISA Trans 2015; 58:292-308IT

Abstract

In this paper, a novel Runge-Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence.

Authors+Show Affiliations

Pamukkale University, Department of Computer Engineering, Kinikli Campus, 20070 Denizli, Turkey. Electronic address: mcetin@pau.edu.tr.Pamukkale University, Department of Electrical and Electronics Engineering, Kinikli Campus, 20070 Denizli, Turkey. Electronic address: iplikci@pau.edu.tr.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

26117284

Citation

Cetin, Meric, and Serdar Iplikci. "A Novel Auto-tuning PID Control Mechanism for Nonlinear Systems." ISA Transactions, vol. 58, 2015, pp. 292-308.
Cetin M, Iplikci S. A novel auto-tuning PID control mechanism for nonlinear systems. ISA Trans. 2015;58:292-308.
Cetin, M., & Iplikci, S. (2015). A novel auto-tuning PID control mechanism for nonlinear systems. ISA Transactions, 58, pp. 292-308. doi:10.1016/j.isatra.2015.05.017.
Cetin M, Iplikci S. A Novel Auto-tuning PID Control Mechanism for Nonlinear Systems. ISA Trans. 2015;58:292-308. PubMed PMID: 26117284.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A novel auto-tuning PID control mechanism for nonlinear systems. AU - Cetin,Meric, AU - Iplikci,Serdar, Y1 - 2015/06/24/ PY - 2014/05/07/received PY - 2015/05/20/revised PY - 2015/05/27/accepted PY - 2015/6/29/entrez PY - 2015/6/29/pubmed PY - 2015/6/29/medline KW - Auto-tuning KW - MIMO PID controller design KW - Model-based predictive control KW - PID controller KW - Real-time control SP - 292 EP - 308 JF - ISA transactions JO - ISA Trans VL - 58 N2 - In this paper, a novel Runge-Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence. SN - 1879-2022 UR - https://www.unboundmedicine.com/medline/citation/26117284/A_novel_auto_tuning_PID_control_mechanism_for_nonlinear_systems_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0019-0578(15)00134-2 DB - PRIME DP - Unbound Medicine ER -