Lyapunov-based adaptive PID controller design for buck converter

被引:21
作者
Ghamari, Seyyed Morteza [1 ]
Khavari, Fatemeh [1 ]
Mollaee, Hasan [1 ]
机构
[1] Shahrood Univ Technol, Fac Elect Engn, Shahrood, Iran
关键词
Buck converter; Lyapunov stability; PID controller; PSO algorithm; Noise;
D O I
10.1007/s00500-022-07797-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a Lyapunov-based model reference proportional-integrated-derivative (PID) is designed using this approach for a DC / DC Buck converter. However, under a wider range of disturbances, the PID strategy is not suitable for practical applications, and the parameters must be tuned again for more reliable operations. To this end, a Lyapunov definition-based adaptive mechanism is adopted for the PID strategy, which can increase the stability and robustness of this scheme under various disturbances. Moreover, the system is considered a black-box without the need for accurate mathematical modeling of the system that can result in a lower computational burden as well as ease of implementation. The Lyapunov concept is a modern adaptive algorithm that can find optimal answers in shorter periods with more accuracy and reliable stability insurance. To examine the strength of this method, conventional fractional-order PID (FOPID) and PID control techniques are also tested to be compared with this work using the PSO algorithm to tune their parameters. Finally, the results related to both simulations and experimental outputs are tested, showing faster dynamics and significant robustness of Lyapunov-based PID strategy in different challenging scenarios.
引用
收藏
页码:5741 / 5750
页数:10
相关论文
共 30 条
[1]   Control of a Buck DC/DC Converter Using Approximate Dynamic Programming and Artificial Neural Networks [J].
Dong, Weizhen ;
Li, Shuhui ;
Fu, Xingang ;
Li, Zhongwen ;
Fairbank, Michael ;
Gao, Yixiang .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2021, 68 (04) :1760-1768
[2]  
Ekinci S, 2019, 3 INT S MULT STUD IN
[3]  
Ekinci S, 2019, INT ARTIFICIAL INTEL
[4]  
Emami SA, 2008, 2008 INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION: (ICMA), VOLS 1 AND 2, P519
[5]  
Erickson R W., 2007, Wiley Encyclopedia of Electrical and Electronics Engineering, DOI DOI 10.1002/047134608X.W5808.PUB2
[6]   Robust self-tuning regressive adaptive controller design for a DC-DC BUCK converter [J].
Ghamari, S. Morteza ;
Mollaee, Hasan ;
Khavari, Fatemeh .
MEASUREMENT, 2021, 174
[7]   Generalised model predictive controller design for A DC-DC non-inverting buck-boost converter optimised with a novel identification technique [J].
Ghamari, Seyyed Morteza ;
Khavari, Fatemeh ;
Molaee, Hasan ;
Wheeler, Patrick .
IET POWER ELECTRONICS, 2022, 15 (13) :1350-1364
[8]   Fractional-order fuzzy PID controller design on buck converter with antlion optimization algorithm [J].
Ghamari, Seyyed Morteza ;
Narm, Hossein Gholizade ;
Mollaee, Hasan .
IET CONTROL THEORY AND APPLICATIONS, 2022, 16 (03) :340-352
[9]   PID controller modifications to improve steady-state performance of digital controllers for buck and boost converters [J].
Guo, LP ;
Hung, JY ;
Nelms, RM .
APEC 2002: SEVENTEENTH ANNUAL IEEE APPLIED POWER ELECTRONICS CONFERENCE AND EXPOSITION, VOLS 1 AND 23, 2002, :381-388
[10]   Lyapunov based adaptive controller for power converters used in hybrid energy storage systems [J].
Hassan, Mudasser ;
Paracha, Zahir Javed ;
Armghan, Hammad ;
Ali, Naghmash ;
Said, Hafiz Ahsan ;
Farooq, Umar ;
Afzal, Ammar ;
Hassan, Muhammad Arshad Shehzad .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2020, 42