{"title":"Exact-Feedback-Linearization-Based Adaptive Second-Order Sliding Mode Control Design for DC–DC Boost Converters","authors":"Jinlin Sun;Jun Xia;Shihong Ding;Xinghuo Yu","doi":"10.1109/TIE.2024.3476994","DOIUrl":null,"url":null,"abstract":"The voltage regulation system of a boost converter operating in continuous conduction mode is a typical nonminimum phase system, posing significant challenges for the corresponding controller design. In this article, we employ the exact feedback linearization technique to effectively mitigate the complexities arising from the nonminimum phase characteristic. To address the voltage regulation challenge inherent to the boost converter with various disturbances, we propose an adaptive second-order sliding mode (SOSM) controller formulated within the Lyapunov framework. By dynamically modulating the control gain, the proposed controller circumvents the overestimation issue typical in other SOSM approaches, thereby diminishing chattering induced by excessive gain. In addition, unlike conventional adaptive SOSM methods, the proposed controller requires merely the disturbances to be bounded, without the need for the derivatives of these disturbances to be bounded. On this basis, the proposed controller ensures finite-time stability of the closed-loop system and concurrently enhances its transient response and robustness. Finally, comparative hardware experiments are conducted to demonstrate the effectiveness and superiority of the proposed controller.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 5","pages":"5397-5407"},"PeriodicalIF":7.2000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10740387/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The voltage regulation system of a boost converter operating in continuous conduction mode is a typical nonminimum phase system, posing significant challenges for the corresponding controller design. In this article, we employ the exact feedback linearization technique to effectively mitigate the complexities arising from the nonminimum phase characteristic. To address the voltage regulation challenge inherent to the boost converter with various disturbances, we propose an adaptive second-order sliding mode (SOSM) controller formulated within the Lyapunov framework. By dynamically modulating the control gain, the proposed controller circumvents the overestimation issue typical in other SOSM approaches, thereby diminishing chattering induced by excessive gain. In addition, unlike conventional adaptive SOSM methods, the proposed controller requires merely the disturbances to be bounded, without the need for the derivatives of these disturbances to be bounded. On this basis, the proposed controller ensures finite-time stability of the closed-loop system and concurrently enhances its transient response and robustness. Finally, comparative hardware experiments are conducted to demonstrate the effectiveness and superiority of the proposed controller.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.