Adaptive super-twisting sliding mode altitude trajectory tracking control for reentry vehicle. (January 2023)

• Record Type: Journal Article
• Authors: Shen, Ganghui; Xia, Yuanqing; Zhang, Jinhui; Cui, Bing
• Is Part Of: ISA transactions. Volume 132(2023)
• Page Start: 329
• Page End: 337
• Publication Date: 2023-01
• Subjects: Super-twisting sliding mode control -- Finite-time control -- Adaptive law -- Fast nonsingular terminal sliding mode -- Reentry vehicle; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2022.06.023
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This paper addresses the altitude trajectory tracking control problem of reentry vehicle subject to bounded uncertainty. A new continuous adaptive super-twisting sliding mode control (ASTSMC) method is developed based on conventional super-twisting sliding mode control (STSMC) and adaptive gain technique, which can improve tracking accuracy and achieve high control performance. Based on adaptive gain technique, the designed ASTSMC method requires no prior information on uncertainty and avoids the overestimation of control gain, then the unexpected chattering phenomenon is alleviated. By employing fast power rate reaching law and modified fast nonsingular terminal sliding mode (FNTSM) surface, the designed controller achieves faster convergence and stronger robustness than conventional STSMC methods. Furthermore, the finite-time stability of closed-loop system is proved through Lyapunov theory. Simulation results are executed to validate the superiority of the proposed controller. Highlights: A novel adaptive super-twisting sliding mode control (ASTSMC) law is proposed to address trajectory tracking problem for reentry vehicle under bounded uncertainty. The proposed ASTSMC law can resolve the gain overestimation, and it requires no prior information on uncertainty. By employing fast power rate reaching law, the proposed ASTSMC law achieves fast finite-time convergence and exhibits strong robustness.