Polynomially parameter dependent exponential stabilization of sampled-data LPV systems
作者：
Highlights：
• Polynomially sampled parameter dependent controller is proposed to stabilize the sampled-data LPV system with a larger maximum sampling interval.
• An exponential stabilization condition is derived by using a new polynomially parameter dependent Lyapunov function with looped functionals.
• The derived exponential stabilization condition is represented as a sum of squares condition which provides a feasible solution that guarantees global optimality.
• The proposed method is applied in the numerical example and compared with other methods to show the effectiveness of the proposed method.
摘要
•Polynomially sampled parameter dependent controller is proposed to stabilize the sampled-data LPV system with a larger maximum sampling interval.•An exponential stabilization condition is derived by using a new polynomially parameter dependent Lyapunov function with looped functionals.•The derived exponential stabilization condition is represented as a sum of squares condition which provides a feasible solution that guarantees global optimality.•The proposed method is applied in the numerical example and compared with other methods to show the effectiveness of the proposed method.
论文关键词：LPV Systems,Exponential stabilization,Sampled parameter dependent controller,Sum of squares,Looped-functionals
论文评审过程：Received 12 January 2021, Revised 1 May 2021, Accepted 22 June 2021, Available online 10 July 2021, Version of Record 10 July 2021.
论文官网地址：https://doi.org/10.1016/j.amc.2021.126473
