4.7 Article

L1 finite-time stabilization for positive semi-Markovian switching systems

Journal

INFORMATION SCIENCES
Volume 477, Issue -, Pages 321-333

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2018.10.045

Keywords

Semi-Markovian process; Transient performance; Finite-time boundedness; Finite-time controller

Funding

  1. National Natural Science Foundation of China [61703231, 61773235]
  2. Natural Science Foundation of Shandong [ZR2017QF001, ZR2017PF001, ZR2017MF063]
  3. Chinese Postdoctoral Science Foundation [2017M612235, 2018T110670]
  4. Taishan Scholar Project [TSQN20161033]
  5. Excellent Experiment Project of Qufu Normal University [jp201728]
  6. Basic Science Research Programs through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2017R1A2B2004671]

Ask authors/readers for more resources

This paper investigates robust finite-time stabilization scheme for positive semi-Markovian switching systems (S-MSSs). Semi-Markovian process (SMP), external disturbances, and transient performances at a finite-time level may appear in a controlled system. A more general system model for S-MSSs that covers Markovian switching systems (MSSs) as a special case is suitable for describing some complex systems that are subject to random abrupt changes in structure and parameter. The main motivation for this is that finite-time problems can be used to describe the transient performance of practical industrial control processes. First, under the framework of stochastic semi-Markovian Lyapunov functions theory, some sufficient conditions for finite-time boundedness (FTBs) and L-1 FTBs criteria for positive S-MSSs are proposed for all admissible disturbances. Then, a novel L-1 finite time controller design method that employs the gain matrix decomposition method is presented to reduce some conservativeness, thereby guaranteeing that the resulting closed loop system (RLCS) could achieve positivity, FTBs, and attain a prescribed L-1 noise attenuation performance index in standard linear programming (LP). Finally, a practical example is introduced to show the effectiveness of the main theory (C) 2018 Elsevier Inc. All rights reserved.

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