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Asynchronous Learning-Based Output Feedback Sliding Mode Control for Semi-Markov Jump Systems: A Descriptor Approach

Abstract

This paper presents an asynchronous output-feedback control strategy of semi-Markovian systems via sliding mode-based learning technique. Compared with most literature results that require exact prior knowledge of system state and mode information, an asynchronous output-feedback sliding surface is adopted in the case of incompletely available state and non-synchronization phenomenon. The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem. Based upon the co-occurrence of two subsystems, the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions. Furthermore, a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion. Finally, the proposed theoretical method is substantiated through two numerical simulations with the practical continuous stirred tank reactor and F-404 aircraft engine model, respectively.

article Article
date_range 2024
language English
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Featured Keywords

Manifolds
System dynamics
Dynamics
Stochastic processes
Switches
Numerical simulation
Numerical models
Asynchronous switching
learning-based control
output feedback
semi-Markovian jump systems
sliding mode control(SMC)
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