A novel learning-based asynchronous sliding mode control for discrete-time semi-Markov jump systems

H∞ control for networked semi‐Markovian jump systems with generally incomplete transition probabilities and distributed delays

“…Recently, S‐MJSs have received increasing attention which cover the basic analysis regarding to the stability and control strategies of NCSs in References 17,18. Particularly, a novel learning‐based asynchronous sliding mode control problem for discrete‐time S‐MJSs was studied in Reference 17, which uses S‐MJSs to depict NCSs with stochastic changing, and this kind of NCSs is dubbed as the semi‐Markovian jump NCSs (S‐MJNCSs), and sliding mode control problem for discrete‐time nonlinear S‐MJSs with partly unknown semi‐Markov kernel was investigated in Reference 18.…”

“…Different from MJSs, sojourn time in semi‐MJSs (S‐MJSs) is not necessarily subject to geometrically distribution, what is more, in S‐MJSs, the transition probabilities (TPs) can be time varying 15,16 instead of being constant, which also means powerful capability of system modeling of S‐MJSs. Recently, S‐MJSs have received increasing attention which cover the basic analysis regarding to the stability and control strategies of NCSs in References 17,18. Particularly, a novel learning‐based asynchronous sliding mode control problem for discrete‐time S‐MJSs was studied in Reference 17, which uses S‐MJSs to depict NCSs with stochastic changing, and this kind of NCSs is dubbed as the semi‐Markovian jump NCSs (S‐MJNCSs), and sliding mode control problem for discrete‐time nonlinear S‐MJSs with partly unknown semi‐Markov kernel was investigated in Reference 18.…”

Asynchronous observer‐based sliding mode control for 2‐D Markov jump Roesser systems

“…[13][14][15][16] In view of this, plentiful relevant research achievements on MJSs have been reported in theoretical fields and engineering applications. 17,18 One of the basic paradigms for stabilizing of MJSs is to find some control laws that completely correspond to or are independent of the system mode, that is, it is assumed that the controller mode is synchronized or independent with the operation mode of the original plant. Due to the observation error or measurement delay in the system mode signal, such an implicit assumption in the synchronous paradigm is unrealistic and mismatched modes scenario is very common in practical applications.…”

“…Markov jump systems (MJSs), as a representative class of stochastic hybrid systems composed of continuous state and discrete events, have been effective on catering for multi‐mode switching dynamics of complex physical systems 13‐16 . In view of this, plentiful relevant research achievements on MJSs have been reported in theoretical fields and engineering applications 17,18 . One of the basic paradigms for stabilizing of MJSs is to find some control laws that completely correspond to or are independent of the system mode, that is, it is assumed that the controller mode is synchronized or independent with the operation mode of the original plant.…”

Design of unknown input observer for discrete-time Markov jump systems with unknown input in both state equation and output equation

“…Similarly, such a special and complex system also exists in actual production and life. They have multiple modes, and each mode has different system parameters (Li et al, 2022). When the operating environment or work cycle of the system is different, the system will jump between different modes.…”