Finite‐time dissipative control for time‐delay Markov jump systems with conic‐type non‐linearities under guaranteed cost controller and quantiser

Abstract

For a class of conic-type non-linear time-delay Markov jump systems, the asynchronous dissipative output feedback controller based on the guaranteed cost control and quantiser is designed in this study. In real applications, the system and the controller modes are always non-synchronous, so we introduce the hidden Markov model to solve this problem. Furthermore, we define three novel auxiliary variables and use quantisers to accomplish the output feedback controller design. Then, the finite-time boundedness and strict dissipativity of the closed-loop systems are guaranteed by sufficient conditions, and the controller also meets the guaranteed cost-control performance. By solving a set of linear matrix inequalities, we get the controller gains, the guaranteed cost control performance index J * , and the dissipative performance index α. Finally, the correctness and feasibility of this designed approach are demonstrated by a given example.

SMOTE-NC and gradient boosting imputation based random forest classifier for predicting severity level of covid-19 patients with blood samples

“…Therefore it is a necessity to consider these disturbances with alternative approaches like Markov jump systems (MJS) and fault detection, etc. as suggested in studies [42,44]. MJS and fault detection filtering methods are a good way of describing complex systems with external disturbances [42] Besides, more detailed knowledge of system parameters improves the efficiency of the model.…”

“…Hence, in this study, preprocessing steps were carefully applied before establishing a prediction model when uncertainties in the data set and mentioned studies were considered. However, in this work, a different and more simple approach than studies of [42][43][44][45] has been implemented for uncertainties like missing values, outliers, and an imbalanced number of output variables. Missing values were filled with iterative imputations methods and oversampling technique was used to change the imbalance situation while outliers were not removed from the model since they could provide hidden patterns with patient's anomalous blood samples.…”

Asynchronous dissipative control for networked time-delay Markov jump systems with event-triggered scheme and packet dropouts

“…However, the introduction of network also produces some new issues, e.g., time delay and packet dropouts. To solving these problems, a variety of approaches have been proposed [9][10][11][12][13][14][15][16][17]. In the case of packet dropouts, the works [9][10][11] investigated the fuzzy control of nonlinear MJSs, the H ∞ filtering of networked nonlinear discrete-time systems and the output feedback control of NCSs, respectively.…”

“…In the case of packet dropouts, the works [9][10][11] investigated the fuzzy control of nonlinear MJSs, the H ∞ filtering of networked nonlinear discrete-time systems and the output feedback control of NCSs, respectively. As for the study of networked MJSs with time delay [12][13][14][15][16], the issue of state estimation based on sliding mode observer was addressed [13]. The stability of delayed MJSs with infinite states was analyzed, and a sufficient condition for the mean square stability of the system was given in the form of linear matrix inequalities (LMIs) [15].…”

“…In addition, dissipative theory has been studied for a long time, which means that the storage of energy is less than the supply of energy; that is, there is energy dissipation in the system. In recent years, scholars have conducted a lot of research on dissipative control [12,[30][31][32]. Based on dissipative theory, the stability of sampled-data MJSs was studied [30], and the problem of sliding mode control for nonlinear MJSs with external disturbances was investigated [31].…”