On event‐triggered guaranteed cost control for discrete‐time semi‐Markovian neural networks having communication delays and dual‐terminal probabilistic faults

Abstract

This article aims to address the guaranteed cost control synthesis problem for discrete‐time semi‐Markovian neural networks (D‐SMNNs) considering communication delays along with probabilistic faulty sensors and actuators (dual‐terminal probabilistic faults) by adopting a modified event‐triggered mechanism. Our primary target of this research is to implement a suitable feedback controller such that the resulting D‐SMNNs achieve stochastically stable. To be more concrete, the structural and coefficient switchings of the NNs are characterized by a semi‐Markovian process (SMP) along with the lower and upper bounds of the transition probabilities (TPs), which can reflect the reality more accurately and has a wider application scope. For optimize the resource utilization of the band‐limited communication networks, a modified event‐triggered transmission strategy is put forward to lessen the unnecessary data transmission over network. Additionally, according to different failure rates and the measurement distributions of intelligent modules, a more practical probabilistic sensors and actuators faulty model for networked D‐SMNNs is synthesized, which including additivity and multiplicity. The anamorphic probability of sensors and actuators are governed by a battery of mutually independent stochastic variables that obeys certain probabilistic distribution over the preknown interval false[0,𝕋false]false(𝕋≥1false). Therein, the distortion degree and failure rate for each sensor and actuator can be separately quantized and characterized with the aid of mathematical variance and expectation. Briefly, in comparison to the existing faulty models, the novelty of this extended fault model lies in it can characterize more features in practical industrial applications. Afterwards, by resorting to the Lyapunov functional method and combining with both the stochastic analysis technique and matrix inequality decoupling manipulation, several sufficient conditions on ensuring stabilization for solving both the guaranteed cost controller gains and event‐triggered coefficients are formulated in the shape of a group of linear matrix inequalities (LMIs), which can be verified by exploiting standard compute software. After that, the controller design is reformulated as an optimization problem with LMI constraints immediately. Eventually, three simulation examples are carried out to substantiate the potency and accuracy of the proposed control synthesis methodology.

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

“…It is known that one of issues is system structures and parameters jumping, [5][6][7] which is caused by environmental changes, inter-subsystem coupling and the scope of work, and parts failures, while another issue is inevitable transmission delay. 8,9 which may lead to the degraded performance or even instability of NCSs. It is significant to overcome the adverse influences induced by network to guarantee the stability and even high dynamic performance of NCSs.…”

“…However, the involvement of network also brings some challenging features. It is known that one of issues is system structures and parameters jumping, 5‐7 which is caused by environmental changes, inter‐subsystem coupling and the scope of work, and parts failures, while another issue is inevitable transmission delay 8,9 . which may lead to the degraded performance or even instability of NCSs.…”

Reliable quantized sampled‐data LFC for semi‐Markov jump interconnected multi‐area power systems: Dealing with incomplete TRs

“…Based upon on this, it has been widely applied for modeling various stochastic systems. Compared to the MJSs, the semi‐MJSs offers increased flexibility since it can accommodate an arbitrary distribution of sojourn‐time 14–17 . During practical operation of IMAPSs, incidents such as internal system failures, sudden changes in external environmental factors and alterations in subsystem interconnectivity are inevitable and impact the system's stability severely, which may lead to serious consequences directly.…”

Dynamic event‐triggered asynchronous security load frequency control for semi‐Markov jump multi‐area power systems against deception attacks

“…Meanwhile, the IMAPSs affected by these factors have the characteristics of Markov process 14 . Compared with MJSs, the semi‐MJSs are more flexible for its sojourn‐time follows an arbitrary distribution 15–17 . Therefore, the semi‐MJSs are further advanced to the modeling of IMAPSs.…”

“…14 Compared with MJSs, the semi-MJSs are more flexible for its sojourn-time follows an arbitrary distribution. [15][16][17] Therefore, the semi-MJSs are further advanced to the modeling of IMAPSs. A general semi-Markov process was applied to describe the switching of secondary control of microgrid power systems in Reference 18.…”