Event-triggered load frequency control of Markovian jump interconnected power systems under denial-of-service attacks

This work deals with the dynamic-memory event-triggered-based load frequency control issue for interconnected multiarea power systems (IMAPSs) associated with random abrupt variations and deception attacks. To facilitate the transient faults, a semi-Markov process is addressed to model the dynamic behavior of IMAPSs. In order to modulate transmission frequency, a novel area-dependent dynamic-memory event-triggered protocol (DMETP) is scheduled by resorting to a set of the historically released packets (HRPs), which ensures better dynamic performance. From the viewpoint of the defender, the randomly occurring deception attack is taken into account, which is regulated by a Bernoulli-distributed scalar. Benefitting from the DMETP scheduling, a novel framework of the memory-based asynchronous control strategy is formulated, in which the hidden semi-Markov model is adopted to reveal the mode mismatches. Based on the Lyapunov theory, sufficient conditions are established to ensure the stochastic stability of the resulting systems. In the end, the simulation result is presented to reveal the efficiency of the proposed dynamic-memory event-triggered-based approach. 

A Dynamic-Memory Event-Triggered Protocol to Multiarea Power Systems With Semi-Markov Jumping Parameter

Stability Analysis of Markovian Jump Systems

ABSTRACT In recent years, the problems of asynchronous control and filtering for Markov jump systems (MJSs) have received great research attention from scientific and engineering communities. The asynchronous situation between the original MJSs and the controller/filter is modelled by the hidden Markov model (HMM). This work gives a survey on the recent development of the HMM-based asynchronous controller and filter design for different MJSs, covering linear MJSs, fuzzy MJSs, semi-MJSs and 2D MJSs. Finally, a conclusion is drawn and the potential future research directions of MJSs are also discussed.

A survey on hidden Markov jump systems: asynchronous control and filtering

Improved dissipativity-based sampled-data control synthesis of nonhomogeneous Markovian jump fuzzy systems against mismatched fuzzy-basis functions

Markovian jump systems (MJSs) can be regarded as a special type of jump system, whose jumping law governing the switches among the subsystems are a Markovian chain or process [1]. Similar to other control systems, the subsystems in MJSs are usually described by some type of dynamic equations, while a Markov process that can be either continuous time or discrete time describes the jumping law. On the other hand, MJSs also are hybrid dynamic systems typically consisting of both the dynamic state space and the set of discrete events, where a Markov process describes the discrete events for MJSs [2], [3].

A Brief Tutorial and Survey on Markovian Jump Systems: Stability and Control

This chapter consists of two applications of Markovian jump systems. Section 7.2 considers the fault-tolerant control for wheeled mobile manipulators. We are concerned with the output feedback \(H_{\infty }\) control based on a high-gain observer for wheeled mobile manipulators, since the velocity signals are generally not available and indirectly obtained from the measured positions.

Applications Based on the Markov Jump Theory

Networked Control System: A Markovian Jump System Approach

This chapter investigates Markovian jump systems with imprecise jumping parameters. Two switching cases are considered.

System with Imprecise Jumping Parameters

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