Jump Systems Subject Research Articles

Dynamic Event-Triggered Asynchronous Fault Detection via Zonotopic Threshold Analysis for Fuzzy Hidden Markov Jump Systems Subject to Generally Hybrid Probabilities

Dynamic Event-Triggered Asynchronous Fault Detection via Zonotopic Threshold Analysis for Fuzzy Hidden Markov Jump Systems Subject to Generally Hybrid Probabilities

$$\mathcal {H}_{\infty }$$ Control of Time-Delayed Markov Jump Systems Subject to Mismatched Modes and Interval Conditional Probabilities

$$\mathcal {H}_{\infty }$$ Control of Time-Delayed Markov Jump Systems Subject to Mismatched Modes and Interval Conditional Probabilities

Event-Triggered Control for Markov Jump Systems Subject to Mismatched Modes and Strict Dissipativity.

In order to save network resources of discrete-time Markov jump systems, an event-triggered control framework is employed in this article. The threshold parameter in the event-triggered mechanism is designed as a diagonal matrix in which all elements can be adjusted according to system performance requirements. The hidden Markov model is introduced to characterize the asynchronization between the controller and controlled system. The effect of randomly occurring gain fluctuations is taken into account during the controller design. For the purpose of guaranteeing that the closed-loop system is stochastically stable and satisfies the strictly (D₁,D₂,D₃)-ɣ-dissipative performance, sufficient conditions are constructed by employing the Lyapunov function and stochastic analysis. After linearization, the proposed controller gains are obtained by solving the linear matrix inequalities. Ultimately, a practical example of the dc motor device is used to illustrate the effectiveness of the proposed new design technique.

Formula omitted] and [formula omitted] Control with sector bound optimization for Continuous Time Markov Jump Lur’e Systems

This paper addresses the H2 and H∞ control of Markov Jump Systems subject to a class of nonlinearities that include them on the Lur’e system framework, with sector slope optimization. The proposed controllers are robust to nonlinearities belonging to a sector. We propose mode-dependent controllers; in other words, the Markov mode θ(t) is available to controllers. The design of such controllers considers the optimization of the H2 and H∞ costs as well as the sector slope, which determines the class of accepted nonlinearities. The results are illustrated through two practical examples: coupled electrical machines and the semi-active suspension of a quarter car.

ℋ2 and ℋ∞ Filtering for Continuous-Time Markov Jump Lur'e Systems with Sector Bound Optimization

This paper is about the and filtering of Markov Jump Systems subject to a class of nonlinearities which include them on the Lur'e systems framework. The proposed filters are robust to nonlinearities belonging to a given sector with maximum slope. With regard to the availability of the Markov parameter, we present strategies which allow us to design either mode-dependent and modeindependent filters, with sector bound optimisation. The results are illustrated by two examples.

Zonotope-Based Asynchronous Fault Detection for Markov Jump Systems Subject to Deception Attacks via Dynamic Event-Triggered Communication

Zonotope-Based Asynchronous Fault Detection for Markov Jump Systems Subject to Deception Attacks via Dynamic Event-Triggered Communication

Robust observer-based sliding mode [formula omitted] control for stochastic Markovian jump systems subject to packet losses

This paper studies the robust observer-based sliding mode H∞ control issue for discrete-time stochastic Markovian jumping systems (MJSs) subject to packet losses (PLs). Here, a state variable observer of an initial system is designed to estimate the state and a series of Bernoulli random variables is utilized to model the PLs, whose occurrence probability is allowed to be imprecise. Then, a linear switching function is constructed based on the estimated state space. The aim of our paper is to design an observer-based sliding mode H∞ control strategy such that, the stochastic stability conditions with prescribed H∞ performance are established for augmented MJSs under the PLs with imprecise occurrence probability, which is composed of the sliding mode dynamics and the error system. The linear sliding surface can be determined by solving some linear matrix inequalities (LMIs). In addition, by proposing an improved reaching condition, the desired robust observer-based H∞ controller is designed in discrete-time setting to drive the system state from any initial one onto the designated sliding surface. Finally, the usefulness of observer-based H∞ control method is demonstrated via some numerical simulations.

Asynchronous Filtering for Delayed Fuzzy Jump Systems Subject to Mixed Passivity and $${\user2{H\infty }} $$ Performance

This paper investigates asynchronous mixed passivity and $$H\infty $$ filter design for fuzzy jump systems with time-varying delays. Firstly, new time delay-dependent stability conditions for the fuzzy Markovian jump systems are obtained by constructing a mode-dependent Lyapunov functional and introducing free weight matrices technique. Secondly, the asynchronous filter is designed via linear matrix inequalities, which can ensure stochastic stability and the mixed passivity and $$H\infty $$ performance of the augmented Markovian jump filtering error system. A numerical example and a single-link robot arm are utilized to show the effectiveness of the method.

Adaptive Neural Sliding Mode Control of Markov Jump Systems Subject to Malicious Attacks

This article investigates the problem of adaptive neural sliding mode control for Markov jump systems. The transition probabilities of the Markov process are partly unknown. The cyber layer, which is vulnerable to the adversary, is deployed to broadcast the control signal to the actuator. The attacker can inject malicious information to the control signal to deteriorate the system performance. A sliding mode controller is designed to stabilize the system. Then, sufficient conditions that ensure the stability of the closed-loop system are given in the framework of the Lyapunov theory. In the end, two simulation examples are applied to illustrate the effectiveness and feasibility of the proposed methodology.

Asynchronous Control of Continuous-Time Nonlinear Markov Jump Systems Subject to Strict Dissipativity

This paper addresses the strictly dissipative control problem for continuous-time nonlinear Markov jump systems via Takagi–Sugeno fuzzy rules. The modes of a devised fuzzy controller are assumed to run asynchronously with the modes of original system, which is widespread in practice and described through a hidden Markov model. A sufficient condition is acquired to ensure the stochastic stability and strict dissipativity of the closed-loop systems, based on which the design method of an asynchronous fuzzy controller is provided. Finally, one example is presented to illustrate the effectiveness and new features of the proposed design techniques.

Finite-time Sliding Mode Control of Markovian Jump Systems Subject to Actuator Faults

This paper addresses the problem of finite-time boundedness (FTB) for a class of Markovian jump systems (MJSs) via sliding mode control (SMC) technique, in which there may happen actuator faults in all of control channels and mismatched external disturbance. By means of the available boundary information of actuator faults, a suitable sliding mode controller is designed such that state trajectories are driven to sliding surface before a specified finite (possibly short) time interval. Furthermore, a partitioning strategy is introduced to derive the sufficient conditions for ensuring the FTB of the closed-loop systems over the whole specified finite-time interval including the reaching phase and the sliding motion phase. Finally, a practical example are provided from an F-404 aircraft engine system to illustrate the proposed method.

Reduced-Order Partially Mode-Dependent Energy-to-Peak Filter Design for Discrete-Time Markov Jump Systems Subject to Quantizer Faults and State-Dependent Noises

This paper investigates the reduced-order energy-to-peak filter design problem of discrete-time Markov jump systems with partially unknown transition probabilities, random quantizer faults and state-dependent disturbances. Attention is focused on the design of a reduced-order partially mode-dependent filter to mitigate quantization effect and stochastic disturbance, and ensure a prescribed energy-to-peak noise attenuation level. Via using the partly mode-dependent Lyapunov function, sufficient conditions for the existence of the filter are expressed in terms of linear matrix inequalities. Finally, three numerical examples are provided to demonstrate the effectiveness of the proposed approach.

On Finite-Time Stochastic Stability and Stabilization of Markovian Jump Systems Subject to Partial Information on Transition Probabilities

The problems of finite-time stochastic stability and stabilization for a class of linear Markovian jump systems subject to partial information on transition probabilities are considered in this paper. By introducing the concept of finite-time stochastic stability for linear Markovian jump systems, a new method is proposed to ensure that the state trajectory remains in a bounded region of the state space in mean square sense over a pre-specified finite-time interval. Based on this stability result, the finite-time stochastic stabilization criterion is then given. Finally, two numerical examples are shown to illustrate the effectiveness of the proposed method.