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• The H ∞ fault-tolerant control scheme is studied for a class of conic-type nonlinear Markov jump systems with sensor and actuator faults. • The hidden Markov model is introduced to deal with the asynchronous phenomenon, and the H ∞ fault-tolerant controller is designed by selecting suitable Lyapunov-Krasovskii functional. • The proposed control strategy can not only ensure the finite-time boundedness of the closed-loop system, but also guarantee the required H ∞ performance. This paper studies the H ∞ fault-tolerant control problem for a class of conic-type nonlinear Markov jump systems with sensor and actuator faults as well as unknown disturbances. Firstly, the hidden Markov model is introduced to deal with the asynchronous problem existing in the control systems. By selecting suitable Lyapunov-Krasovskii function, linear matrix inequalities techniques are applied to obtain the H ∞ fault-tolerant controller. A new condition of the state feedback H ∞ fault-tolerant controller with actuator faults and sensor faults is presented. The proposed control strategy can not only ensure the finite-time boundness of the closed loop system, but also guarantee the required H ∞ performance. Lastly, the availability of the design scheme is validated by a simulation example. [ABSTRACT FROM AUTHOR]

Abstract: This paper studies the finite-time state estimation and H ∞ filter design problem for a class of uncertain Markovian jumping systems (MJSs) with bounded transition probabilities. Based on the selected Lyapunov–Krasovskii functional, the finite-time H ∞ filter is constructed to derive a sufficient condition such that the filtering error dynamic MJSs are finite-time bounded and satisfies a prescribed level of H ∞ disturbance attenuation in a finite time-interval. Then, in terms of linear matrix inequalities (LMIs) techniques, the sufficient condition on the existence of finite-time H ∞ filter is presented and proved. The filter matrices can be solved directly by using the existing LMIs optimization techniques. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design approach. [Copyright &y& Elsevier]

Abstract: This paper provides the observer-based finite-time control problem of time-delayed Markov jump systems that possess randomly jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. The observer-based finite-time H ∞ controller via state feedback is proposed to guarantee the stochastic finite-time boundedness and stochastic finite-time stabilization of the resulting closed-loop system for all admissible disturbances and unknown time-delays. Based on stochastic finite-time stability analysis, sufficient conditions that ensure stochastic robust control performance of time-delay jump systems are derived. The control criterion is formulated in the form of linear matrix inequalities and the designed finite-time stabilization controller is described as an optimization one. The presented results are extended to time-varying delayed MJSs. Simulation results illustrate the effectiveness of the developed approaches. [Copyright &y& Elsevier]

Abstract: The unbiased H ∞ filtering problem is studied for stochastic Markov jump system with constant and neutral time-delays. By re-constructing the system, the dynamic filtering error characteristics of unknown inputs and time-delays are obtained. A sufficient condition is initially established on the existence of mode-dependent unbiased H ∞ filter of constant time-delay system using stochastic Lyapunov–Krasovskii function. Then, the unbiased H ∞ filter is also designed for the jump system with constant and neutral time-delays. The design criterions are presented in the form of linear matrix inequality. Finally, the unbiased H ∞ filtering problems are described as optimization algorithms. Numerical examples illustrate the effectiveness of the developed techniques. [Copyright &y& Elsevier]

• Fault detection scheme for conic nonlinear systems in finite frequency domain is designed. • Sufficient conditions to realize H_ fault sensitivity and H_ disturbance attenuation. • The fuzzy fault detection problem is transformed into an optimization algorithm. • A tunnel diode-circuit is given to confirm the validity of the designed scheme. In this paper, we focused on the issue of fault detection subject to a class of conic-type nonlinear systems in the finite frequency domain (FFD). Applying Takagi Sugeno (T-S) fuzzy models, the conic-type dynamic error system is established. To prove that the residual vector is robust to external disturbances and sensitive to faults, we provide some conditions to realize H − fault sensitivity performance and H ∞ disturbance attenuation performance within the FFD. Then, utilizing linear matrix inequalities techniques, the fuzzy fault detection observer design problem is transformed into an optimization algorithm. Finally, a numerical example related to a tunnel diode-circuit is given to confirm the validity of the designed scheme. [ABSTRACT FROM AUTHOR]

This paper addresses finite-time boundedness and stabilization problem for n -neuron uncertain positive Markovian jumping neural networks (MJNNs). Firstly, we analyze the positive MJNNs in the input-free case and then propose a sufficient condition to ensure the input-free finite-time boundedness. Then applying the state feedback scheme, a suitable finite-time stabilizable controller is devised to guarantee the positiveness of the closed-loop MJNNs. Moreover, some sufficient conditions for the existence of the controller gain solutions are proposed and proved by using the stochastic Lyapunov-Krasovskii functional approach and linear matrix inequalities techniques. Finally, we give two simulation examples to demonstrate the effectiveness and feasibility of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper addresses finite-region asynchronous H ∞ filtering for a class of two-dimensional Markov jump systems (2-D MJSs). A mathematical model is established using the Roesser model, and asynchrony is accounted for using a hidden Markov model (HMM). The modes jumping between the target system and the designed filter are determined by the given conditional probability matrix. Sufficient conditions are derived using suitable Lyapunov function and linear matrix inequalities (LMIs) to ensure stable filtering performance. The practical applicability of the approach is illustrated by two examples. Overall, this study offers a method to tackle filtering challenges in 2-D Markov jump systems, incorporating HMM, Lyapunov functions, and LMIs to effectively solve the finite-region asynchronous H ∞ filtering problem. • An HMM is used to describe the asynchronous phenomenon between the system and the filter. • Lyapunov functional and recursive formulas effectively analyze the FRB of filtering error system. • The Darboux equation and the heat exchange process both validate the effectiveness of the filter. [ABSTRACT FROM AUTHOR]

• An ETS is proposed to reduce energy consumption. • An event-triggered-based controller is designed for MJCPSs. • The uniform upper/lower bounds are used to describe DoS attacks. • Sufficient conditions are given to stabilize the MJCPSs. This paper is concerned with the event-triggered-based H ∞ control problem for Markov jump cyber-physical systems against denial-of-service attacks. The uniform upper and lower bounds are used to describe the characteristics of aperiodic denial-of-service attacks. An event-triggered scheme is introduced to reduce the waste of resources and avoid communication channel congestion. Based on multi-Lyapunov functions, sufficient conditions are proposed to guarantee the asymptotic mean-square stability and H ∞ performance of the switched closed-loop Markov jump cyber-physical systems. By solving linear matrix inequalities, the event-triggered-based controller gain matrices, and H ∞ performance index are obtained. In the simulation, an F-404 aircraft engine system is employed to clarify the validity of the proposed event-triggered-based controller design approach in face of denial-of-service attacks. [ABSTRACT FROM AUTHOR]

• A novel online mode-free integral reinforcement learning algorithm is proposed to solve the mutiplayer non-zero sum games. • The online learning is used to compute the corresponding N coupled algebraic Riccati equations. • The policy iterative algorithm is applied to solve the coupled algebraic Riccati equations corresponding to the multiplayer nonzero sum games. In this paper, a novel online mode-free integral reinforcement learning algorithm is proposed to solve the multiplayer non-zero sum games. We first collect and learn the subsystems information of states and inputs; then we use the online learning to compute the corresponding N coupled algebraic Riccati equations. The policy iterative algorithm proposed in this paper can solve the coupled algebraic Riccati equations corresponding to the multiplayer non-zero sum games. Finally, the effectiveness and feasibility of the design method of this paper is proved by simulation example with three players. [ABSTRACT FROM AUTHOR]