Stability analysis for neutral Markovian jump systems with partially unknown transition probabilities

This paper addresses the problem of the delay-dependent stability for neutral Markovian jump systems with partial information on transition probability. The time delays discussed in this paper are time-varying delays. Combined the new constructed Lyapunov functional with the introduced free matrices, and using the analysis technique of matrix inequalities, the delay-dependent stability conditions are obtained. The obtained results are formulated in terms of LMIs, which can be easily checked in practice by Matlab LMI control toolbox. Three numerical examples are given to show the validity and potential of the developed criteria.     

Finite-time lag synchronization of master-slave complex dynamical networks with unknown signal propagation delays

This paper studies the finite-time lag synchronization issue of master-slave complex networks with unknown signal propagation delays by the linear and adaptive error state feedback approaches. The unknown signal propagation delays are fully considered and estimated by adaptive laws. By designing new Lyapunov functional and discontinuous feedback controllers, which involves the estimated error rather than the general synchronization error, sufficient conditions are derived to ensure lag synchronization of the networks within a setting time. It is interesting to discover that the setting time is related to initial values of both the estimated error and the estimated unknown signal propagation delays. Finally, two numerical examples are given to illustrate the effectiveness and correctness of the proposed finite-time lag synchronization criteria.     

Stability of Markovian jump systems with generally uncertain transition rates

This paper is concerned with exploring stability analysis for a class of Markovian jump systems (MJSs) with generally uncertain transition rates (GUTRs). In the GUTR model, each transition rate can be completely unknown or only its estimate value is known. This new uncertain model is more general than the existing ones and can be applicable to more practical situations. The stability criterion for such a class of uncertain MJSs is derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is given to illustrate the effectiveness and applicability of the proposed method.     

Distributed formation control for multiple quadrotor UAVs under Markovian switching topologies with partially unknown transition rates

This paper addresses distributed formation control for a group of quadrotor unmanned aerial vehicles (UAVs) under Markovian switching topologies with partially unknown transition rates. Instead of the general stochastic topology, the graph is governed by a set of Markov chains to the edges, which can recover the traditional Markovian switching topologies in line with the practical communication network. Extended high gain observers (EHGOs) are constructed with a two-time-scale format to deal with the issue of nonlinear input coefficients, so that there could be a higher estimation precision of the system uncertainties. To impel multiple quadrotor UAVs to achieve a predesigned formation shape, a modified integral sliding mode (ISM) control protocol is proposed here with a multi-time-scale structure, which allows independent analysis of the dynamics in each time scale. The stability proof for the system state space origin is derived from the singular perturbation method and Lyapunov stability theory. In addition, the introduced ISM controller can deal with the time varying desired references with the bounded accelerations and is robust to the disturbances. Finally, simulations on six quadrotor UAVs are given to verify the effectiveness of the theoretical results.     

Less conservative stabilization conditions for Markovian jump systems with partly unknown transition probabilities

This paper is devoted to the robust stabilization problem for a class of MJLSs with mode transition probabilities taken to be partly known, unknown, and unknown but with known bounds. To meet the needs of less conservative stabilization conditions, this paper proposes a valuable approach that (1) can express the conditions in terms of matrix inequalities with homogeneous polynomial dependence on partly unknown transition probabilities and (2) can include all possible slack variables related to transition probability constraints in the relaxation process coupled with deriving a finite set of linear matrix inequalities (LMIs). Finally, two numerical examples are reported to illustrate the effectiveness of the derived stabilization conditions.     

Robust control for Markovian jump systems with partially known transition probabilities and nonlinearities

This paper investigates robust _H∞$H_{\infty }$ controller design for Markovian jump systems (MJSs) with partially known transition probabilities (TPs) and nonlinearities. A general nonlinearity model is proposed, the generalization lies in three aspects: (1) the nonlinearities include both state and delayed state information; (2) the nonlinearities satisfy sector-bounded conditions; (3) apart from the lower and upper bounds, the probability information of the nonlinearities belonging to different sector bounds is utilized. The MJSs are considered with some of the TPs completely unknown, which can cover the MJSs with completely known TPs and completely unknown TPs as special cases. It should be noted that the relationship between known and unknown TPs is utilized, which can reduce the conservatism of the results. By using the Lyapunov functional method, sufficient conditions are derived. At last, two simulation examples show the application and effectiveness of the proposed method.     

Improved asynchronous stabilization method for nonhomogeneous Markovian jump fuzzy systems with incomplete transition rates

This paper proposes an improved asynchronous stabilization method for nonhomogeneous Markovian jump fuzzy systems (MJFSs) with incomplete transition rates via a nonparallel distributed compensation (non-PDC) control scheme. To cover a more realistic situation in the continuous-time MJFS domain, this paper focuses on addressing the following issues differently from previous studies: 1) emergence of a nonhomogeneous Markov process and asynchronous control mode, 2) separation of the Lyapunov matrix from the control gain within stabilization conditions, and 3) relaxation of stabilization conditions subject to multiple time-varying parameters. Specifically, the effects of nonhomogeneity and asynchronism are simultaneously reflected in the stabilization conditions, and separation and relaxation techniques are additionally developed as needed. Finally, the advantages of our method are illustrated through two examples: the first is provided to show the effectiveness of the proposed separation technique, and the second is provided to show that the relaxed stabilization conditions are less conservative than previous results.     

Finite-time synchronization of delayed complex dynamic networks via aperiodically intermittent control

In this paper, the finite-time synchronization problem of complex dynamic networks with time delay is studied via aperiodically intermittent control. By compared with the existed results concerning aperiodically intermittent control, some new results are obtained to guarantee the synchronization of networks in a finite time. Especially, a new lemma is proposed to reduce the convergence time. In addition, based on aperiodically intermittent control scheme, the essential condition ensuring finite-time synchronization of dynamic networks is also obtained, and the convergence time is closely related to the topological structure of networks and the maximum ratio of the rest width to the aperiodic time span. Finally, a numerical example is provided to verify the validness of the proposed theoretical results.     

Optimal synchronization controller design for complex dynamical networks with unknown system dynamics

In this paper, the optimal synchronization controller design problem for complex dynamical networks with unknown system internal dynamics is studied. A necessary and sufficient condition on the existence of the optimal control minimizing a quadratic performance index is given. The optimal control law consists of a feedback control and a compensated feedforward control, and the feedback control gain can be obtained by solving the well-known Algebraic Riccati Equation (ARE). Especially, in the presence of unknown system dynamics, a novel adaptive iterative algorithm using the information of system states and inputs is proposed to solve the ARE to get the optimal feedback control gain. Finally, a simulation example shows the effectiveness of the theoretical results.     

Finite-time and fixed-time synchronization of discontinuous complex networks: A unified control framework design

This paper is concerned with the finite-time and fixed-time synchronization of complex networks with discontinuous nodes dynamics. Firstly, under the framework of Filippov solution, a new theorem of finite-time and fixed-time stability is established for nonlinear systems with discontinuous right-hand sides by using mainly reduction to absurdity. Furthermore, for a class of discontinuous complex networks, a general control law is firstly designed. Under the unified control framework and the same conditions, the considered networks are ensured to achieve finite-time or fixed-time synchronization by only adjusting the value of a key control parameter. Based on the similar discussion, a unified control strategy is also provided to realize respectively asymptotical, exponential and finite-time synchronization of the addressed networks. Finally, the derived theoretical results are supported by an example with numerical simulations.     

Finite-time outer-synchronization for complex networks with Markov jump topology via hybrid control and its application to image encryption

This paper investigates the problem of finite-time outer-synchronization for discrete-time complex networks with Markov jump topology in the presence of communication delays and possible information losses and its application to image encryption. A hybrid control, which is subject to both stochastic jumps and deterministic switches, is proposed to realize finite-time and stochastic outer-synchronization for the concerned networks. By utilizing a stochastic Lyapunov functional combined with the average dwell-time method, sufficient conditions are found such that the synchronization error dynamical system is stochastically stable in finite-time. Two numerical examples are presented to illustrate the effectiveness of the proposed method. Finally, the complex network consists of four coupled Lorenz systems are utilized to generate chaotic sequences and a new chaotic image cryptosystem is constructed to transmit encrypted images based on the synchronized drive-response complex networks. Experiments are conducted by using numerical simulation, and the security is analyzed in terms of key space, key sensitivity, histogram distributions, correlation coefficients, information entropy and differential attack measures. The experimental results show that the proposed chaotic image cryptosystem has the advantages of high security against some classical attacks.     

Multiple integral techniques for stochastic stability analysis of Markovian jump systems: A unified uncertain transition rates

This paper studies the stochastic stability problem for Markovian jump systems with unified uncertain transition rates via multiple integral techniques. The considered transition rates unify some existing ones in a framework, which are more general and practical. A multiple-integral-type Lyapunov–Krasovskii functional (MITLKF) is constructed, which contains more ply of integral terms than some existing ones. In order to obtain a tighter bound of the MITLKF, an auxiliary function-based multiple integral inequality (AFMII) is proposed, which encompasses some existing ones as its special cases. Based on these ingredients, a novel stability condition is derived for Markovian jump systems with the unified uncertain transition rates. The effectiveness of the proposed approach is demonstrated by two examples.     

Fault detection of discrete-time delay Markovian jump systems with delay term modes partially available

This paper focuses on the fault detection problem for a class of discrete-time delay Markovian jump systems with delay term modes partially available. A crucial but general hypothesis considered here is there is a suitable and effective detector to provide a measurement signal of operation mode of delay term. The fault detection filter used as the residual generator could depend on the original system operation mode or the signal emitted from detector. Via minimizing the error between the residual and fault signal, the problem of fault detection and isolation (FDI) is converted into an H_∞ filtering problem and closely related to a probability representing the degree of dependence between the original and measurable signals. An improved Lyapunov function depending on such two operation modes is exploited to study the corresponding problems. Sufficient conditions for the existence of the desired FDI filter are presented in terms of LMIs. When such a probability is uncertain or partially unknown, similar problems are also considered. A practical example is used to demonstrate the effectiveness and superiority of the proposed methods.     

Sampled-data predictive control for uncertain jump systems with partly unknown jump rates and time-varying delay

This paper presents a sampled-data predictive control strategy for a class of uncertain continuous-time Markovian jump linear system (MJLS) with time-varying delay. The system under consideration covers MJLS with completely known jump rates and arbitrary switched linear system. The predictive formulation utilizes both off-line and on-line optimization paradigms. The feasibility of the control scheme and the stability of the closed-loop system are investigated by introducing a modified stochastic invariant ellipsoid. The conditions for the existence of a stabilizing optimal controller for the underlying system are obtained via the semi-definite programming (SDP). A numerical example is given to verify efficiency and potential of the developed approach.     

Security control for Markov jump system with adversarial attacks and unknown transition rates via adaptive sliding mode technique

This paper is concerned with the security control problem for a class of Markov jump systems subject to false data injection attack and incomplete transition rates. An on-line estimation strategy is provided for the time-variant and unknown cyber-attack modes. And then, an adaptive sliding mode controller is synthesized with different robust terms for different modes to guarantee the reachability of the specified sliding surface. Moreover, the sufficient conditions for the stability of the closed-loop systems are derived. Finally, it is shown from simulation results that the effect of both false data injection attack and incomplete TRs can be effectively attenuated by the present adaptive SMC method.     

Finite-time synchronization of delayed dynamical networks via aperiodically intermittent control

In this paper, we concern the finite-time synchronization problem for delayed dynamical networks via aperiodically intermittent control. Compared with some correspondingly previous results, the intermittent control can be aperiodic which is more general. Moreover, by establishing a new differential inequality and constructing Lyapunov function, several useful criteria are derived analytically to realize finite-time synchronization for delay complex networks. Additionally, as a special case, some sufficient conditions ensuring the finite-time synchronization for a class of coupled neural network are obtained. It is worth noting that the convergence time is carefully discussed and does not depend on control widths or rest widths for the proposed aperiodically intermittent control. Finally, a numerical example is given to demonstrate the validness of the proposed scheme.