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The Early‐Middle Jurassic is one of the crucial coal‐forming geologic periods in the world and an important target for hydrocarbon exploration in the Turpan‐Hami Basin, China. The paleoenvironment and vegetation reconstruction of the Early‐Middle Jurassic have been investigated using elemental geochemistry and palynological analysis to reveal paleoclimate evolution. A total of 48 genera of pteridophyte spore and 35 genera of gymnosperm pollen were identified, and 5 palynological assemblages were longitudinally divided, which showed significant differences in geochemical behaviours. The paleoenvironment was a transition from suboxidation to anoxia and then to an oxidation environment under freshwater conditions. The paleowater in the northern Taibei Sag was deeper than that in the southern part during the Middle Jurassic, which coincided with the sedimentary background of the sublacustrine fan in the north and the shallow braided river delta in the south. The paleovegetation evolved from mixed lowland–upland forest in the Hettangian‐Toarcian, to lowland fern forest in the Aalenian‐Bajocian, to upland conifers forest in the early Bathonian, to upland Cheirolepidiaceae forest in the late Bathonian‐Callovian. The Toarcian and Bathonian‐Callovian arid climate and the Hettangian‐Pliensbachian and Aalenian‐Bajocian warm‐humid climate were responses to the continued global warming events and the intensification of the East Asian monsoon circulation, respectively. The influence of the Bathonian‐Callovian aridification event on the sedimentary response in the southern Taibei Sag will be delayed due to the gradual southward migration of the depositional centre. [ABSTRACT FROM AUTHOR]

This article addresses the problem of distributed joint estimation for a class of discrete‐time time‐varying systems subject to random nonlinearities and unknown inputs over sensor networks. For the purpose of energy‐saving, the dynamic event‐triggering mechanism is adopted to govern the signal transmission between the sensor and the local estimator. First, some constraint conditions are introduced to decouple the unknown input to eliminate their impact. Then, by means of mathematical induction, an upper bound of the filtering error covariance is individually obtained for the state and the unknown input by solving coupled Riccati‐like difference equations. Subsequently, the matrix simplification method is adopted to tackle the sparsity problem caused by sensor networks. In addition, the required distributed estimator gains are acquired by minimizing the obtained upper bounds of filtering error covariances. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed joint estimator design scheme. [ABSTRACT FROM AUTHOR]

This article studies the fault detection problem for a class of discrete‐time impulsive systems using mixed dissipativity theory. First, under the impulsive effects, a fault diagnosis observer is designed such that it is insensitive to disturbances, and sensitive to faults. Then, a mixed dissipativity concept is introduced to deal with impulsive effects, disturbances insensitivity condition and faults sensitive condition in one framework such that the impulsive error dynamic is dissipative with respect to the proposed mixed supply rate. Based on the proposed mixed supply rate, sufficient conditions are obtained to guarantee the dissipativity of the impulsive estimation error dynamic. Moreover, sufficient conditions are established for the existence of the desired fault observer. The corresponding solubility conditions for the designs of the desired observer are also obtained. Finally, simulation results are proposed to demonstrate the effectiveness of our proposed strategy. [ABSTRACT FROM AUTHOR]

This paper is concerned with the distributed cubature Kalman filtering (DCKF) for a class of discrete time‐varying nonlinear systems subject to stochastic communication protocol (SCP). In order to avoid the data collisions, the SCP is introduced to randomly schedule each sensor node information from one of the neighboring nodes to the filter which is presented via not only the information of itself sensor but also the information of neighboring sensors. The considered scheduling probability of the selected node is unknown. Therefore, the exact filtering error covariance is not available. The purpose of this paper is to design a DCKF under the spherical–radial cubature rule such that an upper bound of the filtering error covariance is guaranteed by utilizing fundamental inequality. Such an upper bound is dependent on known upper and lower bounds of the scheduling probabilities. Subsequently, the desired filter matrices are given by minimizing the upper bound of the filtering error. A sufficient condition is derived by using Riccati‐like difference equations method. Besides, a recursive form of filter algorithm is designed for online computation. Finally, the usefulness of the DCKF is verified by utilizing a simulation example on the induction machines. [ABSTRACT FROM AUTHOR]

This article addresses the distributed recursive filtering problem for a class of time‐varying multirate systems in sensor networks with randomly occurring nonlinearities and the communication protocol. A multirate model is considered where the sampling period of the sensors is slower than the updating period of the system state. Accordingly, the lifting technique is proposed to transform the multirate system into a single‐rate system. In order to avoid data collisions, the random access protocol (RAP) scheduling is applied to determine which signal/packet selected by RAP scheduling can access the shared network for each sensor. Attention is focused on the design of a distributed recursive filter such that, in the simultaneous presence of randomly occurring nonlinearities, the multirate strategy and the RAP scheduling, an upper bound for the filtering error covariance is obtained with the help of the mathematical induction method. Furthermore, by utilizing a novel matrix simplification technique, the filter parameters are recursively calculated by minimizing the obtained upper bound. Finally, the effectiveness of the proposed distributed recursive filtering scheme is demonstrated via a numerical example. [ABSTRACT FROM AUTHOR]

This paper is concerned with the set‐membership consensus of cooperation‐competition multi‐agent systems (CCMASs) with the round‐robin (RR) protocol. First, the relationship between cooperative and competitive agents is featured by the graph theory. Second, the RR protocol is used to relieve the burden of data transmission among agents due to the limited network bandwidth. Third, a novel concept of set‐membership consensus for CCMASs is presented to disclose the bound of consensus errors. In the framework of set‐membership filtering, a novel co‐design framework of set‐membership estimation and set‐membership consensus is provided to realize the desired cooperation‐competition consensus, where an ellipsoid is obtained to estimate the agent state. The controller and observer gains as well as the ellipsoid parameters are obtained by a recursive convex optimization algorithm. Finally, an illustrated example is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of the event‐triggered finite‐time nonfragile H∞ synchronization control for a class of discrete time‐delayed complex networks with switched topology. To decrease the unnecessary signal transmission and save control cost, the dynamic event‐triggering scheme is employed in the controller‐to‐actuator channel where the varying triggering threshold is governed by a dynamical equation. The main purpose of this paper is to design a nonfragile synchronization controller such that the synchronization error dynamics satisfies both the finite‐time boundedness and the H∞ disturbance rejection level. By constructing appropriate Lyapunov–Krasovskii functional and using the average‐dwell‐time technique, the desired controller gains are acquired in terms of the solution to a set of linear matrix inequalities. Finally, a numerical simulation example is provided to demonstrate the effectiveness of the proposed synchronization controller design scheme. [ABSTRACT FROM AUTHOR]

In this paper, the variance‐constrained H∞ synchronization control problem is investigated for a class of discrete time‐delayed complex dynamical networks. Considering the case where a dynamical network cannot achieve the synchronization by itself, the feedback controllers are added to drive the network toward a desired orbit. To further decrease both the frequency of controller update and the energy consumption, an intermittent pinning strategy is developed to control only a small part of the network nodes. The purpose of the addressed synchronization control problem is to design a set of feedback controllers such that the closed‐loop system achieves both the prescribed H∞ disturbance attenuation level and the variance constraints. By resorting to a combination of the Lyapunov stability theory and the switching system approach, a sufficient condition is obtained under which the dynamical network reaches the overall synchronization. Furthermore, the expected gains of the intermittent pinning controllers are parameterized by solving a set of linear matrix inequalities. Finally, a numerical example is exploited to verify the effectiveness of our proposed theoretical results. [ABSTRACT FROM AUTHOR]

In this article, a protocol‐based H∞ filtering problem is investigated for piecewise linear (PWL) systems with mixed delays. Stochastic access protocol (SAP) is utilized to schedule the signal transmission via a constrained communication channel, under which only one measurement value can be transmitted to the filter at each time instant following a Markov process. When SAP is applied to PWL systems, only a part of system modes can be observed due to the incomplete measurement information. Therefore, a measurement‐dependent parameter storage rule with a certain probability distribution is introduced to overcome the difficulties coming from SAP‐induced incomplete information. By resorting to the proposed mode storage rule, a novel measurement‐dependent asynchronous H∞ filter model is constructed and the problem is converted into a new switching process of a larger state space following a reconstructed Markov process. Subsequently, a sufficient condition is established to guarantee the H∞ performance, and the probability‐dependent filter parameters are obtained by applying the stochastic analysis technique. Finally, a numerical example is given to show the effectiveness of the design approach. [ABSTRACT FROM AUTHOR]

Summary: The article develops a novel stubborn set‐membership filtering with the dynamic event‐triggered scheme for discrete‐time nonlinear systems with the state‐delays, unknown‐but‐bounded noises as well as abnormal measurements. First, in comparison with traditional event schemes, a dynamic event‐triggered scheme with a time‐varying auxiliary offset variable in the threshold is employed to schedule the access token with the purpose of mitigating the communication burden. A novel fuzzy stubborn filter in a distributed way is then constructed to obtain the ellipsoid set including the real state while constraining the direct influence of abnormal measurements, which could come from outliers or a malicious modification by attackers. An algorithm with the form of recursive linear matrix inequalities is presented to determine the desired ellipsoids as well as the distributed filter gains, where the operation of the algorithm do not depend on the global information of network topology. Finally, the validity of the proposed scheme is illustrated via an inverted pendulum system. [ABSTRACT FROM AUTHOR]

In this article, the design problem of ℓ2–ℓ∞ proportional–integral observer (PIO) is investigated for a class of discrete‐time systems with mixed time‐delays. The mixed time‐delays comprise both the discrete time‐varying delays and infinitely distributed delays. The round–robin protocol (RRP) is employed to schedule the data transmissions from the sensors to the observer so as to mitigate the communication burden and prevent the data collisions. A novel PIO is developed whose observer gain is dependent on the data transmission order as a reflection of the effects induced by the RRP scheduling. By resorting to the token‐dependent Lyapunov functional and the matrix inequality technique, the desired PIO is designed with exponentially stable error dynamics of the state estimation and guaranteed ℓ2–ℓ∞ disturbance attenuation/resistance capacity. Finally, a simulation example is exploited to verify the validity of the proposed observer design method. [ABSTRACT FROM AUTHOR]

Summary: This article focuses on the collaborative design of a class of discrete‐time switched systems with sojourn probabilities. For the purpose of preventing the data collision, the Try‐Once‐Discard (TOD) protocol is employed to govern the information transmission between sensors and the controller. Moreover, it is worth noting that the values of sojourn probabilities, which are not given ahead, have an effect on the system stability. As a consequence, a novel collaborative design framework is established, in which the sojourn probability and static output‐feedback controller are to be designed simultaneously. By considering the effect from the TOD protocol and using the Lyapunov function related to the mode and protocol, a sufficient condition is derived to guarantee the exponential mean square stability of the closed‐loop system with a prescribed lower bound on the decay rate. Then, the desired sojourn probabilities and controller gains dependent on the corresponding mode and protocol are obtained in terms of convex optimization method with equality constraints. Subsequently, an estimation approach is provided to estimate the decay rate and decay coefficient of the closed‐loop system. Finally, one numerical example is given to testify the effectiveness of the proposed design approach. [ABSTRACT FROM AUTHOR]

Summary: In this article, the robust model predictive control (RMPC) problem on the basis of output feedback (OF) is dealt with for a class of multirate time‐varying systems with polyhedral uncertainties and limited‐bandwidth channels. For alleviating the communication burden caused by the limited transmission capacity, the Round‐Robin (RR) protocol is exploited to allocate transmission permissions in a pre‐scheduled order. Meanwhile, in order to reduce the communication cost while ensuring the system performance, the multirate mechanism is presented to govern the update rate of the plant and the sampling rate of the sensors. By means of the lifting technique, given a uniform sampling rate, a comprehensive augmentation system is established on the fixed moving horizon. The objective of the addressed RMPC problem is to design a set of OF‐based RMPC controllers such that, in the presence of the multirate scheme and the RR transmission protocol, the desirable performance is guaranteed. Then, the desired RMPC gains are directly obtained, with the help of inequality analysis technique and RR‐dependent Lyapunov‐like approach, to ensure the asymptotic convergence of system states. Two illustrative examples are given, which include a DC motor system and a numerical simulation example, to demonstrate the effectiveness of the proposed protocol‐based RMPC controller design strategy. [ABSTRACT FROM AUTHOR]

Summary: This article investigates the extended Kalman filtering problem for a class of stochastic nonlinear systems with quantization effects and Round‐Robin (RR) communication protocols. The uniform quantization is considered and the resulting quantization error is characterized as an additive white noise sequence obeying the uniform distribution over certain intervals. For the sake of reducing communication traffic of the network as well as alleviating data collisions, the RR mechanism is introduced to schedule the data transmission from the sensors to the filter. By combining the periodic property of the RR protocol and the zero‐order holder strategy, the input signal of the filter is modeled by a sequence of delayed quantized measurements. The main purpose of this article is to design an extended Kalman filter for the stochastic nonlinear systems, in the simultaneous presence of quantization errors, stochastic nonlinearities, and stochastic noises, such that an optimized upper bound for the filtering error covariance is derived. By solving two coupled Riccati‐like difference equations, the filter gain matrix is explicitly formulated. An RR protocol‐based recursive filtering algorithm is developed for the online implementation. Furthermore, a sufficient condition is established to ensure the uniform boundedness of the filtering error in the mean‐square sense. Finally, a simulation example is given to demonstrate the practical validity of the designed filter algorithm. [ABSTRACT FROM AUTHOR]

Summary: In this article, the finite‐time fault tolerant control problem is investigated for a class of discrete‐time stochastic parameter systems subject to censored measurements. For the sake of relieving the communication burden, a stochastic communication protocol governed by a Markov chain is employed to determine which actuator has the access to the network at each transmission instant. Moreover, an improved performance index dependent on the predetermined censored threshold is constructed to evaluate the disturbance rejection level of the fault tolerant controller in the simultaneous presence of both external disturbances and censoring effects. The main aim of the addressed problem is to design a fault tolerant controller such that the closed‐loop system satisfies both the stochastically finite‐time boundedness and H∞ performance requirements. In light of the Lyapunov theory combined with matrix inequalities, some sufficient conditions are derived skillfully, and the desired controller gains are calculated by solving a set of linear matrix inequalities. Finally, two simulation examples are utilized to demonstrate the effectiveness of the developed controller design method. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with distributed entropy filtering for a class of time‐varying systems subject to non‐Gaussian noises and denial‐of‐service attacks. A distributed Kalman‐type filter is constructed by fusing the information from neighboring sensors in the one‐step prediction estimation. The maximum correlation entropy criterion with weighted Gaussian kernels instead of the traditional least squares and minimum variance indices is then employed to evaluate the filtering performance under the more general case of non‐Gaussian noises. For the considered scenario, a new algorithm of distributed maximum correntropy criterion Kalman filters is developed by utilizing traditional fixed‐point iterative rules, and the desired filter gains are dependent on both the one‐step prediction cross‐variance and the weighted Gaussian kernel function. In light of a similar analysis process and an introduced auxiliary cost, its suboptimal version is proposed to avoid the calculation of cross‐variance and thereby satisfying the requirement of real time. Furthermore, a degenerated result is also derived under the traditional correntropy criterion (ie, with unit weighted matrices). Finally, the simulation results show the merit of proposed distributed maximum correntropy criterion Kalman filters in the presence of denial‐of‐service attacks and non‐Gaussian noises. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a codesign strategy of an event‐triggered scheme and a fault detection filter (FDF) is developed for the networked switched systems with delayed measurements. A novel switching rule is proposed to better describe the switching behavior in a real system, under which the probability staying in each subsystem is time varying and results in a piecewise continuous system dynamics. An event‐triggered strategy based on the relative error with respect to the delayed measurement signal is established to reduce the communication burden. Our attention is concentrated on the construction of an event‐triggered fault detection technique for the proposed switched system with delayed measurements. Combining the stochastic analysis techniques and the average dwell time (ADT) method, a sufficient condition is obtained to guarantee the finite‐time boundedness of the generated residual system, the sensitivity of the residual signal to faults, and the disturbance attenuation of the switched system to external disturbances. Based on the established condition, a codesign strategy is developed to get the event‐triggered threshold and the FDF gain. Finally, two simulation results verify the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

Summary: This paper provides a reliable fusion scheme over sensor networks subject to abnormal measurements and energy constraints. Two kinds of channels are employed to implement the information transmission in order to extend the lifetime. Specifically, the one has the merit of high reliability by sacrificing energy cost and the other reduces the energy cost but could result in packet loss. For the addressed problem, a χ2 detection in local state estimator is first designed to remove abnormal measurements, which could come from outliers or a malicious modification by attackers. Then, a new strategy is developed to compensate the lost local estimation transmitted by low‐reliable channels. Furthermore, by view of matrix operation and probability theory, a set of recursive formulas are developed to calculate desired error covariance matrices of local state estimation, compensated state estimation as well as fusion estimation. The optimal fusion weights are obtained analytically and the advantage of fusion estimation is disclosed by resorting to these covariance matrices. Finally, a numerical example is used to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the issue of the finite‐horizon H∞ fault estimation is dealt with for a class of discrete time‐varying systems subject to randomly occurring faults and multiple fading measurements. The missing phenomena may occur in a random way from different sensors, which is represented by an individual stochastic variable meeting a certain probability distribution. Furthermore, in order to alleviate the communication burden, the torus‐event–based protocols are adopted to schedule the data transmissions only when some significant events occur. Our aim of the presented issue is to estimate the fault such that, with multiple fading measurements via the received information governed by torus‐event–based protocols, the H∞ index is satisfied over a given finite horizon. Sufficient conditions are obtained for the desired time‐varying estimator in terms of the technique of stochastic analysis and the methods of completing squares. The desired estimator gains are calculated by working out two backward recursive Riccati difference equations. Finally, a numerical simulation is given to verify the usefulness of our designed fault estimation approach. [ABSTRACT FROM AUTHOR]

In this study, the event‐triggered distributed fault detection problem is investigated for a class of discrete‐time uncertain systems in the finite frequency domain. A sensor network is utilised to collect the information of interest, and an event‐triggered communication scheme is adopted to alleviate the communication burden. For the addressed problem, a distributed fault detection filter is designed based on the measurement information from its neighbouring nodes and itself by the given topology. In addition, a fashionable index, named as H−/H∞ performance, is employed in order to simultaneously achieve the residual sensitivity to faults and the robustness against disturbances. By resorting to Euler's formula combined with Lyapunov stability theory, some sufficient conditions are established to satisfy the desired performance over a given finite‐frequency domain, and the distributed fault detection filter gains are explicitly characterised by solving a series of linear matrix inequalities. A simulation example is conducted to illustrate the feasibility of the proposed filter design technique. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the robust model predictive control (RMPC) problem for polytopic uncertain systems with state saturation nonlinearities under the Round‐Robin (RR) protocol. With respect to the practical application, one of the most commonly encountered obstacles that stem from the physical limitation of system components, ie, state saturation, is adequately taken into consideration. In order to reduce the network transmission burden and improve the utilization of the network from the controller nodes to the actuator node, a so‐called RR protocol is employed to orchestrate the data transmission order. At each transmission instant, only one controller node that obtains the priority is accessible to the shared communication network. Our aim of the underlying problem is to design a set of controllers in the framework of RMPC such that the closed‐loop system is asymptotically stable. By taking the influence of the RR protocol and the state saturation precisely into account, some sufficient criteria are established in terms of the token‐dependent Lyapunov‐like approach. Then, an online optimization problem subjected to some matrix inequality constraints is provided, and the desired controllers can be obtained by solving the certain upper bound of the objective addressed. Finally, a distillation process example is provided to illustrate the effectiveness of the proposed RMPC approach. [ABSTRACT FROM AUTHOR]

This study investigates the security problem for a class of polytopic uncertain systems by virtue of robust model predictive control (RMPC) approach. In consideration of the difficulties in accessing the system states, a novel dynamic‐output‐feedback RMPC strategy is presented to guarantee the security of the discussed system subject to randomly occurring deception attacks and persistent bounded disturbances. Such the randomly occurring attack is characterised by using a Bernoulli binary distributed white sequence with a given successful probability. Under this condition, a novel concept of system security in mean‐square sense is presented based on RMPC technique, in which the system is required not only to satisfy the specified performance index but also to keep all the states in an invariant set by designing a time‐varying terminal constraint set. Moreover, due to the presence of the persistent bounded disturbances and model uncertainties, the worst‐case cost function is considered. By using a Lyapunov function approach dependent of the input‐to‐state stability (ISS), the dynamic‐output‐feedback RMPC scheme is designed by solving an optimisation problem including some inequality constraints, and the upper bound of the investigated cost function is obtained. In addition, the ISS performance is ensured for the polytopic uncertain system with both the randomly occurring deception attacks and persistent disturbances. Finally, a numerical simulation example is developed to show the effectiveness of the proposed dynamic‐output‐feedback RMPC strategy. [ABSTRACT FROM AUTHOR]

This study is concerned with the finite‐horizon bounded H∞ synchronisation and state estimation for the discrete‐time complex networks with missing measurements based on the local performance analysis. First, a new local description of the bounded H∞ synchronisation performance index is proposed, which considers only the synchronisation errors among neighbours. In addition, a more general sector‐bounded condition is presented, where the parameter matrices are different for different node. Next, by establishing the vector dissipativity‐like for the complex network dynamics, the H∞ synchronisation criterion is derived in term of the locally coupled conditions for each node. These conditions implemented in a cooperative manner can judge whether the complex network reaches synchronisation. Similarly, the existence conditions for the estimator on each node are obtained, and then the estimator parameters are designed via the recursive linear matrix inequalities. Notably, these conditions on each node by cooperation among neighbours can achieve the desirable performance index. The distinctive features of the authors' algorithms are low complexity, scalability, and distributed execution. At last, two numerical examples are utilised to verify the effectiveness and applicability of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In networked systems, intermittent failures in data transmission are usually inevitable due to the limited bandwidth of the communication channel, and an effective countermeasure is to add redundance so as to improve the reliability of the communication service. This paper is concerned with the model predictive control (MPC) problem by using static output feedback for a class of polytopic uncertain systems with redundant channels under both input and output constraints. By utilizing the min-max control approach combined with stochastic analysis, sufficient conditions are established to guarantee the feasibility of the designed MPC scheme that ensures the robust stability of the closed-loop system. In terms of the solution to an auxiliary optimization problem, an easy-to-implement MPC algorithm is proposed to obtain the desired sub-optimal control sequence as well as the upper bound of the quadratic cost function. Finally, to illustrate its effectiveness, the proposed design method is applied to control a networked direct current motor system. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study is concerned with the event‐based security control problem for a class of discrete‐time stochastic systems with multiplicative noises subject to both randomly occurring denial‐of‐service (DoS) attacks and randomly occurring deception attacks. An event‐triggered mechanism is adopted with hope to reduce the communication burden, where the measurement signal is transmitted only when a certain triggering condition is violated. A novel attack model is proposed to reflect the randomly occurring behaviours of the DoS attacks as well as the deception attacks within a unified framework via two sets of Bernoulli distributed white sequences with known conditional probabilities. A new concept of mean‐square security domain is put forward to quantify the security degree. The authors aim to design an output feedback controller such that the closed‐loop system achieves the desired security. By using the stochastic analysis techniques, some sufficient conditions are established to guarantee the desired security requirement and the control gain is obtained by solving some linear matrix inequalities with non‐linear constraints. A simulation example is utilised to illustrate the usefulness of the proposed controller design scheme. [ABSTRACT FROM AUTHOR]

In this paper, a distributed output feedback model predictive control (OFMPC) algorithm is presented for the polytopic uncertain system subject to randomly occurring actuator saturation and packet loss. Compared with the intensively applied state feedback control in MPC, the OFMPC is more feasible to the real world because the system states are often unmeasurable. With taking both actuator saturation and packet loss into account, the presented OFMPC algorithm is more practical. Moreover, by splitting the controller inputs into two independent parts, the presented dynamic output feedback control (DOFC) strategy provides more freedom to the controller design. With the global system decomposed into some subsystems, the computation complexity is reduced, thus the online designing time can be saved. By defining the estimation error function and forming an augmented system to handle the DOFC and by transforming the nonlinear feedback law into a convex hull of linear feedback laws, the distributed controllers are obtained by solving a linear matrix inequality (LMI) optimization problem. Finally, some simulation examples are employed to show the effectiveness of the techniques proposed in this paper. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this study, the stochastic sampled‐data approach is developed to deal with the H∞ control problem for a class of linear multi‐agent systems. For each agent, signals should be transmitted to the control input, including not only its own measurements, but also the output information received from the neighbour agents. The relationships of information communications between the whole multi‐agents are totally reflected by a weighted directed graph with a fixed topology structure. To the addressed problem, the author's focus is to design an output feedback controller for each agent such that, for the external energy bounded disturbances, the exponential stability in the mean square sense and interference rejection ability under consideration can be guaranteed. By assuming that the sampling period of each agent switches between two values in a probabilistic way, the stochastic sampling phenomenon is well characterised in every sampling tasks. In virtue of Lyapunov theory and semi‐definite programming method, sufficient conditions are derived to ensure the exponential stability as well as H∞ performance, and the feedback controllers are also designed by solving some certain matrix inequalities. Finally, a numerical simulation is given to demonstrate the validness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper investigates the output feedback stabilization of stochastic nonholonomic systems which have both nonlinear drifts and Markovian switching. The state-scaling and backstepping techniques are exploited in the design of control laws. The output feedback stabilizing control laws and switching control strategy are proposed so that the closed-loop system can be stabilized in probability in the large. In the end, an example of nonholonomic mobile robots is provided to illustrate the effectiveness of control laws. [ABSTRACT FROM AUTHOR]

This study considers robust H∞ filtering for discrete system with uncertain multiple missing measurements and probabilistic non‐linearities. The measurement missing rate is assumed to be known with uncertainties and the non‐linearities' variation information between different bounds is utilised to build new type of non‐linearity model. Employing these new characteristics, new filtering error dynamics with time delay and uncertainties are proposed. By using Lyapunov functional approach, sufficient conditions on the H∞ performance analysis are obtained, and the desired filter parameters can also be obtained by solving certain linear matrix inequalities. Finally, an example is proposed to show the effectiveness of the proposed model and design procedures. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, the gain-scheduled control problem is addressed by using probability-dependent Lyapunov functions for a class of discrete-time stochastic delayed systems with randomly occurring sector nonlinearities. The sector nonlinearities are assumed to occur according to a time-varying Bernoulli distribution with measurable probability in real time. The multiplicative noises are given by means of a scalar Gaussian white noise sequence with known variances. The aim of the addressed gain-scheduled control problem is to design a controller with scheduled gains such that, for the admissible randomly occurring nonlinearities, time delays and external noise disturbances, the closed-loop system is exponentially mean-square stable. Note that the designed gain-scheduled controller is based on the measured time-varying probability and is therefore less conservative than the conventional controller with constant gains. It is shown that the time-varying controller gains can be derived in terms of the measurable probability by solving a convex optimization problem via the semi-definite programme method. A simulation example is exploited to illustrate the effectiveness of the proposed design procedures. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]