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An innovative technique for developing fuzzy preview tracking control nonlinear systems using Takagi‐Sugeno (T‐S) fuzzy models is discussed. The design considers robustness against state time‐changing latency, input saturation, and reference tracking. To achieve this, the T‐S fuzzy system was combined with time‐changing latency and input saturation to create an augmented error system, transforming the original fuzzy preview tracking control issue into a stability issue for the augmented error systems. Next, a new fuzzy preview tracking controller was developed by considering the T‐S fuzzy systems' states or outputs, a distinct integrator, and a previewed reference signal to solve the tracking control issue. For the augmented error system's asymptotic stability, new adequate conditions were derived by employing the fuzzy Lyapunov function, small gain theory, and linear matrix inequality (LMI) method. Finally, the proposed method's effectiveness was demonstrated using two numerical examples. [ABSTRACT FROM AUTHOR]

ABSTRACT This article investigates anti‐attack stabilization with passivity problem of uncertain singular semi‐Markov jump systems (singular S‐MJSs) with exogenous disturbance and delay. An ingenious non‐fragile observer‐based neural sliding mode control (SMC) scheme is put forward to solve the problem. First, considering unmeasured states, a distinctive non‐fragile and decoupled observer, which does not contain the control input or any auxiliary sliding mode compensator design as in existing observer‐based SMC approaches, is established such that the disadvantages of sliding mode switching in observers in existing literature can be avoided. Then, “only one sliding surface” design and a new system analysis route are presented, and the derived sliding surface is accessibly designed. Next, a new version of stochastic admissibility and passivity sufficient condition is given, and a related algorithm via an optimization problem is proposed to determine the controller gain and the observer gain by linear matrix inequalities (LMIs). Further, a novel observer‐based anti‐attack neural SMC law, which utilizes a neural network‐based approach to approximate actuator attack, is proposed to stabilize the singular S‐MJSs against actuator attack. Finally, simulation and comparison results are presented, which demonstrate the effectiveness and superiority of our method. [ABSTRACT FROM AUTHOR]

In this article, we address the topics of fault reconstruction and robust fault‐tolerant tracking control for periodic piecewise polynomial uncertain systems with time‐varying delays, faults and external disturbances. In detail, the periodic piecewise polynomial learning observer system is configured with the intent to concurrently reconstruct the faults and immeasurable states of the system that is being considered. Precisely, the key intent of this study centers around in devising a robust fault‐tolerant tracking control to achieve the tracking performance of the system as intended with mixed H∞$$ {H}_{\infty } $$ and passivity performance. To this end, a robust fault‐tolerant tracking control is designed by incorporating the reconstructed faults and error feedback, which aids in vouching for the outcomes that were desired. Besides, by building the periodic piecewise polynomial Lyapunov–Krasovskii functional and making use of the matrix polynomial lemma and Wirtinger's inequality, certain adequate conditions are procured in the frame of linear matrix inequalities. Subsequently, the required gain values for the devised controller and the configured observer are found by using the established linear matrix inequalities. Ultimately, in order to attest the controller's intrinsic potential and relevance, numerical example along with the simulation results is supplied. [ABSTRACT FROM AUTHOR]

ABSTRACT In this article, the reachable set estimation problems for a class of singular discrete‐time nonlinear systems (SDNS) with time‐varying delay (TVD) are presented. First, we employ a Lyapunov function scheme and utilize zero‐type free matrix equations. Based on this, a criterion is derived in the form of linear matrix inequalities (LMIs) to guarantee that the considered system to be regular, causal, and the state trajectory x1$$ {x}_1 $$ of the system is bounded. Second, by developing the singular systems decomposition technique into slow and fast subsystems and using the introduced auxiliary lemma, we establish that the x2$$ {x}_2 $$ state trajectory of the fast subsystem is also bounded, and the reachable set of singular nonlinear system is bounded within the ellipsoid. Finally, Numerical examples are presented to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article addresses the static output feedback load frequency control (LFC) problem for semi‐Markov type interconnected multi‐area power systems (IMAPSs) through non‐fragile proportional‐integral (PI) strategy. Primarily, by roundly exploiting the dynamical properties and considering random mutations of the IMAPSs, the semi‐Markov jump process (MJP) is elaborately scheduled for establishing the dynamical model with precision. Subsequently, on account of the characteristic of geographical isolation, a memory‐like sampled‐data LFC mechanism considering time‐varying transmission delay for the semi‐Markov jump IMPASs is formulated accordingly. Additionally, the non‐fragile issue is explored for the PI controller gain fluctuations to meet the actual operation scenario. After that, a mode‐dependent two‐side polynomial‐type looped Lyapunov functional is constructed for enhancing flexibility. Then, in virtue of the stochastic analysis technique, some relaxed conditions guaranteeing stochastic stability with prescribed H∞$$ {H}_{\infty } $$ performance are thereby derived in the shape of linear matrix inequalities (LMIs). Ultimately, a numerical example is carried out to validate the efficacy of the developed control methodology. [ABSTRACT FROM AUTHOR]

This article addresses the problem of designing an event‐triggered fault detector within a networked nonlinear system described by a Takagi–Sugeno (T–S) fuzzy model, accounting for time‐varying delays and denial‐of‐service (DoS) attacks characterized by a binary Markov chain. Our focus is on constructing an event‐triggered residual system, which aims to detect malfunctions in the original fuzzy system while optimizing communication resource allocation. Specifically, it is tailored to combat DoS attacks in the event generator‐to‐fault detector channel and mitigate network‐induced time‐varying delays. Utilizing the Lyapunov–Krasovskii function approach, we formulate linear matrix inequalities to establish the necessary conditions ensuring the asymptotic mean‐square stability of the residual system, meeting a predefined H∞$$ {H}_{\infty } $$ performance criterion. Finally, the simulation results are presented to validate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This article considers exponential stabilization (ES) of switched interval type‐2 (SIT2) fuzzy systems with asynchronous switching control. The SIT2 fuzzy system switches from one mode to another according to transition probabilities (TPs). A general SIT2 fuzzy quantized event‐triggered output controller (QETOC) is designed to save the communication resources. The QETOC employs distinctive membership functions from those of the IT2 fuzzy model and switches with mode‐pendent switching delay, which is more practical than asynchronously switched control techniques with a common switching delay and control schemes without TP. By designing discretized multiple Lyapunov function (DMLF) and using convex combination technique, sufficient conditions formulated by linear matrix inequalities (LMIs) are obtained to ensure that the DMLF does not 'jump high' at the moment of switching, and hence the conservatism of obtained results is significantly reduced since no additional dwell time is needed for the stabilization. It is discovered that the SIT2 fuzzy system is not necessary to be unstable on mismatched intervals, and it can be unstable on matched intervals. The advantages of theoretical analysis are verified by numerical simulations, and the classical assumption that each subsystem is unstable on mismatched intervals is conservative for control design. [ABSTRACT FROM AUTHOR]

The purpose of this article is to propose a novel framework employing a looped‐functional approach for the stability analysis of continuous‐time linear systems with asynchronous sampling. In this approach, a negative forward‐difference of a Lyapunov functional consisting of a Lyapunov function and a looped‐functional sufficiently guarantees asymptotic stability of the sampled‐data systems. To reduce the conservatism of the stability criteria, we develop a consecutive time‐intervals‐dependent looped‐functional approach that satisfies a convex looping inequality with respect to each sampling interval. Compared to the existing looped‐functional approaches, the proposed method provides a more general looped‐functional and in turn a more relaxed stability conditions. The existing looped functionals and their associated looping conditions can be considered as special cases of the proposed ones. This relationship can easily be verified by excluding time‐intervals‐dependent terms in the general looped functional. Four numerical examples that consider both periodic and asynchronous sampling cases demonstrate that the proposed looped‐functional approach shows better performance in terms of allowable maximum sampling intervals at a cost of a small additional number of decision variables. [ABSTRACT FROM AUTHOR]

Summary: In this article, a memory event‐triggered mechanism (METM) based switching‐like control method is designed for a cyber‐physical system (CPS), maintain control performance and improve the communication efficiency under denial of service (DoS) attack. In order to obtain better control effect at small sampling periods, a sampler contains the explicit sampling period is designed by using delta operator approach. First of all, a METM based on an acknowledgement character (ACK) mechanism is proposed, which can reduce event triggered data calculations, increase the transmission instants at the crest or trough of the responses and reduce the negative impact of DoS attack. Next, a switching‐like control strategy for the delta operator system converted from the CPS is designed to prevent DoS attack resulting in open‐loop unstable operation of the system. Further, a switching law is designed to maintain the concealment of the secure channel. Then, sufficient conditions are derived for the CPS in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of the designed method is verified by a simulation example. [ABSTRACT FROM AUTHOR]

This article investigates the robust consensus problem for nonlinear multiagent systems against time‐varying false data injection attacks on actuators and sensors. First, the root‐mean‐square (RMS) theory is used to extend the assumption of the slow‐varying or constant attack signals to the case of time‐varying attack signals. Second, a novel distributed multivariate observer (DMO) is designed to estimate the followers' system states and the time‐varying attack signals on actuators and sensors. With the help of the outputs of DMO, a distributed robust consensus control arithmetic is proposed, which can compensate for actuator attacks and isolate sensor attacks so that exponential consensus and robust consensus are achieved. In particular, the robust performance of estimation errors and consensus errors is ensured by establishing the RMS gain index via linear matrix inequality, in which the zero initial conditions of estimation errors and consensus errors are not required. Finally, two simulation examples, including a network of four aircraft longitudinal dynamic systems, are given to verify the effectiveness of the proposed arithmetic. [ABSTRACT FROM AUTHOR]

This article presents a robust security‐based model predictive control (MPC) framework for a class of discrete‐time nonlinear cyber‐physical systems (CPSs) suffering random deception attacks and persistent actuator saturation. In CPSs, the attacks can significantly degrade the control performance. Naturally, a larger degree of control is required, prompting the consideration of actuator saturation in CPS's structure. In our work, the cyberattacks on the controller‐actuator (C‐A) channel are described as a stochastic process with specific probability and bounded energy. The security‐related constraint is introduced to improve the resistance and robustness against attacks. Mean‐square quadratic boundedness is derived to estimate the robustly invariant set. By placing the saturated input into a convex hull, a robust security‐based MPC optimization problem is addressed less conservatively with linear matrix inequality technique. Furthermore, the feasibility of the proposed method is proved recursively, and the stability and security of the closed‐loop system are established in mean‐square sense. In the end, the laboratory tank and reactor‐separator process are applied to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This article is dedicated to event‐triggered anti‐disturbance control of networked control systems via a guaranteed cost triggering scheme. A distribution interconnected observer structure is built to estimate these unknown matched disturbances. A novel event triggered condition is constructed in terms of real‐time cost and averaged functions composed of observer states and the last successfully transmitted one. A composite control scheme is provided by an event‐triggered observer‐based state feedback controller and compensators for the matched disturbances. A sufficient condition in term of linear matrix inequality is supplied to ensure the asymptotic stability of the resultant closed‐loop system. A simulation is carried out to demonstrate the effectiveness of the proposed triggering control strategy. [ABSTRACT FROM AUTHOR]

This paper mainly concerns on the tracking control problem for event‐triggered networked control systems (NCSs) with diversified cyber‐attacks. An event‐triggered mechanism (ETM) is exploited to decrease the amount of redundant transmissions, thus saving communication resources. In addition, a novel tracking error model for NCSs is built with consideration of ETM and diversified cyber‐attacks, which involves deception attacks and Denial‐of‐Service (DoS) attacks. On the basis of Lyapunov stability theory and linear matrix inequalities (LMIs), the stability criterion of the tracking error system is constructed, and the controller is designed to ensure the tracking performance of the system. In the end, simulation examples are provided to testify the validity of the proposed method. [ABSTRACT FROM AUTHOR]

This article focuses on the finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering problem for discrete‐time singular systems with randomly occurring nonlinear perturbations. The main purpose is to design a filter, which ensures the singular error system is stochastically finite‐time bounded and satisfies mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive performance. By constructing an augmented matrix, the properties of matrix determinant and rank are used to prove that the singular system is regular and causal, Finsler's lemma and Projection lemma are used in the design process to acquire additional slack variable matrices, thereby enhancing the solution space with extra degrees of freedom. Then, the unknown parameters of the filter are obtained by solving the less conservative linear matrix inequalities. Finally, the feasibility of the proposed method is verified through a common numerical example and by controlling a DC motor for an inverted pendulum. [ABSTRACT FROM AUTHOR]

This paper deals with finite‐horizon minimum‐variance and covariance steering problems subject to constraints. The goal of the minimum variance problem is to steer the state mean of an uncertain system to a prescribed vector while minimizing the trace of its terminal state covariance whereas the goal in the covariance steering problem is to steer the covariance matrix of the terminal state to a prescribed positive definite matrix. The paper proposes a solution approach that relies on a stochastic version of the affine disturbance feedback control parametrization. In this control policy parametrization, the control input at each stage is expressed as an affine function of the history of disturbances that have acted upon the system. It is shown that this particular parametrization reduces the stochastic optimal control problems considered in this paper into tractable convex programs or difference of convex functions programs with essentially the same decision variables. In addition, the paper proposes a variation of this control parametrization that relies on truncated histories of past disturbances, which allows for sub‐optimal controllers to be designed that strike a balance between performance and computational cost. The suboptimality of the truncated policies is formally analyzed and closed form expressions are provided for the performance loss due to the use of the truncation scheme. Finally, the paper concludes with a comparative analysis of the truncated versions of the proposed policy parametrization and other standard policy parametrizations through numerical simulations. [ABSTRACT FROM AUTHOR]

Different from the Mittag–Leffler stability or asymptotic stability, the exponential stability issue, which provides faster and explicit convergence rate, is studied in this paper for fractional‐order uncertain systems with asynchronous switching and impulses, where the impulsive functions rely on not only switching modes but also impulsive time. Instead of using the inequality Eα(t)≤1αexp(t1α)(0<α<1)$$ {E}_{\alpha }(t)\le \frac{1}{\alpha}\exp \left({t}^{\frac{1}{\alpha }}\right)\kern0.3em \left(0<\alpha <1\right) $$, by utilizing the theory of fractional‐order differential equations, the methods of Lyapunov function and mathematical induction, some novel and less‐conservative stability criteria are developed, respectively, for the case of switched stable subsystems or switched unstable subsystems. The obtained results build a tradeoff between impulsive function, impulsive interval, average dwell time and fractional order. In addition, our results with α=1$$ \alpha =1 $$ are also novel in contrast with the ones of integer‐order switched impulsive systems. Finally, five numerical examples are given to show the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

This article investigates the output feedback H∞$$ {H}_{\infty } $$ control problem of linear systems with infinite distributed input delays. An observer‐based output feedback (OBOF) H∞$$ {H}_{\infty } $$ controller is proposed via the predictor feedback approach, and a sufficient condition for the existence of the OBOF H∞$$ {H}_{\infty } $$ controller is given in terms of a set of linear matrix inequalities. It is shown that the resulting closed‐loop system is globally exponentially stable with a prescribed H∞$$ {H}_{\infty } $$ performance. The obtained results include some results on the same problem for linear systems with bounded distributed input delays as special cases. Two numerical examples are finally presented to illustrate the effectiveness of the proposed H∞$$ {H}_{\infty } $$ controller. [ABSTRACT FROM AUTHOR]

This article considers a path tracking control problem for autonomous vehicles constrained to maintain a safe distance from the next vehicle in the lane. The control design problem is solved by considering a mathematical model of the vehicle that jointly describes the lateral and longitudinal dynamics. Specifically, the ℒ2$$ {\mathcal{L}}_2 $$ optimal controller is designed aimed at minimizing the orientation and position tracking errors with respect to a given reference path. Moreover, the controller is able to ensure that the vehicle can both follow a speed profile and automatically adjusts the vehicle speed to maintain a proper distance from the next vehicle. The lateral dynamic is regulated by a 2‐DOF feedforward/feedback controller, where the feedforward law is implemented by exploiting an inverse kinematic model of the vehicle. On the other side, the feedback action, along with the action of the controller in charge to regulate the longitudinal dynamics, is the ℒ2$$ {\mathcal{L}}_2 $$ optimal gain‐scheduling state‐feedback controller. In particular, a parameter‐dependent quadratic Lyapunov function approach is used to reduce the conservativeness of the solution and a suitable convex LMI optimization problem is formulated for the synthesis. The vehicle is described by a seven‐degrees‐of‐freedom (7DOF) full‐car model, with the tire‐generated forces described by the classical Pacejka's Magic Formula. In order to assess the performance of the proposed control strategy, simulations have been undertaken in Matlab/Simulink by considering an autonomous vehicle driving into an urban scenario. [ABSTRACT FROM AUTHOR]

This article develops a neuro‐adaptive observer for state and nonlinear function estimation in systems with partially modeled process dynamics. The developed adaptive observer is shown to provide exponentially stable estimation errors in which both states and nonlinear functions converge to their true values. When the neural approximator has an approximation error with respect to the true nonlinear function, the observer can be used to provide an H∞$$ {H}_{\infty } $$ bound on the estimation error. The article does not require assumptions on the process dynamics or output equation being linear functions of neural network weights and instead assumes a reasonable affine parameter dependence in the process dynamics. A convex problem is formulated and an equivalent polytopic observer design method is developed. Finally, a hybrid estimation system that switches between a neuro‐adaptive observer for system identification and a regular nonlinear observer for state estimation is proposed. The switched operation enables parameter estimation updates whenever adequate measurements are available. The performance of the developed adaptive observer is shown through simulations for a Van der Pol oscillator and a single link robot. In the application, no manual tuning of adaptation gains is needed and estimates of both the states and the nonlinear functions converge successfully. [ABSTRACT FROM AUTHOR]

This paper studies the event‐triggered control of switched linear system with state‐dependent switching law. A dynamic term is introduced to the switching law to acclimatize the dynamic mode‐dependent event‐triggered controller. Besides, neither the switching law nor the controller needs continuous detection of the system states. Because of the event‐triggered and sampling behavior of the controller, asynchronous between the controller and the system modes are encountered. A new multiple Lyapunov functional is proposed to appropriately characterize the synchronous and asynchronous working modes of the system, and a sufficient exponential stability condition is obtained, which is applicable for the cases when some modes or all modes of the switched system are unstabilizable. Moreover, the event‐triggered control and switching law parameters are jointly designed using linear matrix inequalities. Numerical and comparison studies are offered to provide the validity and superiority of the result. [ABSTRACT FROM AUTHOR]

In this article, by considering the existence of unavailable state, external disturbance, and denial of service (DoS) attacks, an anti‐disturbance trajectory tracking controller is proposed for the air‐ground system composed of unmanned autonomous helicopter (UAH) and unmanned ground vehicle (UGV). Initially, by combining the advantages of conventional event‐triggered scheme (ETS) and memory ETS, a switching‐like event‐triggered mechanism is put forward, which can induce less data transmissions without reducing control performance, and effectively restrain the DoS attacks. Second, by dividing the DoS attacks into active intervals and sleep ones, the concept of acknowledgement character technology (ACK) is presented to define the suitable types of time intervals. Third, a switching‐like dynamic ETS is introduced for the sleep intervals of DoS attacks while the ETS with fixed triggered‐threshold is exploited for the active intervals. Fourth, based on the occurrence of DoS attacks, a switching‐like observer and a normal one are respectively proposed to estimate the UGV state, the UAH state, the reference input of the UGV, and the disturbance of the UAH, which are further utilized to design the tracking controller. Fifth, an augmented closed‐loop system consisting of observation errors and tracking error is established and its stability is analyzed by using Lyapunov stability theory. Then, a sufficient condition on co‐designing the parameters of switching‐like ETS, observers, and tracking controller is presented in terms of linear matrix inequalities (LMI). Finally, the validity and superiority of the proposed control scheme are verified by resorting to simulations and comparisons. [ABSTRACT FROM AUTHOR]

This paper presents a Youla‐Kucera based interpolation between a set of Linear Parameter‐Varying (LPV) controllers, each one being a gain‐scheduled of Linear Time‐Invariant (LTI) controllers designed separately for different operating points. The gain‐scheduling is achieved based on Youla‐Kucera (YK) parameterization. A generalized LPV‐YK control structure is designed to interpolate between various LPV controllers. The closed‐loop system is proved to guarantee the quadratic stability for any continuous/discontinuous interpolating signals in terms of a set of Linear Matrix Inequalities (LMIs). The proposed method can help multi‐variable and multi‐objective systems to achieve high performances at different operating conditions and different critical situations regardless of the interpolation rate. A numerical example is simulated to show the importance of the proposed method to achieve different objectives for lateral control of autonomous vehicles. In addition, the approach has been tested on a real Renault ZOE vehicle to validate its real performance, and compare it with a standard polytopic LPV controller. [ABSTRACT FROM AUTHOR]

This article studies the output feedback H∞$$ H\infty $$ control problem for event‐triggered Markovian jump networked control systems with signal quantization. First, a Lyapunov–Krasovskii function is constructed, which contains time delay, upper bound of time delay and conditional transition probability information of Markovian jump systems. Second, when using the Wirtinger's inequality and the Reciprocally convex inequality to estimate the upper bound of the delay of the weak infinitesimal generator operator of the Lyapunov–Krasovskii function, the event‐triggered scheme and the signal quantization scheme are introduced. Finally, the stability criterion of the closed‐loop system of event‐triggered Markovian jump networked control systems and the design method of the output feedback controller of H∞$$ H\infty $$ disturbance attenuation level γ$$ \gamma $$ are given in the form of linear matrix inequalities (LMIs). The effectiveness of the proposed method is verified by two numerical examples. [ABSTRACT FROM AUTHOR]

This article studies the fault‐tolerant consensus issue of a class of nonlinear two‐time‐scale‐agent systems with heterogeneous sensor faults and external disturbances. First, the decentralized proportional integral (PI) observer for each agent is constructed to estimate the states and sensor faults simultaneously. Then, a distributed adaptive protocol based on the decentralized PI observer is designed to guarantee the consensus of the underlying systems. Some sufficient existence conditions are given in terms of linear matrix inequalities (LMIs) for the decentralized PI observer and the fault tolerant consensus protocol. Note that H∞$$ {H}_{\infty } $$ performance index is employed to attenuate the influence of sensor faults and disturbances on state estimation and the consensus of the underlying systems. Finally, the effectiveness and superiority of the proposed method are demonstrated by an application example and a numerical example. [ABSTRACT FROM AUTHOR]

With the advancement in sensor and communication technology, autonomous systems have been incrementally reshaping the execution of tasks in commercial and military sectors. Since the systems are designed to complete tasks without or with minimal human intervention, fault diagnosis based on sensor data has been crucial to preventing accidents and fatalities. In this paper, fault diagnosis for autonomous systems is designed based on nonlinear adaptive observers, tested in numerical simulations, and implemented in a robotic platform. To this end, we utilize the persistence of excitation conditions on the parametric model of the faults. We derive sufficient conditions for the nonlinear adaptive observer in terms of linear matrix inequality to ensure the convergence of the estimates. Furthermore, we consider one‐sided Lipschitz conditions to obtain less conservative results. The main advantage of using the nonlinear adaptive observer is that the method converges quickly to the actual fault and requires minimum computational effort. However, solving the linear matrix inequality might not be trivial. Numerical simulations based on a single‐link flexible joint robot model and experimental tests in an autonomous quadcopter are performed to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, we study the absolute stabilization of switched Lurie system via dynamic output feedback, where the nonlinearity is unknown and is restricted in a sector. In most works, the nonlinearity is assumed to be known exactly or is restricted in a bounded sector. Here, we consider the most general case with unbounded sector. With the help of switched time‐varying Lyapunov–Lurie function, a dynamic output feedback controller with time‐varying control gain is presented. On this basis, sufficient conditions for absolute stabilization are derived in the framework of mode‐dependent minimum dwell time and mode‐dependent range dwell time. It turns out that this time‐varying control strategy can solve the absolute stabilization of switched Lurie systems that all subsystems are not stabilizable. Moreover, the stability criteria in terms of linear matrix inequality we derived can be easily checked via Matlab toolbox. Finally, the effectiveness of presented methods is verified by several numerical examples. [ABSTRACT FROM AUTHOR]

In this work we study the design of H2$$ {H}_2 $$ filters for phase‐type (PH) semi‐Markov jump linear systems, considering partial information on the system's operating mode and possible parameter uncertainties. With respect to the mode of operation, it is assumed that the state space of the semi‐Markov chain can be written as the union of disjoint sets, called clusters, and the only information available to the filter is which cluster the state of the semi‐Markov chain belongs to. A new linear matrix inequality (LMI) parameterization employing the slack variable technique is introduced for the design of switching full‐order filters according to the cluster observations so that suitable bounds on the H2$$ {H}_2 $$ norm of the estimation error are guaranteed for the uncertain system. If the system is restricted to be a Markov jump linear system and the Markov chain is assumed to be perfectly measured, the design conditions are shown to be also necessary leading to the optimal full‐order filter. Furthermore, the general filter can be particularized into an observer form for the case in which the system matrices are the same within each cluster and there are no parameter uncertainties except for possible uncertainties affecting the transition rates of the jumping process. The paper concludes with an illustrative example in the context of networked control systems. [ABSTRACT FROM AUTHOR]

In this article, the problem of the optimal reset control design for Lipschitz nonlinear systems is addressed. The reset controller includes a base linear controller and a reset law that enforces resets to the controller states. The reset law design is strongly dependent on the appropriate design of the base controller. For this reason, in this article, the base controller and reset law are simultaneously designed. More precisely, an optimal dynamic output feedback is considered as the base controller which minimizes the upper bound of a quadratic performance index, and a reset law is used to improve the transient response of the closed‐loop system. This design is done in a full offline procedure. The problem is transformed into a set of linear matrix inequalities (LMIs), and the reset controller is obtained by solving an offline LMI optimization problem. Finally, two examples are presented to illustrate the effectiveness and validity of the proposed method. [ABSTRACT FROM AUTHOR]

This article investigates the problem of secure memory adaptive event‐triggered filter design for nonlinear network systems under hybrid network attacks. First, the introduction of memory adaptive event‐triggered mechanism and numerical quantization is employed to enhance system performance, optimize network channel utilization, and prevent network congestion. Second, we consider the impact of deceptive attacks and DoS attacks occurring in the network channel on data transmission, which form the hybrid network attacks studied in this article. Subsequently, based on the established error model, we derive sufficient conditions for the mean‐square exponential stability of the system under a given H∞$$ H\infty $$ performance index using Lyapunov–Krasovskii function and linear matrix inequality (LMI) techniques. Furthermore, the filter parameters are determined using the LMI method. Finally, we illustrate the feasibility and generality of the conclusions through numerical simulation examples and a tunnel diode circuit system. [ABSTRACT FROM AUTHOR]

The structured singular value (SSV), or μ$$ \mu $$, is used to assess the robust stability and performance of an uncertain linear time‐invariant system. Existing algorithms compute upper and lower bounds on the SSV for structured uncertainties that contain repeated (real or complex) scalars and/or nonrepeated complex full‐blocks. This paper presents algorithms to compute bounds on the SSV for the case of repeated complex full‐blocks. This specific class of uncertainty is relevant for the input‐output analysis of many convective systems, such as fluid flows. Specifically, we present a power iteration to compute the SSV lower bound for the case of repeated complex full‐blocks. This generalizes existing power iterations for repeated complex scalars and nonrepeated complex full‐blocks. The upper bound can be formulated as a semi‐definite program (SDP), which we solve using a standard interior‐point method to compute optimal scaling matrices associated with the repeated full‐blocks. Our implementation of the method only requires gradient information, which improves the computational efficiency of the method. Finally, we test our proposed algorithms on an example model of incompressible fluid flow. The proposed methods provide less conservative bounds as compared to prior results, which ignore the repeated full‐block structure. [ABSTRACT FROM AUTHOR]

Summary: The reduced‐order observer‐based finite‐time control problem for one‐sided Lipschitz nonlinear switched singular systems is addressed in this paper. First, the design method of the reduced‐order observer is given via state transformation. Then, based on the average dwell time (ADT) approach, some new sufficient conditions for regularity, impulse‐freeness, have a unique solution and finite‐time boundedness (FTB) of the dynamic augmented systems are obtained by exploring the reduced‐order observer‐based controller. Further, the lower finite‐time bound can be obtained by using singular value decomposition method. And the state feedback gain and the observer gain are computed by solving linear matrix inequalities (LMIs). Finally, the validity of the obtained method is illustrated by means of a numerical example and a DC motor system. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a set‐membership state estimation method for Switched Linear Parameter Varying (SLPV) systems subject to unknown but bounded parametric uncertainties, disturbances and noises. A zonotopic outer approximation of the state estimation domain is computed at every time iteration. The size of this zonotope is designed to be convergent and bounded by satisfying P$$ P $$‐radius‐based and Average Dwell Time (ADT) conditions that are formulated in the Linear Matrix Inequality (LMI) framework. An extension of the state estimation method is presented to address the fault/disturbance estimation problem for SLPV systems. By using the state augmentation technique, the fault/disturbance estimation problem is transformed into a state estimation problem of the generated augmented descriptor switched LPV system. An application to vehicle lateral dynamics fault estimation is used for assessment purposes. Simulation results demonstrate the effectiveness of the proposed algorithm and highlight its advantages over the existing methods. [ABSTRACT FROM AUTHOR]

It is well known that control effort is the key factor considered in formation control of a multi‐agent system (MAS). To reduce the controller effort, an economic event‐triggered super twisting control (STC) protocol for the formation tracking of a nonlinear MAS, which avoids the unnecessary computations and transmission of control inputs among agents. Specifically, a distributed leader‐follower control framework, combing the multi‐input STC with event‐triggered strategy, is proposed to ensure that the followers' states reach an agreement on the leaders state. Then, the sufficient conditions for the selection of controller parameters are formulated in terms of linear matrix inequalities (LMIs). On this basis, the event‐triggered conditions for implementing the STC protocol in the network environment are obtained using Lyapunov stability theory. Simulation study is carried out to demonstrate the effectiveness and merits of the STC in terms of formation construction, trajectory tracking, and robustness to system uncertainties. [ABSTRACT FROM AUTHOR]

This article develops a novel event‐triggered subspace predictive control (ET‐SPC) method for discrete‐time linear parameter‐varying (LPV) systems with partially unknown system parameters. An event‐triggered law is developed to alleviate the heavy load of data transmission and computation in the conventional subspace predictive control methods for the LPV systems. The design of the event‐triggered law relies on the input‐to‐state stability (ISS) theory and applies the robust stability condition based on linear matrix inequalities (LMIs), which guarantees the stability of the proposed method. Consequently, the input component can be directly transmitted to the system without receding horizon optimization when the event‐triggered law evaluates that the system satisfies the stability condition. The simulation results illustrate its satisfactory performance, which indicates its potential application involving a considerable amount of data transmission and computation such as the network control systems (NCSs). [ABSTRACT FROM AUTHOR]

This note puts forward continuous event‐triggered impulsive control (CETIC) and dynamic event‐triggered impulsive control (DETIC) to discuss a class of (integral) input‐to‐state stability (iISS, ISS) for nonlinear systems (NSs), where the impulse sequences are produced by certain predesigned event‐triggering conditions. Different from traditionary event‐triggered control (ETC), CETIC indicates that a controller will be stimulated only if the given state‐dependent event condition is invoked. There exist no transfer of control between two continuous impulse triggered instants. Compared with the traditional static ETC, the DETIC can efficaciously lessen controller update and dramatically save energy at the same decay rate. In addition, all sample path solutions (SPS) for the system have the lowest time between events guaranteed to be positive. Utilizing CETIC strategy, we get some Lyapunov conditions to effectually avoid infinite triggering behavior and obtain the ISS‐type stability of the investigative systems. Then, one applies the theoretical consequences to NSs and derive a class of ETC mechanism with impulsive control gains (ICG) by linear matrix inequalities (LMIs). Because of the existence of timer, the DETIC strategy naturally excludes Zeno phenomena. Furthermore, conclusions in this thesis permit the upper bound estimation for the differential Lyapunov function coefficient to be time‐varying function instead of a constant in certain extant results, which means the criteria of the Lyapunov technique in this paper is less conservative and looser. Eventually, three examples with related simulations are demonstrated to indicate the rationalization and usefulness of our conclusion. [ABSTRACT FROM AUTHOR]

In this paper, the H∞$$ {H}_{\infty } $$ saturated control problems of networked systems with random sampling periods and stochastic transmission delays are investigated. The main issue is to design an H∞$$ {H}_{\infty } $$ saturated controller such that the controlled close‐loop system is exponentially mean‐square stable with a desired H∞$$ {H}_{\infty } $$ performance. A matrix exponential which is different from some existing literature is used to reconstruct the discrete‐time stochastic system to an equivalent yet tractable augmented model without any additional conditional constraint. In virtue of reduced‐order confluent Vandermonde matrix approach and Kronecker product operation, the stability condition in terms of linear matrix inequality is derived and then the desired H∞$$ {H}_{\infty } $$ saturated controller is designed. It should be emphasized that the improved method can also be used for the stability analysis and controller design when the system matrix contains complex roots. Finally, two numerical examples and a three‐axis milling machine system are utilized to manifest the reliability and practicality of the designed strategy. [ABSTRACT FROM AUTHOR]

This work investigates the synchronization problem for a kind of discrete complex dynamical networks (CDNs) including nonlinearities, exogenous disturbance, and successive time‐varying random coupling delays. Also, the stochastic variable obeying Bernoulli distribution is exploited to describe the randomness of the coupling delays. The main target of this work is to devise a novel PID controller ensuring that the proposed network is asymptotically synchronized in mean‐square and also meets a specified extended dissipative performance. With the aid of Kronecker product properties, Lyapunov stability theory and free weighting matrix technique, less conservative sufficient criteria is obtained in the form of Linear matrix inequalities (LMIs) to affirm the synchronization of the considered network. At last, the efficacy and potency of the designed control protocol are verified through two examples including the Chen system. [ABSTRACT FROM AUTHOR]

The main focus of this article is to explore the finite‐time stabilization of time‐varying cyber‐physical systems (CPS) that are operating over multipath networks and under random denial‐of‐service (DoS) attacks. In contrast to prior studies, we present a set of necessary and sufficient conditions for achieving finite‐time stability in the closed‐loop model of CPS operating over single‐path network. Notably, this equivalent conditions are established based on the analysis of the state transition matrix (STM). Additionally, we utilized auxiliary systems to study more general CPS operating over multipath networks and obtained a sufficient condition based on STM. Finally, we address a sufficient condition based on the Lyapunov function and introduce a linear matrix inequality (LMI)‐based approach that facilitates the computation of nonfragile controllers. The effectiveness of the developed theoretical results is verified through a stock investment model. [ABSTRACT FROM AUTHOR]

This paper presents a prescribed performance‐based model‐free adaptive resilient control (MFARC) algorithm to address the realization of trajectory tracking for nonlinear cyber‐physical systems (CPSs) under aperiodic denial‐of‐service (DoS) attacks. Firstly, an equivalent linear model is constructed by utilizing the dynamic linearization technique, and a novel output transformation approach is applied to convert the constrained system to an unconstrained one for the MFARC framework. Then, an attack compensation mechanism is presented to estimate the unavailable output signal when attacks are active, such that the negative impact of aperiodic DoS attacks can be compensated. Based on the unconstrained model and the compensation mechanism, a prescribed performance‐based MFARC strategy is constructed to steer the tracking error to the predetermined neighborhood around the origin in the presence of DoS attacks. A major improvement of our result over previous studies is the introduction of prescribed performance control (PPC) into MFARC while reasonably restricting the transient and steady‐state performance of the tracking error even when DoS attacks occur. Additionally, we utilize the linear matrix inequality (LMI) toolbox to obtain better tracking performance by suitably adjusting the time‐varying parameters, which is superior in practical applications. Ultimately, our results indicate that the tracking error consistently remains within a predefined bound. [ABSTRACT FROM AUTHOR]

This article aims to address the reliable quantized sampled‐data load frequency control (LFC) synthesis problem for semi‐Markov jump interconnected multi‐area power systems (IMAPSs) suffering from incomplete transition rates (TRs) and actuator failures. Primarily, the semi‐Markov process configurated with incomplete TRs is utilized to model the structural and coefficient switchings of IMAPSs, which enables a more precise representation of reality and a wider range of application. Subsequently, in order to reduce the control cost and facilitate data processing, an aperiodic quantization sampling mechanism is introduced. Furthermore, a mode‐dependent and comprehensive actuator faulty model is scheduled to portray various stochastically occurring actuator failures, which is more in line with practical application. Then, by fully utilizing the state information of sampled intervals, a two‐sided looped functional with some matrices that are not required to be strictly positive is constructed to enhance the flexibility. In what follows, on the basis of stochastic analysis technique and looped functional, sufficient conditions with two scenarios are established in the form of linear matrix inequalities (LMIs) to guarantee the stochastic stability with an H∞$$ {H}_{\infty } $$ performance of the resultant semi‐Markov jump IMAPSs. Finally, the effectiveness of the proposed control synthesis methodology is validated through a numerical simulation. [ABSTRACT FROM AUTHOR]

For the nonlinear parameter‐varying (NPV) model of unmanned surface vehicle with the consideration of the velocities on yaw and surge as well as wave disturbances, a robust H∞$$ {H}_{\infty } $$ control method is proposed based on extended homogeneous polynomial Lyapunov function (EHPLF) to regulate heading for the superior performance on the rapidity, accuracy, and robustness. First, a NPV model of heading error is established to design a general form of a state feedback controller with a robust H∞$$ {H}_{\infty } $$ performance. Second, a Lyapunov matrix with full states and varying parameter is constructed to derive the robust H∞$$ {H}_{\infty } $$ global exponential stability conditions by Euler's homogeneity relation for the NPV system, known as the EHPLF stability conditions. Third, since the EHPLF stability conditions consist of a set of nonlinear coupled inequalities that cannot be directly solved by sum of squares (SOS) toolboxes, they are decoupled with matrix transformations to obtain the EHPLF‐SOS stability conditions, which is solved for the parameters of the state feedback controller. Finally, the simulation results indicate that EHPLF method exhibits a superior performance on dynamic, steady‐state, and robustness. [ABSTRACT FROM AUTHOR]

Summary: This work primarily concentrates on the design of fault‐tolerant anti‐disturbance control for synchronization of multiple memristor‐based neural networks subject to time delay, matched and mismatched disturbances. Moreover, in the addressed network model, we consider parameter uncertainties and actuator faults. Firstly in order to estimate the matched disturbances generated by the exogenous system, a disturbance observer is devised. Whereas, the mismatched part is tackled by employing the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Subsequently, a unified controller is designed by incorporating error feedback control and the disturbance estimate. Further, with the assistance of Lyapunov stability theory and linear matrix inequality technique, an adequate criteria is procured to ascertain the required synchronization criteria for the assayed network model with the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Following this, by basing on the established conditions, the explicit form of the controller and observer gain matrices is obtained. In the end, a numerical example with simulation results is shown to confirm the potential and usefulness of the conclusions acquired from the theoretical analysis. [ABSTRACT FROM AUTHOR]

This article addresses the issue of event‐triggered security control for nonlinear cyber‐physical systems, characterized by Denial‐of‐Service (DoS) attacks, time‐varying delays, and actuator faults. These complexities are captured using the Takagi–Sugeno fuzzy model. Significantly, this study focuses on DoS attacks targeting the controller‐to‐actuator channel, and subsequently introduces a model for actuator faults that considers the prolonged utilization or degradation of component parts. To optimize communication resource allocation, a model‐independent event‐triggered mechanism is proposed. Utilizing the Lyapunov–Krasovskii function approach, the objective of achieving stochastic stability is transformed into a linear matrix inequalities problem, thus deriving a set of sufficient conditions. The efficiency and validity of the proposed algorithms is demonstrated through simulation results. [ABSTRACT FROM AUTHOR]

Summary: This work proposes a new approach for designing dynamic pre‐compensators to reduce interactions of multivariable uncertain square systems. The proposed method is based on the minimization of the ℋ∞$$ {\mathscr{H}}_{\infty } $$ norm of the difference between the compensated system and a diagonal reference model. The main appeal of the technique is to propose a systematic procedure to obtain the reference model dynamics, in contrast to methods that use the identity matrix as a reference, and to obtain diagonal dominance in a frequency range of interest employing the generalized Kalman‐Yakubovich‐Popov (KYP) Lemma. The design conditions are expressed as linear matrix inequalities (LMI) thanks to a new general parametrization on the decision variables in bilinear products to reduce the conservatism of the solutions compared to standard approaches from the literature. Numerical examples verify the robustness of the proposed method, showing significant decoupling of the uncertain plant. [ABSTRACT FROM AUTHOR]

Summary: This paper focuses on the robustness analysis of discrete‐time, linear time‐varying (LTV) systems subject to various uncertainties, such as static and dynamic, time‐invariant and time‐varying, linear perturbations, and unknown initial conditions. The proposed approach is based on integral quadratic constraint theory and allows for a potentially more accurate characterization of the set in which the initial state resides by imposing separate constraints on the initial values of the state variables as opposed to simply requiring the initial state to lie in some ellipsoid. The adopted problem formulation facilitates the analysis of uncertain LTV systems subject to disturbance inputs that are bounded pointwise in time, and the developed results enable determining useful pointwise bounds on the performance outputs given such inputs. The main analysis result is given for eventually periodic nominal systems, which include linear time‐invariant, finite horizon, and periodic systems as special cases. The analysis conditions are expressed as linear matrix inequalities. Two additional results stemming from the main analysis theorem are provided that can be used to determine overapproximated ellipsoidal reachable sets. Finally, the utility of the proposed approach is demonstrated in an illustrative example. [ABSTRACT FROM AUTHOR]

This paper proposes a shifting feedback linearization controller for nonlinear systems under input saturation. The suggested approach for determining a linear parameter‐varying (LPV) state‐feedback controller is based on employing a linear matrix inequality (LMI)‐based methodology, the input‐output feedback linearization approach, and the shifting paradigm concept. The resultant controller deals with a full linearized version of the nonlinear system under state‐dependent input constraints, and it modifies the closed‐loop convergence speed of the system in accordance with changes in the system's region of linearity. The proposed approach is validated by means of an experimental example. [ABSTRACT FROM AUTHOR]

Achieving the robust fixed‐time stabilization (FxTS) of uncertain reaction‐diffusion systems (RDSs) utilizing intermittent boundary control is a valuable and unresolved problem. This paper simultaneously considers the influence of the uncertainty of non‐diffusion and diffusion coefficients on RDSs and provides an effective solution for the treatment of the uncertainty of diffusion coefficient in the investigation of FxTS. Then, a fixed‐time control scheme is presented to stabilize uncertain RDSs within a fixed time, which incorporates the merits of intermittent and boundary control and reduces control costs in both the spatial and temporal domains. Besides, some sufficient conditions in the form of linear matrix inequalities are deduced to guarantee the robust FxTS of uncertain RDSs with Neumann and mixed boundary conditions, respectively, which contain and generalize some existing results. Finally, the validity of the intermittent boundary control scheme and the FxTS criteria developed in this paper are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

This study focuses on the robust H∞$$ {H}_{\infty } $$ continuous‐discrete hybrid impulsive dynamic output feedback (DOF) control issue for time delays descriptor Markovian jump systems (TDDMJSs) with multidimensional impulsive operator. By applying an improved impulse‐time‐dependent Lyapunov–Krasovskii (L‐K) functional, the novel H∞$$ {H}_{\infty } $$ stochastic admissibilization conditions are formulated as linear matrix inequalities. A desired H∞$$ {H}_{\infty } $$ hybrid impulsive DOF controller is achieved, which includes a continuous DOF controller and a discrete impulsive DOF controller. The H∞$$ {H}_{\infty } $$ stochastic admissibilization of the closed‐loop TDDMJSs can be satisfied by virtue of the desired hybrid impulsive DOF controller. In the end, the validity of the proposed H∞$$ {H}_{\infty } $$ hybrid impulsive DOF controller design method is demonstrated by two examples, including an oil catalytic cracking process. [ABSTRACT FROM AUTHOR]

An observer‐based event‐triggered non‐fragile control problem for regulating the levels of oxygen and carbon dioxide (O2$$ {}_2 $$ and CO2$$ {}_2 $$) in patients blood during the extra‐corporeal blood circulation (ECC) process with random communication packet losses is explored in this work. The main intention of this work is to design an observer‐based event‐triggered and non‐fragile controller for ensuring the finite‐time boundedness criterion for the resulting system with mixed H∞$$ {H}_{\infty } $$ and passivity performance index over a finite interval of time. In addition to the limited bandwidth of the channels, such random packet losses might occur simultaneously between the sensors and the controllers, and between the controllers and the actuators. Unlike most studies in the literature, we have found that, since the controller‐actuator link has packet dropouts, the observer's control input differs from that of the plant. The sufficient conditions derived are presented in a linear matrix inequalities frame work. Finally, simulation results are used to validate the efficacy of the proposed control method. The results show that the proposed observer‐based event‐triggered non‐fragile controller keeps the blood gases within physiological limits during a stable ECC process. [ABSTRACT FROM AUTHOR]

Summary: Under the aperiodic Denial‐of‐service (DoS) attacks, this paper studies the resilient adaptive event‐triggered synchronization control problem for a class of Piecewise‐Homogeneous Uncertain Markov Jump Neural Networks (PHUMJNNs) with time‐varying delays. First of all, a new way of carving DoS attacks is given from the defenders' perspective, that is, aperiodic DoS attacks based on fixed detection periods. Then, under such attacks, a new Resilient Adaptive Event‐triggered Communication (RAETC) is designed between sensor and controller, which has a threshold function based on the net change rate and is real‐time updated depending on the present sampling state. Next, a single functional is used in the construction of the Lyapunov‐Krasovskii functional, while a new looped functional is introduced that makes full use of the state information of the current instant t$$ t $$, the trigger instant tkh$$ {t}_kh $$ and the next trigger instant tk+1h$$ {t}_{k+1}h $$. Based on the constructed single functional, under the framework of the input delay method and the linear matrix inequality technique, the exponential mean square stabilization criterion of the error system is obtained, which makes the master system and the slave system synchronized. In the end, three simulation examples are used to illustrate the validity of the obtained results. [ABSTRACT FROM AUTHOR]