This work explores the core challenge of adaptive event-triggered sliding mode control (SMC) for networked discrete singular systems (NDSSs) in the presence of false data injection (FDI) attacks. This innovative adaptive event-triggered design draws inspiration from the median filtering technique to use the average values of current sampled output signal and the latest transmitted trigger signal as the trigger condition. By focusing on the instantaneous characteristics, the accuracy of the trigger judgment of the proposed adaptive event-triggered mechanism (AETM) is improved. Taking into account the false data injection attacks, a collaborative control method integrating the AETM and the observer-based sliding mode control is specifically formulated to utilize the robustness of sliding mode control to enhance the security and reliability of the NDSSs. By applying the singular value decomposition technique, fresh criteria for the NDSS to be regular, causal, and bounded are obtained based on linear matrix inequalities (LMIs). Furthermore, the finite-time convergence of the system trajectories to a region in the vicinity of the equilibrium point is guaranteed by the proposed SMC law. Ultimately, a direct current (DC) motor model and a tunnel diode circuit system simulations verify the effectiveness and practicality of the proposed method.

This paper investigates neural network-based dynamic adaptive event-triggered security compensation feedback control for implicit power systems (IPSs) subjected to false data injection (FDI) attacks. By introducing a time-varying positive exponential term, a new dynamic adaptive event-triggered mechanism (DAETM), which can avert Zeno phenomenon and address the issue that the controller fails to cancel the internal impulses of singular systems when using period-sampling based event-triggered mechanisms, is proposed to achieve the goal of enhancing communication efficiency while relieving channel load. Via adopting radial basis function (RBF) neural network (NN) approximation method to estimate the unknown FDI attack signals, the event-based security compensation feedback (SCF) controller with adaptive corrective term is designed, which can compensate the FDI attack signals and minimize the effect of FDI attacks. Considering the designed DAETM as well as the adopted RBF NN approximation method, a novel Lyapunov-Krasovskii (L-K) functional is constructed, which captures the dynamic adaptive event-triggered information and facilitates to obtain the ideal adaptive law of NN weight matrix, thereby contributing to the realization of regularity, impulse-freeness and ultimate boundedness of IPSs and promoting the collaborative design of DAETM and SCF controller. The final simulation results for IPSs validate the effectiveness of the studied methodology.

This paper is concerned with the co-design problem of the adaptive neural sliding mode compensation controller and multidomain DoS-attack-aware scheduling protocol (MDSP) for the direct current microgrids (DC-MGs). It is considered that the process of transmitting the system data over wireless networks is vulnerable to intrusion by cyber-attacks, in which the aggressors might send denial-of-service (DoS) attacks to the output data and inject fake messages into the control signal. Due to the fact that not all data in DC-MGs can be acquired from direct measurements, an attack-parameter-dependent observer is introduced to estimate the unknown states under DoS attacks. Then, with the objective of enhancing the system responsiveness and bandwidth utilization, a novel MDSP is presented by introducing a multidomain structure, which enables to maintain the communication function of DC-MGs when some channels fail or are blocked. In the meantime, the neural network technique is employed to approximate unknown attack information based on the observer states, thus recovering normal data attacked by potential false data injection (FDI) attacks. Additionally, by introducing the partitioning strategy, the corresponding resilient finite-time boundedness for both the reaching phase and sliding motion phase is acquired, respectively. An adaptive sliding mode compensation controller is devised by introducing the additional compensation terms, which can improve the control accuracy and the adaptability to cyber-attacks, thus ensuring that the states of DC-MGs are rapidly entered and maintained on the sliding surface during a finite-time interval. Finally, the availability and validity of the presented approach is verified through a DC-MG with three constant power loads.

This article investigates the finite-time switching control issue based on switched observer for networked discrete implicit systems under dynamic event-triggered protocol (DETP) and denial-of-service (DoS) attacks. First, regarding the intermittent characteristic of DoS attacks, a switched observer adapted to such attacks is devised to tackle the unavailability of state information. In addition, to enhance the efficiency of network resource utilization, an improved DETP is introduced, which not only relies on the latest transmission data and the current sampling data, but also combines the changes in their average values to dynamically adjust the triggering threshold. Next, by adopting the singular value decomposition approach, the iterative technique and by constructing the Lyapunov-Krasovskii (L-K) functional correlated with the DoS attack signals, the criteria of singular finite-time boundedness for the networked controlled implicit systems are acquired. The proposed cooperative scheme for DETP and observer-based switching controller promotes both communication efficiency and the resilience of the implicit systems to DoS attacks. Finally, the validity of the mentioned collaborative design switching control method is confirmed by taking direct current motor model and tunnel diode circuit as simulation examples.

This research is concerned with$H_{\infty } $security feedback control for networked singular Markovian jump systems (NSMJSs) with actuator faults and denial of service (DoS) attacks under mode-dependent switching-like adaptive event-triggered scheme. To handle energy-limited denial of service attacks and further strengthen communication efficiency, a mode-dependent switching-like adaptive event-triggered scheme (MSAETS) adopting state-dependent adaptive threshold function is introduced. By exploiting singular value decomposition (SVD) technique and establishing a mode-related discontinuous Lyapunov-Krasovskii (L-K) functional, novel$H_{\infty } $stochastic admissibility criteria for NSMJSs with DoS attacks and actuator faults are acquired, and the relationship between event-triggered parameters and DoS attacks energy is developed through the clever use of matrices/vectors norms and iterative method. Collaborative design method of event-triggered scheme and security feedback controller is proposed, which can make sure the$H_{\infty } $stochastic admissibility of NSMJSs while alleviating the communication burden and improving communication efficiency. The validity of the suggested cooperative control strategy is demonstrated via using an oil catalytic cracking process. Note to Practitioners—In actual engineering, numerous dynamic systems are usually modeled as singular systems, such as oil catalytic cracking processes, power systems, etc. Noteworthy, the investigation of singular systems is considerably complicated and more challenging than normal ones since numerous factors have to be contemplated in parallel, including stability, regularity, non-impulsiveness or causality. Most existing control results are poorly suited to these types of practical systems. Meanwhile, practical systems inevitably endure sudden changes in system structure or/and parameters, actuators may fail completely or partially during operation, and open communication environment and limited bandwidth of communication networks pose a range of challenges including packet losses, network-induced transmission delays and malicious network attacks, all of which may lead to reducing system performance, compromising system stability and eventually result in catastrophic accidents. To address the above challenges, in this work, the mode-dependent switching-like adaptive event-triggered$H_{\infty } $security feedback control scheme is designed for NSMJSs with DoS attacks and actuator faults.

This paper mainly focuses on fixed time control for interlayer synchronism problem under voltage-flux–time (VFT) delay deplux memristive neural networks (DDMNNs). Distinct from most previously reported achievements, continuous memristive VFT neural networks (MMNs) field with$2^{2{n^{2}} + n}$variables are considered, where the memristor is considered as a continuous time-varying uncertain parameter, and n is the number of states in DDMNNs. This memristor is a type of continuous system built on the HP memristor. To synchronize VFT DDMNNs, a fixed time control policy is proposed for interlayer synchronism of flux and voltage values under the VFT DDMNNs. According to the second method of Lyapunov, selecting appropriate Lyapunov functionals and using inequality techniques, the structure and parameters of a kind of fixed time controller are designed, and interlayer synchronism criteria for DDMNNs are obtained. Finally, a secure communication scheme based on interlayer synchronism is designed. It is found that the fixed settling time is relative to the constructive of DDMNNs and the parameters of the fixed time controller. Note to Practitioners—This work solves the fixed time interlayer synchronism control problem of VFT DDMNNs, which can be applied to some practical scenarios, such as information security communication and image encryption. When transmitting signals in computer networks, for security, encryption mechanisms are usually added to network communication protocols to achieve secure communication. In some encryption applications, there are special requirements for speed of encryption and decryption, which requires reducing encryption and decryption time and improving efficiency of encryption. This work provides a fixed time control strategy which can achieve synchrony for VFT DDMNNs under controllable time, thereby achieving encryption under controllable time. Meanwhile, improve encryption efficiency in secure communication.

This paper mainly concentrates on the issue of fixed-time cluster secure synchronization upon interlayer switching networks with DoS attacks, in which the DoS attacks may cause random damage to the nodes/edges in networks and then generate impulsive disturbances. To resist the attacks, one robust fixed-time discontinuous control strategy is proposed, such that all the nodes in interlayer switching networks can achieve the cluster secure synchronization even when the communication topology are disconnected or changed over time after being influenced by attacks. By using the Lyapunov method, several effective conditions for fixed-time cluster secure synchronization and the maximum convergence time near to the actual value are obtained. In view of the comparison principle, a suitable estimation method upon stability time for the switching networks is established, and the stability time is computable and controllable. Moreover, the correlation among attack intensity, connectivity network, impulsive interval, impulsive disturbance intensity and synchronization time is revealed. Simulation case is finally supplied to manifest the availability of the obtained outcomes.

This article investigates estimator-based attack-tolerant compensation control for discrete singular systems (DSSs) under false data injection (FDI) attacks and a hybrid internal dynamic variables (IDVs)-dependent event-triggered mechanism. With the aim of managing the transmission of measurement outputs in a more flexible manner to save the limited network bandwidth, a novel hybrid IDVs-dependent dynamic event-triggered mechanism is introduced in this paper. The triggering mechanism is characterized by having not only an additive IDV but also a multiplicative IDV related to the measurement output errors. In order to mitigate the adverse effects of FDI attacks on DSSs, an attack estimator and an attack-tolerant compensation controller are collaboratively designed, where the attack estimator can simultaneously estimate the system states and the cyber-attack signals. Using the singular value decomposition technique, regularity and causality of DSSs are proved, the ideal estimator gains and the attack-tolerant compensation controller gain are obtained simultaneously based on linear matrix inequalities, and new conditions for singularH∞ finite-time boundedness of DSSs are given. Lastly, a direct current motor-controlled inverted pendulum demonstrates the practicability and effectiveness of the estimator-based attack-tolerant compensation control method.

The problem of normalized proportional-derivative (P-D) and intermittent hybrid$H_{\infty}$control for delayed descriptor impulsive systems (DDISs) is studied in this work. The P-D and intermittent hybrid state feedback controller is designed, such that normalisation and$H_{\infty}$stabilisation of DDISs can be realised. A novel impulsive-inputs-dependent Lyapunov-Krasovskii functional based on a couple of auxiliary functions is constructed, which is continuous along the system state trajectories without imposing additional conditions on impulsive dynamics. Improved$H_{\infty}$stability criterion is proposed in the form of linear matrix inequalities by utilizing free weighting matrix technique, and the$H_{\infty}$stability criterion is described as a single condition based on a combination of discrete and continuous dynamics. Finally, the usefulness of the method set forth in this work is demonstrated by a two-loop circuit network.Note to Practitioners—This work is motivated by realizing normalized P-D and intermittent hybrid$H_{\infty}$control for delayed descriptor impulsive systems. In practical engineering, many dynamic systems have to be formulated as descriptor systems when modeling, such as circuit systems, vehicle suspension systems, and so on. It is worth pointing out that infinite dynamic modes will occur due to the algebraic constraints in descriptor systems, and can lead to internal impulsive behavior. At the same time, these systems are often accompanied by external impulsive perturbations, such as the sudden failure of a component in circuit systems, etc. The internal and external impulses can cause serious damage to the system performances and stability. Most of the existing control schemes are not well suited for such practical systems. In addition, due to the presence of time-varying delays, the delayed dynamic systems can easily collapse and cause significant damages. In this work, the P-D and intermittent hybrid$H_{\infty}$controller is designed so as to deal with the above challenges.

This article considers the problem of event-based$H_{\infty }$fuzzy control for implicit hybrid active vehicle suspension systems (IHAVSSs) embedding acceleration and Markovian jumping characteristics under random deception and denial-of-service (DoS) attacks. Aiming at conserving of communication resources, an event-triggered strategy is introduced in the communication link between sensor and controller. The accelerations of sprung, unsprung and tyre are taken into account, the active vehicle suspension systems are constructed as the implicit one. Admissibility conditions are derived under the framework of linear matrix inequalities by utilizing the piecewise Lyapunov-Krasovskii (L-K) functional. Via singular value decomposition (SVD) technique, the IHAVSSs are proved to be regular and impulse-free. By means of Takagi-Sugeno (T-S) fuzzy method and parallel-distributed compensation (PDC) technique, a mode-dependent (M-D) fuzzy feedback controller (FFC) is designed to ensure$H_{\infty }$stochastic admissibilization of IHAVSSs under random deception and DoS attacks. The validity of the results is demonstrated by using the quarter active vehicle suspension model produced by Quanser company. Note to Practitioners—The active vehicle suspension systems hold paramount significance in practical applications, effectively dampening vibrations from road surfaces and enhancing ride comfort. Concurrently, as networking advances, interconnectedness among various components within the active vehicle suspension system grows. However, the communication links are vulnerable to malicious attacks that may decrease the performance of the AVSSs, which inspires our current research. This paper delves into the$H_{\infty }$stochastic admissibilization of the AVSSs subjected to network malicious attacks, and makes full use of the dynamic variable of the system in the modeling process, that is, the accelerations of each components are selected as the system state variable. The method is applied to a platform simulation, and the stochastic admissibility of implicit hybrid active vehicle suspension systems under random deception and DoS attacks is realized.

This article focuses on the development of an observer-based finite-time Takagi–Sugeno (T–S) fuzzy sliding mode control strategy for unmanned marine vehicles (UMVs) under hybrid cyberattack scenarios. To relieve the communication burden for the industrial control network, a new dynamic memory-based event-triggered protocol (ETP) is properly put forward, which concerns the historically released data and two auxiliary dynamic variables. Due to the influence of aperiodic spoofing attacks and denial of service (DoS) attacks, the T–S fuzzy model of UMVs is transformed into a framework of stochastic switched T–S fuzzy systems. In the light of the T–S fuzzy observer, a memory-based T–S fuzzy sliding mode controller is constructed concerning the DoS attacks and spoofing attacks. Criteria of finite-time stable for the closed-loop stochastic switched T–S fuzzy systems are attained for the reaching stage and sliding mode stage. By means of the orthogonal decomposition method, a cooptimization method for the observer, controller, and weight matrix within the dynamic memory-based ETP framework is obtained. Eventually, a benchmark UMV is employed to validate the efficacy of the developed methodology.

This article investigates the issue of distributed dual-terminal adaptive event-triggered admissible consensus tracking for linear leader-following descriptor multi-agent systems (DMASs) against asynchronous denial-of-service (DoS) attacks. Due to the various off/on moments and durations of consecutive asynchronous DoS attacks on different edges, the communication topologies of DMASs are considered to be randomly switched according to different types of DoS attacks, and the switched topologies are governed by Markov chains. To mitigate dispensable information transmission, a novel dual-terminal adaptive event-triggered protocol is put forward, which excludes the Zeno behavior in addition to flexibly adjusting the inter-event interval. Then, a local estimator based on state reconstruction is designed in a triggered way to exactly estimate agents’ states between two successive triggered moments. Additionally, by constructing a modified mode-dependent Lyapunov-Krasovskii functional and employing singular value decomposition technique, the frequencies and durations of DoS attacks are analyzed and the admissible consensus tracking conditions are acquired for DMASs when frequencies and durations of DoS attacks satisfy bounded conditions. Lastly, multiple transistor electrical circuit systems are employed to demonstrate the validity of the proposed strategy.

This paper investigates fault detection and robust security control of implicit Markovian jump (IMJ) systems affected by random false data injection (FDI) attacks and packet loss under memorized output-perceptive event-triggered protocol (MOETP). In order to harmonize control performance and communication efficiency, a mode-dependent MOETP is proposed by designing an output-dependent threshold function and introducing weight parameters. Fault detector and feedback controller incorporating random FDI attacks and packet loss information are cooperatively designed to detect the occurrence of system faults and achieve robust security control for IMJ systems. Considering the property that the derivative of “time-varying delay” function is 1 and the definition of error in MOETP, a novel mode-delay-related Lyapunov-Krasovskii functional is constructed so as to derive the strict linear matrix inequality criteria of$H_{\infty }$stochastic admissibility as well as the expected gains of fault detector and security controller based on free-weight matrix method and matrix transformation technique. The validity of the presented co-design methodology is confirmed by a tunnel diode circuit system.

This article lays the spotlight on embedded-adaptive-observer-based$H_\infty$integrated fault estimation and memory fault-tolerant control for a nonlinear delayed implicit robotic arm. To tackle the nonlinearity of the system, a prototypical Takagi–Sugeno fuzzy method is deployed. An embedded adaptive proportional–integral observer program is proposed to implement$H_\infty$simultaneous estimation of the original system states, sensor faults, and actuator faults via the fault-embedded technique, embedding the sensor faults into the original system states and allowing them to be transformed into new substates. The development of a fresh fuzzy Lyapunov–Krasovskii functional with time delays, Markov jump modes, and fuzzy information creates a firm groundwork for the outcome of the fuzzy delayed implicit jump system meeting with stochastic admissibility and$H_\infty$performance metrics. Novel observer-based memory-aware fault-tolerant controller is engineered by taking the form of linear matrix inequalities to compensate the impact of time delays, perturbations, and faults. To illustrate the validity of the method put forward, a single-link robotic arm device is offered as an example finally.

This work addresses the issue of$H_{\infty }$adaptive sliding-mode control (SMC) for nonlinear delayed singular systems (NDSSs) under impulsive attacks (IAs). The NDSSs subjected to IAs are modeled as fuzzy delayed singular impulsive systems (FDSISs), and a neoteric fuzzy integral sliding surface function is constructed based on the piecewise auxiliary functions method, which is continuous on$(0,+\infty)$without any other additional conditions. Then, a suitable SMC law and an adaptive SMC law are designed, such that the state trajectories of FDSIS can be driven to the predetermined sliding surface in finite time. In addition, an improved impulse-time-dependent Lyapunov-Krasovskii functional containing characteristics of IAs and time delays is designed, and it is demonstrated to be continuous along the FDSIS trajectories. Improved conditions are put forward in the form of strict linear matrix inequalities via congruent transformation technology, which can guarantee that the singular sliding-mode dynamics under IAs fulfills$H_{\infty }$stochastic admissibilization. Finally, the practicability of the approach presented is attested and the effects of IAs on convergence time are testified by the networked truck-trailer system.

In this article, we endeavor to address the problem of asynchronous attack detection for a class of nonlinear cyber-physical system (CPS) under the dynamic-memory event-triggered transmission protocol (DMETP). Malicious attacks under consideration are composed of the parameter-dependent false data-injection (FDI) attacks and the multichannel deception attacks with the time delay. Meanwhile, we attempt to employ the T-S fuzzy singular Semi-Markov jump linear parameter-varying (SS-MJLPV) systems to describe the stochastic jump characteristics and nonlinear time-varying characteristics of CPSs. Then, the DMETP is proposed for the first time, which can not only relieve the bandwidth pressure but also obtain the key released packets at the crest or trough of the curve. By augmenting the states of the original system and the asynchronous attacks detection filter, the issue of attacks detection is converted into an auxiliary dissipative filtering for the CPS. Moreover, sufficient conditions for the existence of the attacks detection filter are obtained. Finally, the effectiveness of the proposed scheme is verified via the networked truck-trailer reversing system.

This article researches$H_{\infty }$asynchronous admissibilization for nonlinear singular delayed hybrid hydraulic turbine governing systems with impulsive perturbations. By exploiting Takagi–Sugeno fuzzy technique, the fuzzy singular delayed hybrid hydraulic turbine governing system with impulsive perturbations is built, which cannot only accurately and concisely describe the dynamic behaviors of the pipeline, but also resist damages for the hydraulic turbine system caused by sudden reasons. Then, the asynchronous fuzzy state-feedback controller (FSFC) is designed by using parallel distributed compensation technique, and the asynchronous mechanism between the modes of FSFC and the modes of controlled plant is depicted by a hidden Markovian model. By constructing an improved timer-dependent Lyapunov–Krasovskii functional, the new criteria about$H_{\infty }$admissibilization for fuzzy singular delayed hybrid hydraulic turbine governing systems with impulsive perturbations can be acquired. The gains of asynchronous FSFC are expressed by solving linear matrix inequalities. Impulsive operators are successfully generalized and extended from$\mathbb{R}$to$\mathbb{R}^{n\times n}$, which makes the approach presented in this article more universal. Finally, the simulation results prove the correctness and availability of the method provided in this article.

This article is dedicated to design asynchronous aperiodic sampled-data controller for a class of Markov jump systems with switching transition rate. The sampling controller corresponding switching transition rate matrix mode is not synchronized with the system corresponding switching transition rate matrix mode due to the possible switching of the transfer rate matrix in the sampling interval. With the help of T–S fuzzy models, the state-space representation of the system is turned into a fuzzy Itô stochastic switched Markov jump systems. By constructing novel Lyapunov functionals, mean square exponential stability criteria, and dissipativity criteria are presented. Furthermore, an asynchronous aperiodic sampled-data controller is designed for fuzzy Itô stochastic Markov jump systems. At last, by fuzzing the nonlinear tunnel diode circuit model and nonlinear mass-spring-damper mechanical model, the effectiveness and lower conservativeness of the proposed method are illustrated.

In this article, an aperiodic sampled-data control problem is investigated for polytopic uncertain switched complex dynamical networks subject to actuator saturation. Due to the constraint on the upper bound of the sampling interval being no greater than the dwell time, the issue concerning the asynchronization between the sampled-data controller mode and the system mode is hence considered to be caused by subsystems that may switch in a sampling interval. By considering the sampling interval without switching and the sampling interval with switching, the parameters-dependent loop-based Lyapunov functionals are constructed, respectively. With the help of the constructed functional, mean-square exponential stability criteria for the error polytopic uncertain switched complex dynamical networks are presented under the definition of average dwell time. Furthermore, based on the stability criteria, the asynchronous aperiodic sampled-data controller is designed for polytopic uncertain switched complex dynamical networks subject to actuator saturation. The polytopic uncertain switched complex dynamical networks can be guaranteed to exponentially synchronize with the target node based on the proposed stability conditions and aperiodic sampled-data controller design method. Finally, by transforming the proposed theoretical conditions into the LMI-based objective optimization problem, the domain of attraction of polytopic uncertain switched complex dynamical networks is estimated. An example based on switched Chua's circuit is applied to verify the effectiveness of the proposed method.

In this article, sampled-data synchronization problem for stochastic Markovian jump neural networks (SMJNNs) with time-varying delay under aperiodic sampled-data control is considered. By constructing mode-dependent one-sided loop-based Lyapunov functional and mode-dependent two-sided loop-based Lyapunov functional and using the Itô formula, two different stochastic stability criteria are proposed for error SMJNNs with aperiodic sampled data. The slave system can be guaranteed to synchronize with the master system based on the proposed stochastic stability conditions. Furthermore, two corresponding mode-dependent aperiodic sampled-data controllers design methods are presented for error SMJNNs based on these two different stochastic stability criteria, respectively. Finally, two numerical simulation examples are provided to illustrate that the design method of aperiodic sampled-data controller given in this article can effectively stabilize unstable SMJNNs. It is also shown that the mode-dependent two-sided looped-functional method gives less conservative results than the mode-dependent one-sided looped-functional method.

This article reports our study on asynchronous H∞filtering for fuzzy singular Markovian switching systems with retarded time-varying delays via the Takagi-Sugeno fuzzy control technique. The devised parallel distributed compensation fuzzy filter modes are described by a hidden Markovian model, which runs asynchronously with that of the original fuzzy singular Markovian switching delayed system. The fuzzy asynchronous filtering dealt with in this article contains synchronous and mode-independent filtering as special cases. Novel admissibility and filtering conditions are derived in terms of linear matrix inequalities so as to ensure the stochastic admissibility and the H∞performance level. Simulation examples including a singlelink robot arm are employed to demonstrate the correctness and effectiveness of the proposed fuzzy asynchronous filtering technique.

In this article, the dissipativity-based sampled-data control problem is studied for the fuzzy switched Markovian jump systems (FSMJSs). By considering the problem of the asynchronous switching caused by the subsystems' switching occurred during the sampling intervals, constructing novel time-dependent Lyapunov functional, and using average dwell time (ADT) approach, sufficient mean-square exponential stability criteria, and strictly (Q,S,R)-γ- dissipativity criteria are proposed under the constraints that the maximum sampling period is no larger than the dwell-time between the transition rates switching instants. Meanwhile, a relationship between ADT and sampling period is revealed for FSMJSs. Based on the strictly (Q,S,R)-γ- dissipativity criteria, the sampled-data controller is designed for FSMJSs. A circuit simulation example is provided to illustrate the effectiveness of the proposed method.

This article is concerned with the issue of asynchronous feedback control for fuzzy degenerate jump systems with mode-dependent time-varying delays via Takagi–Sugeno fuzzy control technique under observer-based event-driven characteristic. The improved observer and event trigger transmit not only state estimate signals but also the information of Markovian jump modes to the controller under the networked nonperiodic sampling scheme. Applying parallel distributed compensation technique, the asynchronous fuzzy feedback controller is devised, and the asynchronous fuzzy controller modes are depicted by a hidden Markovian model, where the modes of fuzzy controller run asynchronously with that of the original degenerate fuzzy jump systems. Exponentially decreasing function is employed to devise the triggering threshold, which can ensure not only the admissibility of the delayed fuzzy degenerate jump systems but also the effectiveness of event-driven strategy. Original stochastic admissibility and asynchronous feedback control conditions are characterized by linear matrix inequalities. A numerical example and a single-link robot arm model are applied to illustrate the correctness and validity of the proposed observer-based event-driven asynchronous fuzzy feedback control technique.

The issue of adaptive fuzzy prescribed performance tracking control is considered in this article for strict-feedback stochastic uncertain nonlinear systems. A novel adaptive tracking control design approach, in which the fuzzy systems are employed to approximate the totally unknown nonlinear terms, is proposed by incorporating the technology of prescribed performance control with the method of command filtered backstepping design. The proposed adaptive state feedback controller can ensure that the output tracking error converges to a predefined arbitrarily small residual set in probability and all the signals of the closed-loop system can be bounded in probability, meanwhile, the problem of “explosion of complexity” is solved. The effectiveness of the presented method is verified by two simulation examples.

To deal with a class of nonlinear systems with unknown control directions, a command filter-based adaptive tracking controller is designed in this paper. In the design process, fuzzy logic system is required to handle nonlinear functions, command filter is employed to settle the explosion of complexity problem and Nussbaum function is introduced to compensate the influence of unknown directions problem. Finally, the proposed control approach guarantees that error signals converge into bounded compact sets around the origin and all closed-loop signals are bounded. The effectiveness of the presented scheme is illustrated by a simulation example.

This article considers admissibility analysis and stabilization for implicit Markovian jump systems (IMJSs) with retarded discrete-distributed delays. Admissibility analysis is investigated for the unforced delay IMJSs by virtue of reciprocally convex integral inequality technique and Barbalat’s lemma. State feedback controller is designed via the matrix transformation technique to realize the stabilization of the delayed closed-loop IMJSs. By selecting comprehensive L-K functional with modes and delays information, admissibilization conditions are presented in terms of LMIs. Two illustrative examples including an inverted pendulum controlled by a direct current motor (DCMCIP) system are utilized to certify the effectiveness and practicality of the admissibilization technique.