In data-driven mechanical fault diagnosis, domain adaptation is used to solve the problem of different distribution of collected data under varying operating conditions. However, the assumption of consistent label space between source and target domains is difficult to satisfy due to the types of faults that occur under different operating conditions not being completely identical. To address the problem of label inconsistency in partial domain adaptation, we propose a feature separation weight rectified network (FS-WRN). Shared domain features are extracted by feature separation, and the source and target domain distributions are aligned using the rectified local maximum mean discrepancy. The source-domain features are weight-rectified by capturing changes in the target domain distribution during training to minimize the effect of negative transfer due to private classes. Three public datasets are used, and the results show that FS-WRN has promising fault diagnosis performance under complex partial domain adaptation tasks.

It is well known that most position synchronization control schemes merely relay on position error dynamics, which are hard to fully explore the potential capability of synchronized plants. Therefore, this paper studies the synchronization motion control using both the position and velocity states for the dual-cylinder hydraulic system. This indicates that more states are involved in the synchronization regulation, which thus provides the ability of enhancing synchronous performance. Meanwhile, a novel fast finite-time observation approach is proposed and designed for each actuator to compensate the uncertainties of forces and flow rates, and eliminate the load variation caused by different loads and disturbances of two actuators. The proposed observer converges faster than traditional ones with exponential or asymptotic rates benefiting from the homogeneity technique. It is also proved that the proposed control scheme can ensure both synchronizing and tracking errors to exponentially converge to an adjustable compact set or zero when the system is only subject to constant disturbances. Finally, experiments on the aero-engine Hardware-in-the-loop (HIL) platform with hydraulic actuators are conducted to verify the effectiveness and practicability of the proposed synchronization control scheme.

This article investigates the event-triggered adaptive robust motion control for hydraulic actuators with parametric uncertainties and system nonlinearities. Under the continuous communication condition, the traditional adaptive robust motion controller is recursively presented. In order to reduce the unnecessary bandwidth consumption in the aero-engine networked control platform, an adaptive threshold triggered mechanism according to network resources is developed to synthesize the motion controller. Adjustable threshold parameters are involved to flexibly adjust the data transmission times depending on the network bandwidth occupation. It is proved that with the motion controller and the proposed adjustable threshold triggered mechanism, all the closed-loop system signals are globally bounded, and the hydraulic system output achieves asymptotic tracking to the reference trajectory by virtue of the adaptive technique, the Nussbaum-type and sign functions. Besides, the Zeno behavior is excluded, successfully. Finally, the proposed event-based control scheme is tested and discussed on the aero-engine hardware-in-the-loop (HIL) experiment platform with hydraulic actuators.

Generally, asymptotic tracking motion control algorithm can ensure the stability of the closed-loop system, but hardly exploits the potential system performance. As an alternative, a high-accuracy control method with finite-time regulation is studied in this paper for hydraulic actuators pertaining to complex unknowns and limited communication bandwidth. During system modeling, a hydraulic actuator system is expressed in the Brunovsky form with a lumped disturbance term, instead of the conventional semi-strict-feedback form, such that the tracking control can be transformed to the stabilizing problem. As a result, the homogeneity-based finite-time motion controller enables to be recursively constructed. This paper develops a finite-time observer to simultaneously estimate the partial unknown state and the lumped disturbance, with a short time, thereby improving the disturbance rejection and transient response. Moreover, a novel threshold triggering mechanism is proposed to alleviate the limited communication resources and ensure the relatively small amplitude fluctuation of control inputs via a minimum function. The stability and finite-time convergence of the closed-loop system are all proved. Meanwhile, the Zeno behavior is avoided. Finally, the proposed control scheme is tested and verified on the aero-engine Hardware-in-the-loop (HIL) test-rig with hydraulic actuators.Note to Practitioners—This paper displays how to utilize the event-triggered communication protocol and finite-time control for hydraulic actuators in the networked control systems. The designed event-triggered mechanism saves more communication resources while ensuring the satisfied motion control effect. Moreover, the internal and external uncertainties are all tackled with the developed finite-time observer. Experimental results verify that the proposed schemes are easily implemented, but with the plentiful performance improvements of motion control, disturbance attenuation (i.e., finite-time output tracking and unknown estimation), and the capability on saving network resources. In addition, the proposed event-driven control scheme is also feasible for other mechatronic systems, e.g., linear motor, DC motor and marine surface vehicles.

In this article, a set-membership estimation observer is designed for Takagi–Sugeno (T-S) fuzzy 2-D systems on Roesser model. The T-S fuzzy 2-D systems have unmeasurable premise variables, which cause prescribed influence to estimation. First, the observer and error systems are built and analyzed based on parallel distributed compensation. Then, the observer gain matrices are computed by solving an optimal problem to ensure the radius of error zonotopes converge to zero, so that estimation errors are asymptotically stable. In addition, we prove that the radius of error zonotope satisfies$L_\infty$performance. To demonstrate the effectiveness of proposed method, a T-S fuzzy 2-D system transformed from a nonlinear Darboux equation is studied and the simulation results are presented to show the advantage of proposed approach.

In this paper, a class of finite-time state zonotopes are proposed for the interval estimation of switched systems with asynchronous switching. First, considering the mismatch between the system mode and the observer mode, an augmented switching signal is adopted to deal with the asynchronism uniformly. Then, the state zonotopes are constructed in the synchronous and asynchronous intervals, respectively, to enclose the actual system state. Specific iteration procedures are provided for the generator matrix. Moreover, a new criterion is newly proposed to address that the estimation error is finite-time bounded with a pre-specified upper bound under the hybrid mode-dependent switching. Solvable conditions are presented to optimize the observer gain and ensure a finite-time$\mathcal {L}_{2}$gain in attenuating the unknown-but-bounded perturbation. Finally, the effectiveness of the proposed method is validated through the application to a switched converter.

Adaptive robust control technique is investigated to devise trajectory tracking event-triggered controller for a class of uncertain nonlinear systems. Different from most existing results, this article divides the entire control input into two parts, including the model compensation input term and the robust term, which are separately dealt with by means of special triggered mechanisms. The advantage of separation is that the system reduces the magnitude of chattering amplitude within triggered inputs. To balance the information updating frequency and the magnitude of chattering amplitude, this article proposes the dynamic-threshold-triggered mechanism and provides a new Lyapunov function to guarantee the global boundedness of all the closed-loop signals as well as the convergence of the tracking error to an arbitrary small set around zero. This article also considers desired compensation adaptive robust event-triggered control strategy, thereby further saving bandwidth resources and smoothing the triggered inputs. The Zeno behavior is excluded for two triggering schemes. Finally, simulation and hardware-in-the-loop experiments are used to verify the effectiveness of the proposed strategies.

This article investigates the problem of quantized sampled-data control for continuous-time switched Takagi–Sugeno (T–S) fuzzy systems with the asynchronous phenomenon. First, considering that the system and controller modes could not be perfectly synchronized all the time, we study possible cases of mode mismatching by exploiting the average dwell time (ADT) switching strategy. Since the fact that a minimum dwell time of each subsystem is not required in the ADT switching rule, multiple system switching is allowed within one sampling interval, which overcomes the limitation of at most once switching during any sampling interval in existing works. Second, the asynchronous premise variables between the fuzzy system and fuzzy controller are taken into consideration in the quantized sampled-data control scheme. Then, by virtue of the Lyapunov function approach, we obtain sufficient conditions to guarantee that the asynchronously switched T–S fuzzy system is exponentially stable with quantized sampled-data input. Furthermore, the weighted$L_{2}$-gain is discussed for the system under external disturbance, and an$H_{\infty }$state feedback controller is correspondingly designed with prescribed disturbance attenuation. Finally, the validity and advantage of the proposed methods are illustrated by two examples.

This article studies the problem of event-triggered fault detection (FD) for 2-D systems subjected to amplitude-bounded exogenous disturbance and measurement noise via a zonotopic residual evaluation mechanism. An event-triggered mechanism is introduced into the FD framework to save limited communication resources. A finite-frequency (FF) mixed$\ell _{\infty }/h_{\infty }$index is derived to ensure the residual signal is sensitive to a fault signal while robust to disturbance and noise, based on which an optimal mixed$\ell _{\infty }/h_{\infty }$FD filter design criterion is provided. Instead of constant thresholds, novel zonotope-based dynamic thresholds are utilized for residual evaluation. Finally, simulation results are presented to illustrate the effectiveness of the developed mechanism.

The aim of this article is to establish generic stability conditions for switched nonlinear systems with mode-dependent average dwell-time (MDADT) switching rules via Takagi–Sugeno (T–S) fuzzy modeling, which cover all unstable modes, all stable modes, and partially unstable modes as special cases. Different from traditional multiple and multiple discontinuous Lyapunov function (MDLF) methods, the proposed novel switching-signal-based multiple discontinuous Lyapunov function (SMDLF) approach divides each mode-running interval dynamically according to the actual switching of the system. The developed approach can not only yield less conservative bounds on the MDADT but can also handle all unstable subsystems, which cannot be done by means of the traditional MDLF. A class of SMDLF is constructed for continuous-time switched T–S fuzzy systems, and relaxed stability conditions are presented for the system with both stable and unstable subsystems, using a larger switching signal space. Then, novel stability conditions are deduced for all stable and unstable subsystems in terms of slow and fast MDADT switching signals, respectively. Finally, comparative simulation examples are provided to verify the advantages and effectiveness of the proposed approach.

In this article, the problem of event-triggered$\mathcal {H}_{\infty }$control design is investigated for a class of continuous-time switched Takagi–Sugeno (T–S) fuzzy systems. Specifically, the nonweighted$\mathcal {H}_{\infty }$performance is guaranteed for the system with mode-dependent average dwell-time (MDADT) switching, which is more general than the weighted one in most existing results. Meanwhile, the existence of asynchronous phenomenon between event-triggered instants is taken into account, which is more practical and complicated in the system under consideration. It is compulsive in most existing results that the candidate controllers are synchronous with the subsystems, while this constraint is released to deal with the case that the system switches more than once between two adjacent event-trigger instants. First of all, by verifying the existence of the minimal inter-execution time, it is demonstrated that the adopted event-triggered mechanism can exclude the Zeno behavior. Next, an improved criterion on stability and$\mathcal {H}_{\infty }$performance is derived for switched T–S fuzzy systems with MDADT switching. On this basis, the mode-dependent event-triggered mechanism and controllers are co-designed. Finally, two simulations are provided to illustrate the effectiveness of the developed event-triggered control scheme.

This article addresses the$H_{\infty }$control issue for Takagi–Sugeno (T–S) fuzzy systems via an event-triggered control mechanism. First, a hybrid event-triggered control strategy combined with an adaptively adjusted approach is proposed, by which the data transmission can be effectively reduced, and meanwhile, the Zeno behavior is excluded. Then, a discontinuous Lyapunov function is constructed for the resulting hybrid event-triggered control system, and a novel lemma is developed for studying the exponential stability and disturbance attenuation performance. By utilizing a time-varying variable to manage the error during the interevent intervals together with using the newly proposed lemma, sufficient criteria are established for the stability and control design of the event-triggered T–S fuzzy system with the imperfect premise matching. Finally, numerical simulations are presented to illustrate the usefulness and advantages of the obtained theorems.

In this work, the problem of event-based fault detection is addressed for unmanned surface vehicles (USVs) under denial-of-service (DoS) jamming attacks. A fault detection filter (FDF) is deployed to generate residual for USV systems with external disturbance and system faults. A resilient event-triggered mechanism is implemented to reduce the bandwidth occupation of communication network and energy consumption of USV system as well as mitigating the influence of DoS attacks. Based on the established framework, a switched residual system is constructed and a criterion is deduced to ensure the exponential stability and weighted$H_{\infty }$performance of residual system via piecewise Lyapunov functional approach. The FDF and resilient event-triggered mechanism are co-designed. Simulation results are provided to testify the efficient performance of the devised resilient event-triggered fault detection method.

In this article, finite-time$\mathcal {H}_{\infty }$control is studied for a kind of continuous-time-switched Takagi–Sugeno (T–S) fuzzy systems with mode-dependent average dwell-time (MDADT) switching. The dynamic event-triggered mechanism (ETM) is utilized to monitor the data transmission from the system plant to the controller, which more efficiently reduces the amount of transmitted data than the conventional static one. First, it is demonstrated that the adopted dynamic ETM can avoid the Zeno behavior, and also yield a larger minimal interexecution time compared with the static one. Then, an improved criterion of finite-time$\mathcal {H}_{\infty }$performance is introduced by utilizing a novel Lyapunov-like function with an internal dynamic variable. Based on this criterion, a dynamic event-triggered controller is designed together with a switching signal subject to the MDADT property. Finally, the validity, and virtues of the proposed control scheme are verified by two simulation examples.

This article investigates the sampled-data control for a class of Takagi-Sugeno (T-S) fuzzy Markovian jump systems via a novel looped functional approach. By refining the fractional delayed state concept, the looped functional is established to include more sampling information of the intervals not only from x(tk) to x(t) but also from x(t) to x(tk+1), which would contribute to a reduction in the conservatism. Then, a sufficient criterion is presented to ensure the stochastic stability of the resulting closed-loop system, based on which the sampled-data controller is further designed for the T-S fuzzy Markovian jump system under the influence of asynchronous premise variables. Finally, the obtained theorems are applied to a numerical example and a practical application to show the effectiveness and superiority of the proposed method.

This article deals with the zonotopic fault detection for fuzzy systems with event-triggered mechanism. An$\ell _1/h_{\infty }$fault detector design method is deduced with considering the asynchronous premise variables caused by event-triggered transmission, such that the residual signal is sensitive to system failure while robust to amplitude-bounded disturbance, and noise. Then, a novel zonotopic residual evaluation process is constructed by converting the asynchronization of premise variables into system uncertainties. Different from most published works on event-triggered fault detection where constant thresholds are utilized for residual evaluation, zonotopic thresholds for residual signal are designed with taking the influences of disturbance, noise, asynchronous premise variables, and event-based transmission into consideration. Finally, a numerical example is utilized to verify the effective performance of the developed strategy.

This paper concerns with the stability analysis for a class of discrete-time switched Takagi-Sugeno (T-S) fuzzy systems. By establishing a semitime-dependent Lyapunov function and exploring the property of mode-dependent average dwell-time switching, improved stability criteria are provided for switched T-S fuzzy systems containing both stable and unstable modes. Then, slow and fast switching strategies are designed, which are adopted for stable and unstable subsystems, respectively. Especially, we also provide the stability conditions for switched systems with all modes stable and unstable. Finally, the validities and advantages of provided techniques are illustrated by some simulation examples.

This paper is concerned with the problem of reliable finite frequency (FF) control for a cloud-aided active quarter-car vehicle suspension system subject to actuator failure. Instead of considering the entire frequency domain, we study the FF control which could restrain the external vibration input more effectively in the concerned frequency domain. In order to improve network bandwidth utilization, an adaptive hybrid event-triggered scheme is proposed for the cloud-aided quarter-car suspension framework. A fault-tolerant controller is designed with considering the communication time-delay and event-triggered mechanism. The adaptive event-triggered condition and the reliable controller are co-designed. Finally, a quarter-car active suspension model is studied to illustrate the efficient performances of the designed controller and the proposed event-triggered scheme.

This paper is concerned with the problem of finite-timeH∞synchronization for a class of discrete-time switched neural networks with quantized feedback controllers. First, we take advantage of mode-dependent average dwell time approach and semi-time-dependent (STD) Lyapunov function method to establish new criteria for the finite-time synchronization. Based on the newly developed criteria, a finite-time bounded real lemma is presented and further, the quantized state feedback controller is designed to ensure the finite-timeH∞synchronization of the underlying neural networks. The conservatism is further reduced by the proposed mode-dependent and STD controller. Finally, we use two illustrative examples to show the effectiveness and superiority of the results obtained in this paper.

In this paper, asynchronous H∞filtering is studied for discrete-time switched Takagi-Sugeno (T-S) fuzzy systems. New Lyapunov functions are constructed for switched systems with asynchronous switching between subsystems and candidate filters. These improved Lyapunov functions are dependent on the mode of filters instead of subsystems, which are more consistent with the switching mechanism of switched systems with asynchronous switching. Meanwhile, they are quasi-time-dependent, which are effective in achieving more general results than traditional time-independent Lyapunov functions. Based on the new Lyapunov functions, a stability and ℓ2-gain criterion is deduced for switched T-S fuzzy systems. Then, switched fuzzy filters are designed to guarantee that the filtering error system is globally uniformly asymptotically stable and has a prescribed H∞performance. At last, an illustrative example is provided to demonstrate the potentials and advantages of the proposed filtering scheme.

This article is concerned with the event-triggered fault detection problem for discrete-time systems subject to unknown-but-bounded (UBB) process disturbance and measurement noise via zonotope-based residual evaluation. To save communication resources, a novel discrete-time dynamic event-triggered mechanism is proposed. An optimal event-triggered l1/H∞fault detection observer (FDO) design criterion is proposed such that the generated residual is sensitive to system faults while robust against exogenous disturbance and measurement noise. On the basis of the designed FDO, a zonotopebased dynamic threshold for residual evaluation is well constructed by considering the impacts of disturbance, noise, and event-triggered communication. Finally, a vehicle lateral dynamic system is adopted to illustrate the effectiveness of the proposed zonotope-based dynamic eventtriggered fault detection mechanism.

The H∞filter design for a class of switched Takagi-Sugeno (T-S) fuzzy systems with persistent dwell time (PDT) is investigated in this paper. The considered switched fuzzy systems contain a limited number of subsystems and each local subsystem is represented by the well-known T-S fuzzy model. Compared with the dwell time (DT) switching or average DT switching that attracted quantities of interests over the last decade, the PDT switching considered in this paper is known to be more general. The stability and £2-gain analysis for switched systems with PDT switching are derived first, based on which a set of full-order H∞filter is designed to guarantee the global uniform asymptotic stability with a prescribed non-weighted H∞noise attenuation performance for the resulting filtering error system. Finally, the effectiveness of the provided method is illustrated with an example.

This paper is concerned with the event-triggered fault detection filter (FDF) design for an unmanned surface vehicle (USV) under the network environment. A framework of fault detection is established for a USV subject to wave-induced disturbance and actuator failures, in which an FDF is utilized to construct a residual model and an integral-based event generator is introduced to save communication resources. Compared with the traditional instantaneous value based event-triggering scheme and periodic sampling, the proposed event-triggering mechanism can not only reduce bandwidth utilization of the network more significantly, but also get rid of the Zeno phenomenon fundamentally. The event-triggering scheme and the FDF are co-designed. Finally, the efficient performance of the proposed fault detection method based on integral-based event-triggering scheme is illustrated by simulation.

This paper is concerned with the exponential synchronization for master-slave chaotic delayed neural network with event trigger control scheme. The model is established on a network control framework, where both external disturbance and network-induced delay are taken into consideration. The desired aim is to synchronize the master and slave systems with limited communication capacity and network bandwidth. In order to save the network resource, we adopt a hybrid event trigger approach, which not only reduces the data package sending out, but also gets rid of the Zeno phenomenon. By using an appropriate Lyapunov functional, a sufficient criterion for the stability is proposed for the error system with extended ( , , )-dissipativity performance index. Moreover, hybrid event trigger scheme and controller are codesigned for network-based delayed neural network to guarantee the exponential synchronization between the master and slave systems. The effectiveness and potential of the proposed results are demonstrated through a numerical example.

This work is concerned with dynamic output feedback control for a class of switched systems with mode-dependent average dwell time switching. By constructing a quasi-time-dependent Lyapunov function, the issues of global uniform exponential stability and ℓ2-gain analysis for the switched system are addressed firstly. Then a set of reduced-order output feedback controllers is designed, which is both mode-dependent and quasi-time-dependent. An example is presented to verify the effectiveness of the proposed method.

Standard support vector machine (SVM) serves as a powerful method for faults diagnosis and classification for last two decades. However, this standard method and its recent versions still encounter many problems for classification and diagnosis. To cope with these problems, a method (SVM-RFE) combines SVM, recursive feature elimination (RFE) and principal component analysis (PCA) is presented in this paper. SVM-RFE and PCA are able to effectively reduce the dimension of features and extract the most relevant features. Based on them, the classification accuracy and calculation speed are improved. In order to demonstrate the effectiveness of the proposed methods, they are applied to diagnose and classify the Wisconsin Diagnostic Breast Cancer (WDBC) data sets with 30 features. It should be noticed that SVM-RFE and PCA are initially applied to this data and the classification accuracy is much better than many other researchers' results. It can be seen that the proposed methods show satisfactory simulation results not only for diagnosing breast cancer but also for its high classification accuracy.

The paper considers the problem of synchronization for dynamical systems with unreliable communication links which are modeled as stochastic dropouts. A robust state feedback controller is designed such that the closed-loop system is stochastically stable in the mean square and preserves a guaranteed H∞performance. A numerical example is provided to show the effectiveness of the proposed results.