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The aim of this article is to develop a new cooperative path following control scheme for a team of autonomous underwater vehicles (AUVs) which track one curve with nonlinear uncertainties. Individual path-following controllers are designed to guarantee that each AUV meets the desired tracking performance. For the cooperative path following, a containment control approach is incorporated into the design, where each AUV is forced to evenly disperse on a path that is parameterized by a continuous variable over a communication network. The main features of the paper that unlike the existing designs are that: first, by employing the command filtered control technique, the assumption of second-order derivative of the reference path is removed. Second, a globally uniformly ultimately bounded (GUUB) path following control structure is proposed that enables two kinds of controllers to switch under different cases. Third, coordination between multiple AUVs is achieved through a containment design, and a path variable containment cooperative path following controller is derived that enables multiple AUVs to be evenly dispersed and guided by the virtual leaders. Finally, the stability analysis and simulation example are given to verify the proposed control strategy. [ABSTRACT FROM AUTHOR]

This study is concerned with the dynamical analysis and vibration attenuation for a three-dimensional (3-D) suspension cable system of a helicopter preceded by output constraints and input backlash. First, the dynamic model of a 3-D suspension cable is constructed in accordance with Hamilton’s principle. Then, a backlash inverse compensator is established to tackle the input backlash nonlinearities. Subsequently, three boundary controllers together with output signal barrier functions are proposed to dampen the oscillations while not violating the cable swing constraints. The uniform boundedness of the closed-loop system is guaranteed with recourse to the direct Lyapunov’s method. Finally, the validity and efficiency of the derived control laws are testified through simulation results. [ABSTRACT FROM AUTHOR]

Threats of cyberattacks have penetrated from disclosing critical user information to destroying/manipulating industrial control systems. Study on data security during network transmission has raised increasing attention in the systems and control community, which is found very necessary and timely in the context of Industry 4.0. In most existing approaches, the protection of the transmitted data from eavesdropping attacks and the detection of malicious integrity attacks are usually carried out separately. In this study, an integrated data-driven framework applicable at the control level is proposed to deal with secure transmission and attack detection simultaneously. In the framework, a secure correlation-based encryption/decryption approach and a trustworthiness judgement approach are proposed. Comprehensive discussions are made regarding the analysis of the sensitivity to attacks, the introduced time delay, and the design degree-of-free. Executable algorithms are presented, corresponding to which hardware is modularized and can work standalone independent from the configuration of the monitoring and control systems or any third-party authentication agencies. Evaluation results on a simulated two-area frequency-load control power grid system are provided to show the effectiveness and performance of the proposed approaches. [ABSTRACT FROM AUTHOR]

This article presents a novel secure-control framework against sensor deception attacks. The vulnerability of cyber-physical systems with respect to sensor deceptive attacks makes that all sensor measurements are not reliable until the system security is assured by an attack detection module. Most of the active attack detection strategies require some time to assess the system security, while injecting a watermark signal to ease the detection. However, the injection of watermark signals deteriorates the performance and stability of the plant. The proposed control framework consists of a dual-rate control (DRC) that is able to stabilize the plant using: 1) a model predictive controller that operates at a slower sampling time; 2) a state-feedback predictor-based controller that operates in the nominal sampling time disregarding the use of the untrustworthy measurements until the attack detector is able to certify the security; and 3) a reconfiguration block (RB) for palliating the effect of the watermarking. Simulation results indicate the efficacy of the proposed DRC framework to defend the system from cyber-attacks and the ability of the RB to improve the closed-loop performance during the watermark injection. [ABSTRACT FROM AUTHOR]

In this article, the output-feedback control problem for a class of nonlinear time-delay systems has been considered. Unmeasured system states and the time-varying delays which appear in all state variables bring great challenges to the controller design. Novel Lyapunov–Krasovkii functionals with control gains are proposed for a delay-independent controller. The system is proved to be asymptotically stable driven by the controller with suitable design parameters. Finally, we apply the new control scheme to a two-stage chemical reactor system and the time-delay tension leg platform system, the effectiveness of the control scheme is illustrated in the simulation results. [ABSTRACT FROM AUTHOR]

Strategic traffic management is crucial for combating traffic congestion at the macroscopic level. However, such a field is still relatively unexplored, particularly for microscopic control objects, such as intersections and coordinated intersection groups. This article proposes a human-in-the-loop recommendation system for strategic urban traffic management, which follows an agent-based structure. A regional agent dispatcher is defined to assign agents for operation whenever “operation on-demand” is required. Such a requirement is identified by a daily-dependent operational mode on strategic traffic operations at a control object level. The strategic management scheme for each control object is guided by a strategic agent (customized), which is essentially a deep recommender model with a specific architecture. By featuring the multiagent design, a customized operational scheme can be generated at the intersection level, which instructs the corresponding controller to take specific operations. The utility of the recommendation system is demonstrated via a case study using real-world traffic data. In both offline and online evaluations, the system performs consistently at traffic operational recommendations in different scenarios and has the potential to provide more reasonable traffic operational strategies than a human-operated system. [ABSTRACT FROM AUTHOR]

This article considers the stabilization issue of switched discrete-time positive systems (SDPSs) with delay by using asynchronous control. Combining transition probability (TP) with mode-dependent average dwell time (MDADT), called TP-based MDADT switching, the SDPSs are more practical than classical models with average dwell-time (ADT) switching. With the aid of a co-positive Lyapunov–Krasovskii functional (CLKF), sufficient conditions ensuring the exponential stability almost surely (ES a.s.) of the SDPSs without control is studied, where the mode is not necessary to be stable. After that, a mode-dependent controller with switching delay is designed to stabilize the SDPSs in the case that there are unstable subsystems. An algorithm is provided to design the control gains. It is discovered that the mode in the closed-loop SDPSs is not required to be stable on synchronous and asynchronous switching intervals. Numerical simulations verify the merits of the new results. [ABSTRACT FROM AUTHOR]

This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-delay systems with input delays and unknown control directions. Different from previous researches that investigated delays and constraints separately, the novelty of this article lies in that it simultaneously considers delays (state and input delays) and input constraints (magnitude and rate constraints) for a class of uncertain nonlinear systems. In this article, the uncertain states and input delays are handled by integrating a constructed auxiliary system that functions as an observer with neural networks (NNs), with which the adverse effects caused by the uncertain states and input delays can be approximated and compensated. By involving smooth hyperbolic tangent functions in the designed auxiliary system, the problem of magnitude and rate constraints of the control input is fully addressed. Then, the backstepping technique runs through the entire control designing process, which allows the designed adaptive neural control strategy to handle the input constraints and delays at the same time. Furthermore, Nussbaum functions are employed to resolve the problem of unknown control directions. Due to the introduction of an input-driven filter, only the output of the system is required to be measured as the control feedback, which promotes the applicability of the designed controller. Under the proposed control scheme, semiglobal, uniform, and ultimate boundedness of all signals of the closed-loop system is realized with uncertain control directions, input and state delays, and guaranteed magnitude and rate constraints of control inputs. Finally, simulation results are illustrated to verify the effectiveness of the presented control method. [ABSTRACT FROM AUTHOR]

Four-wheeled steerable mobile robots have been widely used in industrial fields. However, robust tracking control is hard to achieve with a fixed maneuver mode. Based on a novel internal coupled sliding mode control (ICSMC) method, this study handles the above challenge by constructing a mode-dependent switched mobile robot (MSMR), and then designing an asynchronous $H_{\infty}$ continuous stabilization control scheme. This method governs the system behaviors to perform adaptive-mode allocations asynchronously and smoothly. First, a unified expression of MSMR is formulated, which regards the maneuver modes as optional subsystems. Then, with the coupled sliding surfaces and modified reaching law, an enhanced chattering-free ICSMC technique is established to optimize continuous control inputs for each subsystem. Moreover, using a surveillant criterion that depicts the energy decaying rate, an evaluation rule is built to distinguish the mismatched subsystems and then realize autonomous mode switching for the concerned MSMR. Utilizing piecewise Lyapunov functional technique and mode-dependent average dwell time, new sufficient conditions are derived for global exponential stability and $H_{\infty}$ performance. Comparative experiments implemented on the developed MSMR are carried out to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Mechanical systems with (possibly fast) time-varying but bounded uncertainty are considered. The exact value of the boundary is unknown. All the designer can get is that the boundary values are in a (known) fuzzy set. On the basis, a robust control method is proposed, which can ensure the uniformly bounded and uniformly ultimately bounded of the controlled mechanical system. The control contains two flexibly selectable design parameters. We seek to choose the optimal parameters. For a superior performance, two fuzzy-set-based performance indices are proposed to reflect the transient performance as well as the steady-state performance. Each performance index can be influenced by two design parameters. However, influences are nonconciliatory. This poses a design dilemma: the increase of a parameter may harness one performance while inflict the other. Therefore, the “optimal” choice of the design parameters is not intuitively clear. To resolve this dilemma, the two-player Nash-based noncooperative game theory is adopted, which is a notable feature of this article. Once the problem is formulated, we show that there is always a Nash-equilibrium solution to the two-player problem. We also show how to find it. The approach is very general, which also can be extended to $n$ -player Nash game for future research. The control is applied to a compressor powered by permanent magnet synchronous motor (PMSM) as a demonstration. The resulting performance shows that this Nash-based robust control design is both practical and effective. [ABSTRACT FROM AUTHOR]

This article proposes static/dynamic event-triggered and self-triggered discrete gain scheduled control with a designable parametric minimal interevent time (MIET) to achieve semiglobal stabilization of linear systems with input constraints. First, a novel static event-triggered discrete gain scheduled control, which can improve the control performance and simultaneously save the communication resources, is proposed by utilizing the properties of the parametric Lyapunov equation (PLE). Moreover, the static self-triggered mechanism, in which the next control law updates based on the previous triggered states, is also designed to avoid the monitoring of all states. In order to further increase the interevent times (IETs), the corresponding dynamic event-triggered and self-triggered discrete gain scheduled control are designed, respectively. All the proposed algorithms can not only avoid the Zeno phenomenon but also provide a designable parametric MIET. This allows to easily find a tradeoff between the IETs and the control performance by adjusting the only design parameter. In addition, by exploiting the properties of the PLE, the designed algorithms avoid the complicated relationship between the MIET and the system matrices. In some cases, the MIET can totally avoid the relationship with the system itself and be designed as an arbitrarily large bounded constant. Finally, applications to the spacecraft rendezvous system show the effectiveness of the established algorithms. [ABSTRACT FROM AUTHOR]

This article investigates the finite-time stability (FTS) of switched nonlinear systems (SNSs) with state jumps. Our main concerns are twofold. One is that the SNS only consists of FTS subsystems. The other is that the SNS has both FTS subsystems and exponentially stable (ES) subsystems. Due to the switches and state jumps, the main challenge of the study comes from the estimation of settling time and the synthesis of different Lyapunov functions for FTS/ES subsystems. Based on the analytical-inductive method and the initial-value-dependent dwell-time approach, several FTS criteria for the SNSs are established. Then, we provide the estimation of settling time which is explicitly dependent on the dwell time and initial value. Our results can be applied to the finite-time control problem of switched systems with/without state jumps, even when some subsystems can only be exponentially stabilized through linear feedback control and others are finite-time stabilized by discontinuous/nonlinear controls. Finally, three examples are given to illustrate the proposed results. The finite-time stabilization of a continuous stirred tank reactor and the finite-time consensus of a multiagent system are both adopted as potential applications. [ABSTRACT FROM AUTHOR]

This article presents an input-and-measurement event-triggered output-feedback chattering reduction control for microelectromechanical system (MEMS) gyroscopes. To realize online estimation with decreased communication burden along sensor-to-control channel, a switching threshold-based sampler is embedded to achieve an intermittent measurement-based extended state observer (IMESO) capable of synchronously observing unavailable velocity states and disturbances, meanwhile, a mathematical presentation reflecting the interaction between design parameters and upper boundary of estimation errors is deduced to make argument tuning easy. Next, an event-triggered output-feedback control rule is developed in the controller-to-actuator channel to obtain a discrete control signal with less occupation on communication resources without inducing Zeno phenomena. Besides, to enforce system profiles evolve within the predefined performance boundaries with reduced chattering, a tracking differentiator (TD)-based prescribed performance control (TDPPC) is proposed, where the time differentiation of the preselected envelopes can be managed with smooth transient, and a balance between system performance and sampling cost can be ensured. Finally, a sigmoid function-based TD (STD), rather than dynamic surface control, is utilized to overcome the complexity explosion. Comparison simulations are performed to show the superiorities and effectiveness of the established controller. [ABSTRACT FROM AUTHOR]

In this article, the cooperative fuzzy hierarchical fault-tolerant containment control (FTCC) method is proposed for nonlinear multiagent systems (MASs) over switching directed topologies. Based on the hierarchical mechanism, the problem of the cooperative FTCC for nonlinear MASs under switching directed topologies is decoupled into the cooperative containment control problem of the virtual reference system (upper layer) under switching directed topologies and the tracking control problem of the actual system (lower layer). Due to the existence of switching topologies, the state of the virtual reference system may jump, which further affects the transient performance of the lower tracking system; moreover, the actuator faults may also cause a sudden change in actual system. In order to mitigate the influence of switching topologies and actuator faults on the lower tracking system, the generalized restricted potential function is introduced to ensure the norm of the lower tracking error within the predefined performance function. Finally, a simulation example is introduced to illustrate the theoretical results obtained. [ABSTRACT FROM AUTHOR]

This article is concerned with the robust adaptive control circuit design for pulse wide modulation (PWM)-based dc–dc buck converters with load variations and exogenous disturbances. A robust adaptive perturbation rejection control strategy is first developed to suppress time-varying and state-dependent perturbations, which are composed of load variations and disturbances. Then, equivalent analog control circuits of the adaptive control strategy are implemented on the basis of the circuit theory. Bounded tracking of the closed-loop converter system in the presence of perturbations is achieved based on the Lyapunov stability theorem. Simulations and experimental results are provided to validate the efficiency of the proposed adaptive perturbation rejection control strategy in a dc–dc buck converter system. [ABSTRACT FROM AUTHOR]

In this article, an adaptive swarm control within saturated input based on the nonlinear coupling degree is proposed. Swarm control is a forward study in kinematics and dynamics of the swarm system. However, the coupling degree in the previous work can only manifest whether the agents in the swarm being connected or not, ignoring the connection strength. As a result, the nonlinear coupling degree is proposed, which is more suitable for practical engineering than the previous coupling degree. Based on the nonlinear coupling degree, we put forward novel swarm kinematics and dynamics. Besides, the effects of input saturation and nonlinear dynamics should be considered for this novel swarm control based on the nonlinear coupling degree. Therefore, we introduce the backstepping method to design an adaptive swarm controller. With this controller, the input saturation auxiliary system is designed to reduce the effects of input saturation, and a radial basis function neural network (RBF-NN) is introduced to approximate the nonlinear dynamics. To overcome the differential explosion in the backstepping method, a command filter is put forward to reduce the amount of calculation and reduces the difficulty of the controller design. It is proved that the proposed controller ensures stability based on the Lyapunov stability theory. Finally, the simulation results of a multiagent system composed of six omnidirectional mobile robots illustrate the validity of the proposed controller. [ABSTRACT FROM AUTHOR]

The fixed-time control problem for a class of interconnected systems is studied in this article via an asynchronous event-triggered control strategy, in which all subsystems are interconnected by discontinuous interactions. Especially, due to the discontinuity of interactions, the existence of solutions for the concerned systems is solved via the framework of differential inclusion. Unlike the common ones, the asynchronous event-triggered mechanism in this article generates samplings, triggering events, and control updates asynchronously among multiple subsystems. More significantly, due to the discontinuity of the interactions, a fixed-time discontinuous control law and a specific event-triggered scheme are designed to stabilize this class of interconnected systems in a fixed time. In addition, the interexecution time is lower bounded by a positive constant, and it is assured that the Zeno behavior will not happen. Finally, the effectiveness of the obtained results is illustrated by an example. [ABSTRACT FROM AUTHOR]

This article addresses the asynchronous event-triggered control problem for switched Takagi–Sugeno (T–S) fuzzy systems under data injection attacks. In reducing communication data update frequency, event-triggered control is an effective control method. The periodic sampling-based adaptive event-triggering schemes with switching structure are first proposed, which can dynamically adjust triggered conditions based on system performance. It is assumed that only the event-triggered and quantized data of the system state and the event-triggered switching signal are available for controllers. However, since the switching signal is sampled and triggered, asynchronous switching may occur between subsystems and subcontrollers. Furthermore, the data injection attacks are considered in the communication network of the system. A time-delay closed-loop switched T–S fuzzy system model is obtained by using a model transformation technique. The resulting criterion provides sufficient conditions to ensure that the closed-loop system subject to data injection attacks is exponential stability with an $H_{\infty }$ performance. Moreover, a set of conditions for the co-design of controllers and adaptive event-triggering schemes is presented. Finally, simulations are given to verify the effectiveness of the asynchronous event-triggered control design. [ABSTRACT FROM AUTHOR]

This article addresses an event-triggered adaptive fuzzy tracking control problem for nonlinear systems with unknown control directions. To achieve the practical tracking, fuzzy logic systems are employed to approximate unknown nonlinear function. Nussbaum functions are adopted to address the problem of the unknown control directions. The newly designed controller not only guarantees the tracking error that converges to an arbitrary small neighborhood near the zero but also reduces the communication burden from the controller to the actuator. Moreover, the feasibility of the proposed event-triggered mechanism is verified by excluding Zeno behavior. Finally, the simulation result proves the effectiveness of the designed control scheme. [ABSTRACT FROM AUTHOR]

The consumption of communication resources is an essential issue when control tasks are implemented in a wireless network environment. In order to lessen the network resources, a novel model-based (MB) adaptive event-triggered (ET) tracking control scheme is put forward in this article for strict-feedback discrete-time nonlinear systems. In this article, an event-based adaptive model is constructed by the combination of an $n$ -step-ahead predictor and event-sampled neural networks. Then, the adaptive neural model is used for designing the MB ET controller. Besides, a modified ET condition is constructed without any delay. By combining a decoupled backstepping framework, the reverse Lyapunov stability technology is developed to verify the ultimate boundedness of all closed-loop signals and the convergence of the tracking error. Compared to the zero-order hold method, which keeps transmitted state signals unchanged in the interevent period, the proposed MB ET control scheme can keep the real-time update of state signals transmitted to the controller. It means that the triggering error will be smaller by the MB trigger mechanism, thereby improving the event-based tracking performance and further saving communication resources. Comparisons of simulation results are given to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This article presents a novel stochastic event-triggered communication scheme (SETS) and a switching-like $H_{\infty }$ control method for networked control systems (NCSs) through an open bandwidth-limited network. To overcome the stochastic Denial of Service (DoS) attacks and save the limited network resource, a SETS is first proposed to decrease the number of packets transmitted while considering the malicious DoS attacks. Compared with the existing event-triggered schemes under a precondition that all triggered packets must be successfully transmitted, the proposed SETS has outstanding flexibility since it allows part event-triggered packets to be lost during the communication process. To fully use the dynamic features of communication in an open network, a switching-like control scheme is well designed, which can actively choose the different controller gains based on the current network Quality of Services (QoSs). Then, a networked closed-loop model is constructed, which considered both the effects of SETS and stochastic DoS attacks in a unified framework. Sufficient conditions for the existence of the switching-like controller are presented to ensure the stability of the networked control system while achieving the prescribed performance index. Gain matrices of the desired switching-like controller and the SETS parameters are reached in the light of the solutions to certain matrix inequalities. Compared with the existing time-invariant control strategy in a transmission interval, higher control performance can be expected since both the dynamic network information and the latest available state are well considered in the proposed communication and control framework. Finally, an illustrative example is given to verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

A novel event-triggered optimal tracking control (ETOTC) method is developed for discrete-time nonlinear systems in this study. For the time-invariant desired trajectory, we prove that the tracking error is asymptotically stable, and an upper bound of the real performance index can be predetermined by a design parameter. For the time-varying desired trajectory, the developed triggering condition reduces communication costs by relaxing the restriction of the asymptotic stability of the closed-loop system, and we prove that the tracking error is uniformly ultimately bounded (UUB). The developed ETOTC method entails obtaining the next state of the real system. Therefore, a parallel control approach is proposed to predict the next state by constructing a parallel system for the real system. Neural networks (NNs) and adaptive dynamic programming (ADP) techniques are utilized in the parallel control approach. Moreover, the stability analysis of the closed-loop system is shown, and the tracking error and NN weight estimation errors are proved to be UUB using the Lyapunov approach. Finally, we validate the developed ETOTC method through two simulations. [ABSTRACT FROM AUTHOR]

In this article, a collection of conditions to achieve asymptotic stability of switched nonlinear systems with guaranteed safety via a state-dependent switching law are provided, where the asymptotic stability of individual subsystem is not assumed. Multiple barrier functions and multiple Lyapunov functions (MLFs) are merged as a tool for analyzing the asymptotic stability with guaranteed safety control problem of switched nonlinear systems. Meanwhile, the state-dependent switching law is designed to refrain zeno phenomenon. Moreover, bilinear sum of squares methodologies are employed to construct corresponding MLFs for switched nonlinear systems. Finally, three simulation examples are introduced to prove the effectiveness of the provided method. [ABSTRACT FROM AUTHOR]

This work addresses the nonfragile $H_{\infty }$ controller design problem for a class of discrete-time uncertain nonlinear systems. The norm-bounded uncertainty is contained in the nonlinear plant, which is described by the well-known Takagi–Sugeno (T–S) fuzzy model. The controller gain perturbation is also considered. When the input signal is transmitted from the controller to the system through the digital communication channels, it will be quantized by a static quantizer. The main attention is to design the nonfragile $H_{\infty }$ state-feedback controller for the closed-loop quantized uncertain T–S fuzzy system. By introducing some auxiliary scalars and the fuzzy basis-dependent Lyapunov function approach, sufficient conditions are established in the form of linear matrix inequalities (LMIs). The construction for the nonfragile $H_{\infty }$ controller can be completed by solving these LMIs. In the end, the applicability and effectiveness of the proposed method have been illustrated by two simulation examples. [ABSTRACT FROM AUTHOR]

The control objective of the vertical plane underactuated manipulator (VPUM) is generally to swing up the end point (EP) from the vertical down equilibrium point (VDEP) to the vertical up equilibrium point (VUEP), and finally, to stabilize it at the VUEP. The zone control methods are usually used to achieve this control objective, but the problem of these methods is that they cannot find a unified zone range, and it is easy to appear singularity in the motion process. In this article, for two-link VPUMs, we propose a control strategy based on trajectory planning and optimization, which does not need to divide the zone range, avoids the singularity problem, and can achieve the control objective quickly and smoothly. We design the trajectory by using the time scale method for the active link according to the initial and target states. Then, we obtain the trajectory parameters by employing differential evolution algorithm to ensure that the passive link can also move from the initial states to the target states simultaneously. We design a sliding mode tracking controller to make the active link move along the designed trajectory, so the EP is moved to VUEP. Meantime, we design a sliding mode stabilization controller to ensure that the system is stable at VUEP. Finally, the universality and robustness of the proposed method are proved by simulations. [ABSTRACT FROM AUTHOR]

In an automated manufacturing system (AMS), resources are, in general, subject to unpredictable failures, which invalidate many existing deadlock control strategies. In this article, we propose an adaptive deadlock control policy for an AMS with multiple types of unreliable resources. The considered AMS is modeled with a system of simple sequential processes with resources. First, based on an elementary siphon control method, monitors are added for elementary siphons and some particular dependent siphons to ensure the liveness of a system if there are no resource failures. By considering the fact that an unreliable resource may fail in a system, recovery subnets are added to describe the resource failures and recoveries. Since a monitor added for a siphon may not be able to guarantee that the corresponding siphon is always marked if the failure of a resource in the siphon occurs, the concept of switch controllers is presented so as to make the siphon always remarked if it is emptied by resource failures. It is verified that the adaptive controller proposed in this article can guarantee the liveness of the controlled system no matter whether unreliable resources break down or not. More importantly, if there is no resource failure, the system can maintain predefined production without degrading planned system performance. Finally, examples are presented to illustrate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

This article investigates global exponential stabilization (GES) of Takagi–Sugeno (T–S) fuzzy memristive neural networks with multiple time-varying delays (DFMNNs) via intermittent control strategy. By resorting to differential inclusion theory, comparison means, and inequality techniques, some results are developed to ensure GES of the underlying DFMNNs via a fuzzy intermittent state feedback control law within the sense of Filippov. The outcome is generalized to GES of FMNNs with infinite distributed time delays. Additionally, the global exponential stability of FMNNs with discrete time-varying delays is explored in terms of 1-norm. The derived conditions herein contain certain existing ones as special cases. Finally, three examples are presented to illuminate the validness of the outcomes. [ABSTRACT FROM AUTHOR]

This article deals with the distributed $\mathcal {H}_{\infty }$ robust control problem for linear multiagent systems perturbed by external disturbances and norm-bounded uncertain parameters over the Markovian randomly switching communication topologies. To tackle this problem, the distributed observer-based controller is proposed, which requires the relative information between neighbors and the absolute information of a subset of the nodes, and thus is intrinsically distributed. It is of great interest to see that the distributed $\mathcal {H}_{\infty }$ robust control problem governed by such a controller can be converted to the stabilization with $\mathcal {H}_{\infty }$ disturbance attenuation problems of some decoupled linear systems, whose dimensions equal those of a single node. Then, the $\mathcal {H}_{\infty }$ stochastic robust performance region is defined to indicate the robustness of this controller against the variation of communication topologies. It is theoretically shown that the distributed observer-based controller yields bounded and connected robust performance region. Finally, the theoretical results are verified by conducting numerical simulations and experiments. [ABSTRACT FROM AUTHOR]

In cyber–physical systems (CPSs), it is of great importance to handle network attack issues. In this article, we consider the supervisory control layer of CPSs, focusing on closed-loop control systems vulnerable to sensor-reading modification attacks (SM-attacks), which may disguise the occurrence of an event as a different event by modifying appropriately sensor readings in sensor communication channels. In particular, we consider the plant modeled as a bounded Petri net and the control specification consisting in liveness enforcing. Based on repeatedly computing a more restrictive liveness-enforcing supervisor under no attack and constructing a so-called basic supervisor, a method that synthesizes a liveness-enforcing supervisor tolerant to an SM-attack is proposed. [ABSTRACT FROM AUTHOR]

Synchronization of a class of drive-response timescale-type nonautonomous proportional-delayed neural networks (TNPNNs) is addressed in this article. The key technique to cope with the proportional term is using comparison principle. By timescale theory, inequality technique, and comparison principle, criteria of synchronization are obtained. The method used in this article is effective to cope with TNPNNs and it is a direct approach as well by eliminating the conventional exponential transformation. The obtained results are verified with three examples. [ABSTRACT FROM AUTHOR]

This article investigates the coordination of a class of underactuated systems subject to limited energy supply and channel bandwidth and aims to stabilize system states and exclude Zeno behaviors simultaneously. First, by means of event-triggered (E-T) and quantized techniques, several novel quantized sampled-data-based E-T schemes are constructed, which only require discrete-time controller updates and partial quantized states, and thus efficiently mitigate the control and communication workloads. Then, in order to further lower the communication consumptions, several new triggered sampled-data-based communication rules under fixed and switched networks are established, where the communications are performed only at some specific instants and, thus, the ideally continuous-time signal transmission among neighbors can be avoided. Note that sufficient criteria for achieving the coordination of the underactuated systems are derived in terms of the Lyapunov–Krasovskii functional method. Finally, numerous simulations are carried out to demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This article focuses on the robust D-stabilization analysis of fractional-order control systems where each of the system and the controller may be of fractional order. The coefficients of the system are considered as complex linear functions of interval uncertain parameters, so this article deals with fractional-order polytopic systems. First, a necessary and sufficient condition is introduced for the robust D-stabilization of the closed-loop control system based on the zero exclusion condition and the value set concept. Then, the geometric pattern of the value set of the characteristic polynomial is obtained analytically using the exposed vertices. Second, a function is presented to check the introduced condition. Third, the transition points, at which the exposed vertices of the value set may change, are derived to reduce the computational burthen. Fourth, a new function is provided to determine the D-stability robustness radius (margin) of these control systems, that is, determining bounds on the uncertain parameters such that the control system remains D-stable. The achieved results are applicable to systems of incommensurate order and consequently of commensurate order. Finally, numerical simulations and practical experiments based on a three-degrees-of-freedom flight simulator turn table are conducted to illustrate the achieved results. [ABSTRACT FROM AUTHOR]

This article aims to propose a more efficient control algorithm for uncertain nonlinear systems. An intelligent self-organizing double function-link fuzzy brain emotional control system is proposed which comprises a self-organizing double function-link fuzzy brain emotional controller (SDFLFBEC) and a compensation controller. The proposed SDFLFBEC consists of four substructures and a fuzzy inference system. The substructures are the prefrontal cortex, the amygdala, a double function-link network (FLN) and a self-organizing structure. The prefrontal cortex and the amygdala networks work as a mathematical form that presumes the judgment and emotion of a brain. Specifically, a new double FLN is designed to support the above networks for updating their weights. Next, a self-organizing structure can automatically add or prune the layers to achieve efficient network structure. In addition, the fuzzy inference rules are presented to explain the inference processes of the amygdala and orbitofrontal networks. From the above factors, the proposed SDFLFBEC can effectively reduce the tracking error and achieve favorable control performance. The parameters of the control system are adjusted online using the derived adaptation laws that are taken from a Lyapunov function so that the stability of the system is ensured. Simulation studies of a biped robot and the experimental results of a magnetic levitation system are employed to validate the effectiveness and superiority of the proposed SDFLFBEC. [ABSTRACT FROM AUTHOR]

This article concentrates on finite-time stabilization and energy consumption estimation for nonlinear systems with and without delay. By constructing an appropriate controller and utilizing inequality techniques, sufficient conditions are proposed to guarantee the finite-time stability of the delayed nonlinear system. Furthermore, the energy consumption produced in system controlling is estimated by inequality techniques. Then, we formulate similar results for the delay-free case. Finally, numerical examples are presented to demonstrate the effectiveness of our theoretical results. [ABSTRACT FROM AUTHOR]

This article presents a stabilization achievement for a switched nonlinear time-delay system through output-feedback control under the sampled-data and global senses. An observer with the sampled output measurement is constructed to evaluate the unavailable states, and then a controller formed from the sampled observer states is given. For the stability analysis, a merging virtual switching signal (MVSS) is created to express the asynchronous switching mechanism in the resultant closed-loop system. Through designating a positive-definite function as the Lyapunov function candidate, a proof is conducted to reveal that global stability can be ensured for the considered systems which work under the time-varying delay case and the developed sampled-data controller with a switching restriction. Finally, two examples are provided in this article to indicate the given control strategy usefulness. [ABSTRACT FROM AUTHOR]

This article investigates a political party or an association social network where members share a common set of beliefs. In modeling it as a distributed iterative algorithm with network dynamics mimicking the interactions between people, the problem of interest becomes that of determining: 1) the conditions when convergence happens in finite time and 2) the corresponding steady-state opinion. For a traditional model, it is shown that finite-time convergence requires a complete topology and that by removing neighbors with duplicate opinions reduces in half the number of links. Finite-time convergence is proved for two novel models even when nodes contact two other nodes of close opinion. In a deterministic setting, the network connectivity influences the final consensus and changes the relative weight of each node on the final value. In the case of mobile robots, a similar communication constraint is present which makes the analysis of the social network so relevant in the domain of control systems as a guideline to save resources and obtain finite-time consensus. Through simulations, the main results regarding convergence are illustrated paying special attention to the rates at which consensus is achieved. [ABSTRACT FROM AUTHOR]

This article proposes a sliding-mode-observer (SMO)-based control strategy to regulate the dc-link voltage for a three-phase two-level active front end (AFE). The SMO is designed for the voltage control loop to estimate the external load which is abruptly connected to the AFE dc-link and consequently causes the dc-link voltage fluctuation. The estimated load value is used to compensate the voltage loop controller, therefore, the voltage loop gains more robustness against the load perturbation and its disturbing effect is greatly reduced. The effectiveness and advantage of the proposed control strategy has been verified through theoretical analysis, simulations, and the real-application experiments conducted on a 5 KVA laboratory AFE. The results show that the proposed control strategy provides obvious improvement of the dc-link voltage control performance comparing with the conventional PI controller and demonstrates stronger robustness against the operating point variations caused by the changes in external load and dc-link capacitance. [ABSTRACT FROM AUTHOR]

Resilient distributed coordination control is studied on multiarea power systems with low inertia under hybrid attacks, including denial-of-service (DoS) attack and deception attack. The communication among various areas under the DoS attack is deteriorated to switching residual topologies whose time characteristic is modeled by model-dependent average dwell time (MDADT). Deception attack with malicious strategy targeting at negative feedback control is modeled by a sign function. To obtain resilience performance of the power system under low inertia and hybrid attacks, resilient distributed scheme combining load-frequency control (LFC) with virtual inertia control (VIC) is proposed. Then, resilient frequency control problem of the studied power system is converted to $H_{\infty }$ control of the switched nonlinear system. By employing the Lyapunov stability theory and switched system method, the resilient conditions are given by the lower bound of the average dwell time of each residual topology and the upper bound of deception attacks. Furthermore, a linear matrix inequality (LMI) technique is used to design the distributed resilient control gains of the LFC-VIC scheme. Finally, a simulation of four-area power systems is carried out to verify the validness of our theory. [ABSTRACT FROM AUTHOR]

In this article, an event-triggered control scheme is proposed for a group of elliptical agents to achieve a predefined formation. The agents are assumed to have the same dynamics, and the control law for each agent is only updated at its event sequence based on its own minimum collision time and deviation time. The probability-driven controller is designed to prevent the stuck problem among agents. Mapping-adaptive strategy and angle-adaptive scheme based on the minimum collision distance are also developed. Two examples are presented to analyze and demonstrate the effectiveness and potential of the new event-triggered adaptive control algorithm. [ABSTRACT FROM AUTHOR]

This article involves the problems of stabilization and guaranteed cost control for a class of delayed continuous-time nonlinear systems. The sufficient conditions for the existence of stabilization controllers and guaranteed cost controllers are investigated by constructing a new Lyapunov matrix-based Lyapunov–Krasovskii functional. These conditions can be easily verified by using standard compute software (e.g., the toolbox YALMIP of MATLAB), since they are expressed as simple linear matrix inequalities. Furthermore, the feasible solutions of these linear matrix inequalities are used to describe the explicit forms of stabilization controllers and guaranteed cost controllers. Finally, the validity of the proposed Lyapunov matrix-based LKF method is tested by two numerical examples. [ABSTRACT FROM AUTHOR]

In this article, the containment control problem of multiagent systems (MASs) with active leaders under a directed communication graph is addressed. A novel pull-based event-triggered protocol combined with aperiodic sampled-data mechanism is first presented, where each agent merely updates controller at its own triggering instants. Under the proposed control protocols, the information is only exchanged and calculated at the aperiodic sampling instants, therefore, it can reduce communication congestion and save computing resources. Furthermore, the Zeno behavior is naturally excluded because the trigger instants are in the set of aperiodic sampled instants. By virtue of the algebraic graph theory and Lyapunov stability analysis, it is shown that the active leaders can reach their desired states predefined arbitrarily and all followers are driven to the convex hull formed by the leaders. Finally, an illustrative example is given to validate the theoretical results and emphasize the advantages of the proposed protocols. [ABSTRACT FROM AUTHOR]

This article proposes a global adaptive neural network tracking control method for uncertain strict-feedback nonlinear system with output constraint and dead zone to achieve predefined-time convergence of the tracking error to predefined accuracy. First, an integral-type Barrier Lyapunov function (BLF) is constructed to handle output constraint. Next, radial basis function neural network (RBFNN) control and robust control are used to tackle unknown nonlinear function. The continuous switching function is designed to switch RBFNN control to robust control when the arguments of the unknown function exceed the active region of neural network. Utilizing the property of radial basis function, we derive the upper bound of the term containing the unknown nonlinear function and design adaptive laws to determine the derived upper bound and robust control gain. Then, the predefined time virtual control inputs are obtained and their derivatives are estimated by finite time differentiator. Finally, we use the dead zone inverse technique to obtain the actual control input. Stability analysis shows the presented control scheme achieves global convergence of the errors to predefined accuracy within predefined time. The simulation results verify the effectiveness of the presented control scheme. [ABSTRACT FROM AUTHOR]

In this article, we consider controlling a class of single-input–single-output (SISO) commensurate fractional-order nonlinear systems with parametric uncertainty and external disturbance. Based on the backstepping approach, an adaptive controller is proposed with adaptive laws that are used to estimate the unknown system parameters and the bound of unknown disturbance. Instead of using discontinuous functions, such as the sign function, an auxiliary function is employed to obtain a smooth control input that is still able to achieve perfect tracking in the presence of bounded disturbances. Indeed, the global boundedness of all closed-loop signals and asymptotic perfect tracking of fractional-order system output to a given reference trajectory are proved by using fractional directed Lyapunov method. To verify the effectiveness of the proposed control method, simulation examples are presented. [ABSTRACT FROM AUTHOR]

This article investigates the observer-based non-negative scaled edge-consensus problems of a continues-time networked system with or without input saturation, in which the proposed algorithm only uses the neighboring edges’ outputs. First, the original networked model and preliminary algorithm are simplified by using the line graph theory and constructing a new variable. Then the specific mathematical formulations of feedback matrix and observer matrix are both derived by combining $H_{\infty }$ control theory and low-gain feedback technique. Next, sufficient conditions which can guarantee the non-negative edge states and bounded control inputs are obtained. Moreover, the advantages of low-gain feedback technique for guaranteeing the non-negative edge states and designing the algorithm are developed. Finally, three cases are used to verify the validity of the theorems. [ABSTRACT FROM AUTHOR]

This article is concerned with the anti-disturbance control for Markov jump systems with matched and mismatched disturbances. First, the matched part is estimated by an output-based disturbance observer. Meanwhile, the mismatched part is attenuated by the $H_{\infty }$ controller. Therefore, a composite static output control scheme is built to make the closed-loop system stable with the required $H_{\infty }$ performance. Second, an integral sliding-mode output (ISMO) control approach is proposed to restrain the mentioned disturbances by using the upper bounds of disturbances. Third, an ISMO anti-disturbance strategy is established to integrate the advantages of the above two methods. It is noteworthy to point out that the proposed output observer structure could be reduced to the state case. Moreover, the diagonal constraint on Lyapunov variables is removed in this article. Finally, a numerical example is simulated to validate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This article proposes a novel membership-function dependent approach for the stability/positivity investigation and controller design of a nonlinear, discrete-time system with time delay which is represented by a polynomial fuzzy model to enhance the accuracy of the approximation. The polynomial fuzzy controller is designed based on imperfect premise matching design concept and a set of sum of square (SOS)-based conditions is formulated to check the positivity and stability of the control system. To relax the conservative SOS-based conditions, we employ piecewise Taylor series membership functions (PTSMFs) and introduce the membership function knowledge into the stability conditions. Slack matrices are used to represent the membership function and premise variable knowledge, which contains: 1) regional approximation error between PTSMFs and original membership functions; 2) regional bounds of PTSMFs; and 3) the property knowledge of interpolation membership function of PTSMFs and regional bounds of premise variables. A simulation example is finally given to verify our novel stability/positivity conditions and discrete-time polynomial fuzzy (DPF) controller design. [ABSTRACT FROM AUTHOR]

This article studies the issue of stability for complex network control systems, which comprise multisystems and multicontrollers. These systems and controllers are coupled with each other and linked by communication networks with random delays. The system and controller network topologies are subject to jump, and the dynamic is captured by two models, as: 1) dual-Markov model and 2) hidden Markov model. Correspondingly, the stability conditions based on the Lyapunov-functional method are given for closed-loop stability. Then, the stability conditions are derived by transforming into the linear matrix inequality-based constraint minimization problem for solving controller gains. An illustration is carried out to testify the validation and potentials of the proposed new design techniques. [ABSTRACT FROM AUTHOR]

This article studies the adaptive backstepping control problem for a class of fractional-order (FO) nonlinear systems subject to input quantization and unknown control directions by combining with an indirect FO Lyapunov stability method, and a command filter-based FO dynamic surface control (FODSC) technique. First, a modified FODSC method is utilized to reduce the computational complexity existing in the conventional recursive procedure in which an FO command filter is designed to obtain the command signals and their FO derivatives. Furthermore, the Nussbaum function and neuro-fuzzy networks (NFNs) are adopted to deal with the problem of the unknown control directions and unknown nonlinear functions existing in the system. Moreover, by introducing the compensation and prediction mechanism to controller design, the adaptive controllers, and adaptive laws are constructed to ensure that all the signals of the controlled systems are bounded. Finally, two examples are given to show the validity of the developed control method. [ABSTRACT FROM AUTHOR]

In this article, the $H_{\infty }$ control problem is investigated for a class of discrete-time singularly perturbed systems (DTSPSs) with time-delays and sensor saturations. In order to save the network bandwidth with satisfactory communication reliability during the signal transmissions, a dynamic event-triggered mechanism (DETM) is put forward to regulate the data-packet transmissions from the saturated sensors to the proposed controller. By constructing a novel Lyapunov–Krasovskii functional dependent on the singular perturbation parameter (SPP), the dynamics of the DTSPSs under the DETM are rigorously analyzed, and an output-feedback controller design scheme is then developed to ensure that, for any SPP not exceeding a prescribed upper bound, the closed-loop system is asymptotically stable with a guaranteed $H_{\infty }$ performance index. By resorting to the convex programming techniques, the desired controller gain is parameterized in light of the feasible solutions to a set of matrix inequalities. Finally, the effectiveness and merits of the proposed algorithm are demonstrated by a simulation example. [ABSTRACT FROM AUTHOR]

In this article, we are concerned with the input-to-state stability (ISS) problem for a class of nonlinear systems with exogenous disturbances, where the states of the system are not fully available. Based on the idea of event-triggered control (ETC) strategy, a novel event-triggered mechanism (ETM) is designed to reduce the burden of the communication and controller updating with guaranteed performance requirement. Correspondingly, an observer-based impulsive controller coupled with sample control is proposed such that the controlled system is ISS under the designed ETM. Moreover, the possible accumulations of triggered instants (i.e., Zeno behavior) in the proposed control strategy are excluded. The controller gains and ETM parameters are co-designed by solving linear matrix inequalities (LMIs). Finally, a numerical example is provided to illustrate the effectiveness of the obtained theoretical results. [ABSTRACT FROM AUTHOR]