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This brief investigates the data-driven control problem for a class of nonlinear systems. An incremental triangular dynamic linearization (ITDL) model is presented to equivalently describe these systems, and it contains three parameters including a single time-varying parameter, all of which have clear physical meanings. The ITDL model has obvious advantages compared with the existing partial form dynamic linearization (PFDL) model, although it is a special case of the PFDL model in form. An online estimation algorithm is designed for the single time-varying parameter, and then an adaptive control law is designed. The convergence and stability of the closed-loop system are analyzed, and the corresponding explicit conditions are derived. Finally, a comparative simulation study is conducted to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article addresses cooperative path-following problem of autonomous surface vehicles (ASVs) over a wireless network with constrained resources. A network-based resource-aware control architecture is presented to avoid unnecessary communications, computations, and actuations. Specifically, an event-triggered cooperative control law is designed to deal with the limited network bandwidth. Each ASV broadcasts its cooperation variable to its neighboring ASVs based on predefined event conditions under directed communication links. Then, an event-triggered path-following control law is proposed based on a line-of-sight approach. An event-triggered extended state observer is developed to estimate the uncertainties and external disturbances without periodic estimation. Finally, an event-triggered kinetic control law with aperiodic actuation is developed. The input-to-state stability of the closed-loop path-following system is analyzed by employing cascade theory, and Zeno behavior is excluded. A salient feature of the proposed network-based resource-aware control architecture is that cooperative path following can be achieved with low network traffic and reduced computation. Experiment results are given to illustrate the effectiveness of the proposed network-based resource-aware control architecture for multiple ASVs by using aperiodic communications, estimations, and executions. [ABSTRACT FROM AUTHOR]

This article deals with the problem of network-based path-tracking control of an underactuated unmanned surface vehicle subject to model uncertainties and unknown disturbances over a wireless network. A two-level network-based control architecture is proposed, including a local inner loop and a remote outer loop. In the remote outer loop, an event-triggered line-of-sight guidance law is designed to achieve path tracking while reducing the network burden for the remote control at the kinematic level. In the local inner loop, an extended state observer is employed to estimate the unknown disturbances due to the model uncertainties and environmental disturbances. Based on the estimated information from the extended state observer, an event-triggered anti-disturbance control law is developed to reduce the execution rate of actuators at the kinetic level. The stability of the closed-loop path-tracking system is proved based on the input-to-state stability and cascade stability theory. The effectiveness of the proposed network-based method for path tracking of the USV is verified via experiments. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are of potential use in wireless communication systems due to their ability to perform beam steering, harmonic wave manipulation, and polarization conversion. However, the main challenge in designing RISs is to obtain their electromagnetic (EM) responses, which is time-consuming and computationally prohibitive. In this work, an efficient modeling method is proposed for fast evaluation of the reflection coefficient and far-field patterns of RISs. The proposed method utilizes the microwave network theory to compute the accurate reflection coefficient of RISs elements under the illumination of incident waves from arbitrary directions. Compared to the classical equivalent circuit model, it enables the separate design of meta-atoms and tunable devices at the network level. The proposed method is verified by the full-wave simulation results of two RIS elements and experimental results of a 3-bit RIS. This work forms a fast and feasible route to obtain the responses of RISs, which allows the RISs to find extensive applications in many scenarios. [ABSTRACT FROM AUTHOR]

Traffic sign recognition (TSR) plays an important role in driving assistance system and traffic safety insurance. However, existing methods focus on extracting features of traffic signs and ignore the constraints of spatial positional relationships between traffic signs and other objects in the scene. This way results in incorrectly detecting other similar objects as traffic signs and failing to detect very small traffic signs. A TSR method based on semantic scene understanding and structural traffic sign location is proposed in this study to solve the aforementioned problems. A scene structure model based on the constraints of spatial positional relationships between traffic signs and other objects is proposed to establish trusted search regions. An improved Light-weight RefineNet is used to analyze and understand a scene semantically and accurately and then segment objects in complicated environments precisely. A new network multiscale densely connected object detector (MDCOD) based on densely connected style, multiscale feature fusion, and improved K-means++ algorithms is proposed to recognize very small traffic signs. The trusted traffic signs are found by filtering false candidates outside the scene structure model. The proposed method is tested on Tsinghua-Tencent 100K and German Traffic Sign Detection Benchmark datasets and achieves accuracies of 92.8% and 99.90%, respectively, outperforming the existing methods. [ABSTRACT FROM AUTHOR]

Federated learning (FL) is capable of analyzing tremendous data from smart edge devices in Industrial Internet of Things (IIoTs), empowering numerous industrial applications. However, the increasing privacy concerns and deployment costs of IIoT environment have been posing new challenges for FL. This article proposes PCFed, a novel privacy-enhanced and communication-efficient FL framework to provide higher model accuracy with rigorous privacy guarantees and great communication efficiency. In particular, we develop a sampling-based intermittent communication strategy via a PID (proportional, integral, and derivative) controller on the cloud server to adaptively reduce the communication frequency. In addition, we design a budget allocation mechanism to balance the tradeoff between model accuracy and privacy loss. Then, we develop PCFed+, an enhanced variant for PCFed, with further consideration of infinite data streams on edge servers. Extensive experiments demonstrate that both PCFed and PCFed+ can significantly outperform existing schemes, in terms of communication efficiency, privacy protection, and model accuracy. [ABSTRACT FROM AUTHOR]

This article is concerned with both consensus and coordinated path-following control for multiple nonholonomic wheeled mobile robots. In the design, the path-following control is decoupled into the longitudinal control (speed control) and the lateral control (heading control) for the convenience of implementation. Different from coordinated trajectory tracking control schemes, the proposed control scheme removes the temporal constraint, which greatly improves the coordination robustness. In particular, two new coordinated error variables describing a chasing-and-waiting strategy are introduced in the proposed coordinated path-following control for injective paths and circular paths, respectively. All the closed-loop signals have proved to be asymptotically stable in the Lyapunov sense. Finally, simulation results under three typical paths are presented to verify the proposed coordination controllers. [ABSTRACT FROM AUTHOR]

In this article, a frequency-domain approach is developed to deal with the global consensus problem for a class of general second-order multiagent systems (MASs) subject to actuator saturations. By employing the describing function and the generalized Nyquist criterion, the global consensus problem is thoroughly investigated for both undirected and directed topologies. First, the describing function is introduced to characterize the actuator saturations in the $s$ -plane, and the inherent representation error is quantitatively analyzed from a frequency-domain perspective. Then, by means of the Kronecker product, the addressed consensus problem of the MAS is transformed into a corresponding stability analysis problem for a certain multi-input–multi-output (MIMO) system and, consequently, the generalized Nyquist criterion for MIMO systems is exploited to derive the condition for the global consensus of the MAS where the impact from the actuator saturation is explicitly reflected. Finally, numerical simulations are provided to illustrate the validity of the proposed theoretical result. [ABSTRACT FROM AUTHOR]

This article deals with the proportional–integral observer (PIO) design problem for a class of linear systems with distributed time delays and randomly occurring parameter uncertainties. The measurement signals, transmitted from the sensors to the observer, might suffer from the randomly occurring deception attacks. The random occurrences of parameter uncertainties and deception attacks are governed by two series of Bernoulli random variables with known probability distributions. An outlier-resistant PIO is developed by introducing an innovation saturation mechanism for the sake of alleviating the adverse effects induced by the deception attacks on the estimation performance. The purpose of the addressed problem is to design a PIO that is capable of guaranteeing the mean-square boundedness of the estimation errors while achieving the desired security level. The desired PIO gain is designed by solving a matrix inequality and the validity of the results obtained is shown by a numerical simulation example. [ABSTRACT FROM AUTHOR]

This article demonstrates that nonmaximum suppression (NMS), which is commonly used in object detection (OD) tasks to filter redundant detection results, is no longer secure. Considering that NMS has been an integral part of OD systems, thwarting the functionality of NMS can result in unexpected or even lethal consequences for such systems. In this article, an adversarial example attack that triggers malfunctioning of NMS in OD models is proposed. The attack, namely, Daedalus, compresses the dimensions of detection boxes to evade NMS. As a result, the final detection output contains extremely dense false positives. This can be fatal for many OD applications, such as autonomous vehicles and surveillance systems. The attack can be generalized to different OD models, such that the attack cripples various OD applications. Furthermore, a way of crafting robust adversarial examples is developed by using an ensemble of popular detection models as the substitutes. Considering the pervasive nature of model reuse in real-world OD scenarios, Daedalus examples crafted based on an ensemble of substitutes can launch attacks without knowing the parameters of the victim models. The experimental results demonstrate that the attack effectively stops NMS from filtering redundant bounding boxes. As the evaluation results suggest, Daedalus increases the false positive rate in detection results to 99.9% and reduces the mean average precision scores to 0, while maintaining a low cost of distortion on the original inputs. It also demonstrates that the attack can be practically launched against real-world OD systems via printed posters. [ABSTRACT FROM AUTHOR]

This article addresses the cooperative target enclosing problem of ring-networked underactuated autonomous surface vehicles (ASVs). The target velocity is unavailable, and the ASVs are subject to sideslip effects, unknown control gains, and uncertain kinetics. The control objective is to drive a fleet of ASVs to surround a moving target at a desired range and maintain a spaced formation. An integrated distributed guidance and model-free control method is presented based on extended state observers (ESOs) and a data-driven fuzzy predictor. Specifically, by using two ESOs to estimate the unknown relative kinematics induced by the unknown target velocity and unknown sideslip and a distributed target estimator to recover the target position, intermediate range keeping and phase keeping guidance laws are designed to achieve a circular motion and an evenly spaced formation, respectively. Next, a model-free fuzzy control law is developed based on a data-driven fuzzy predictor, which learns the unknown control gains and uncertain kinetics simultaneously. Finally, the closed-loop control system is proven to be input-to-state stable through Lyapunov analysis. The salient feature of the proposed method is that cooperative circumnavigating a maneuvering target with unknown velocity can be achieved without the global target information and knowledge of vehicle kinetics. Simulation results validate the effectiveness of the proposed distributed guidance and control method for cooperative target enclosing of ASVs. [ABSTRACT FROM AUTHOR]

In this article, the problem of consensus control is investigated for a class of multiagent systems (MASs) with both stochastic noises and nonidentical exogenous disturbances. The signal transmission among agents is implemented through a digital communication network subject to both uniform quantization and round-robin protocol as a reflection of network constraints. The consensus strategy is designed by adopting the estimates of the relative states of the agent to its neighbors, which renders the distributed nature of the controller. A new consensus concept, namely, quasiconsensus in probability, is employed to evaluate the state response of the agents to the stochastic noises, the exogenous disturbances, and the quantization error. An augmented system is first formed that relies on the deviations of the individual state from the average state, the observer error of the relative state, as well as the relative measurement output. Based on the augmented model, an analysis approach on dynamical behaviors is developed to facilitate the consensus analysis of MASs by means of the switching Lyapunov function technique and the stochastic analysis methods. Then, the existence condition and the explicit expression of the time-varying gain matrices are proposed for the expected controller by resorting to the feasibility of several matrix inequalities. Numerical simulation results are presented to demonstrate the applicability of the theoretical results. [ABSTRACT FROM AUTHOR]

Building energy management systems (BEMSs) have been successfully adopted as key control units for modern structures to maintain energy efficiency and provide a comfortable thermal environment for occupants. Recent advances in information and communication technology toward “Industry 4.0” are enhancing the utility of BEMSs. However, challenges, such as how to process the exponentially growing amount of heterogeneous data generated in buildings, need to be addressed to realize “Building 4.0,” which encompasses next-generation smart systems that provide user-centric services. In this article, we propose BEMS–Edge, a framework that integrates seamless, real-time information acquisition, transmission, interpretation, and action in intelligent BEMSs. The primary components, including the Internet of Things (IoT), cloud/edge computing, big data analytics, and artificial intelligence (AI), converge to create a data-driven edge computing fabric offering a range of benefits, such as real-time data analytics and cost savings. The effectiveness of BEMS–Edge is verified by an established, real-world BEMS testbed. [ABSTRACT FROM AUTHOR]

This article is concerned with the problem of recursive state estimation for a class of multirate multisensor systems with distributed time delays under the round-robin (R-R) protocol. The state updating period of the system and the sampling period of the sensors are allowed to be different so as to reflect the engineering practice. An iterative method is presented to transform the multirate system into a single-rate one, thereby facilitating the system analysis. The R-R protocol is introduced to determine the transmission sequence of sensors with the aim to alleviate undesirable data collisions. Under the R-R protocol scheduling, only one sensor can get access to transmit its measurement at each sampling time instant. The main purpose of this article is to develop a recursive state estimation scheme such that an upper bound on the estimation error covariance is guaranteed and then locally minimized through adequately designing the estimator parameter. Finally, simulation examples are provided to show the effectiveness of the proposed estimator design scheme. [ABSTRACT FROM AUTHOR]

This article focuses on the distributed maximum correntropy filtering issue for general stochastic nonlinear systems subject to deception attacks. The considered nonlinear functions consist of a determined one and a stochastic one, and the stochastic signals sent by deception attacks with identified statistic characteristics could be non-Gaussian. The corresponding calculation formulas of both the filter gains and the upper bound of the filter error covariance are proposed by means of the Taylor series expansion and the fixed-point iterative update rule, where the weighted maximum correntropy criterion is utilized to take the place of traditional minimum covariance indexes. Such an upper bound is only dependent on the local information, neighbor information, and the identified statistics of deception attacks and, therefore, the developed filtering scheme realizes the requirement of distributed calculation. Furthermore, a simplified version is obtained by removing weights in the correntropy criterion. Finally, an illustrative example is given to verify the effectiveness of developed distributed maximum correntropy filtering subject to deception attacks. [ABSTRACT FROM AUTHOR]

This article is concerned with event-triggered dynamic positioning for a mass-switched unmanned marine vehicle (UMV) in network environments. First, a switched dynamic positioning system (DPS) model for a mass-switched marine vehicle is established. The switched DPS model takes into consideration changes in the marine vehicle’s mass and the resultant switching of the marine vehicle’s parameters. Second, for a mass-switched UMV controlled through a communication network, a novel weighted event-triggering communication scheme considering switching features is proposed. The weighted error data of multiple sampling instants are utilized to avoid a long-time nontriggering phenomenon. The consideration of switching features guarantees the current sampled data to be transmitted if a switch occurs between the last sampling instant and the current sampling instant. Then, under the event-triggering scheme, an asynchronously switched DPS model for the mass-switched UMV is established in network environments. Based on this model, a mode-dependent DPS controller and event generator co-design method are proposed to attenuate the disturbance induced by wind, waves, and ocean currents. The DPS performance analysis demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of distributed cooperative longitudinal control of automated vehicle platoons subject to a variety of uncertainties, including unknown engine time lags, external disturbances, measurement noises, and actuator anomaly in follower vehicles as well as unknown leader control. First, a unified framework is proposed for accomplishing resilient vehicle platooning, which empowers longitudinal vehicle state estimation, anomaly signal estimation and compensation, and adaptive platoon controller design to be addressed in a comprehensive way. Second, a novel scalable platooning control design approach is developed to guarantee desired platoon stability and resilience over generic communication topologies and various spacing policies. A salient feature of the approach is that the design procedure does not depend on any global information of the associated topology, and thus preserves essential scalability for large and/or size-varying platoons. Third, it is shown that the proposed longitudinal platooning control approach is promising for performing flexible cooperative maneuvers such as platoon splitting and merging that are beyond the capacity of most existing longitudinal platooning strategies. Finally, simulation results for different platoon maneuvers are elaborated to substantiate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

This article addresses the problem of synchronization of impulsive networks with switching topologies. A new synchronization framework is established with an emphasis on settling time estimation. The impulsive networks consist of physical nodes and cyber modules. For physical nodes, states are changed impulsively at discrete time instants due to some switching phenomena or unexpected sudden noises. For cyber modules, two cases of switching scenarios are considered for information exchange patterns during specific time intervals. In the first case, cyber modules lose all the communication links with others, resulting in disconnected topologies. Then, a distributed controller is proposed for nodes without intrinsic nonlinear dynamics. A distinguished feature of this controller is its capability to estimate a bound for settling time, beyond which the synchronization with respect to a virtual target is guaranteed. In the second case, cyber modules lose some communication links but build other new ones with the help of a smart communication center to form connected topologies. A distributed controller is further designed for nodes in the presence of intrinsic nonlinear dynamics. Accordingly, a sufficient condition is derived to achieve synchronization with an estimated settling time bound. For both cases, the estimated bounds are able to reveal the relationship between the impulsive strength and the synchronization performance. Finally, numerical examples including a case study on a modified IEEE 34 bus test feeder are provided to demonstrate the effectiveness of the proposed controllers. [ABSTRACT FROM AUTHOR]

This article is concerned with the consensus control problem for a general class of linear multiagent systems (MASs) subject to actuator imperfection consisting of both actuator saturations and actuator faults. A novel two-step saturation-resistant approach is proposed to attenuate the side effects resulting from the actuator imperfection. In the first step of controller design, the state information received from the neighboring agents is used to design a consensus controller capable of tolerating the actuator fault. Then, in the second step of controller optimization, the domain of attraction (DOA) is introduced for MASs to evaluate the performance of the controller and, subsequently, optimize the controller parameters to enlarge the DOA in terms of solutions to a certain set of matrix inequalities. Finally, simulation examples are provided to demonstrate the effectiveness of the developed saturation-resistant approach. [ABSTRACT FROM AUTHOR]

This article deals with the problem of electromagnetic source localization (ESL). An evolutionary particle filter, which is first used to make a decision on the positions of electromagnetic sources, has two characteristics. One characteristic is that the number of particles can be significantly reduced while the other characteristic is that the particle diversity can be well improved. On the basis of the estimated positions of electromagnetic sources, the position and velocity of the virtual leader can be determined. Then, an event-based fixed-time consensus control approach is proposed such that the positions and velocities of robots reach consensus with the virtual leader over a fixed-time interval while saving resource consumption by reducing the communication frequencies and updating times of control inputs. Finally, simulation and experimental results show the effectiveness of the proposed decision and event-based fixed-time consensus control approach for ESL. [ABSTRACT FROM AUTHOR]

This brief is concerned with the time-varying formation problem for second-order networked multi-agent systems, which are subject to random communication delays and packet dropouts in the sensor-to-controller and controller-to-actuator channels of each agent. A cloud-based time-varying formation predictive control method with control input quantization is proposed to actively compensate for those random communication constraints. A definition of quantized time-varying formation is given, and then a necessary and sufficient condition to achieve the quantized time-varying formation as well as the stability of the resulting closed-loop system is obtained, which is independent of random communication constraints and quantization errors. Simulation results are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article is concerned with set-membership global estimation for a networked system under unknown-but-bounded process and measurement noises. First, a group of local set-membership estimators is deployed to obtain the local ellipsoidal estimate of the true system state. Each estimator is capable of communicating with its neighbors within its communication range. Second, a global estimation approach is proposed which generates a trace-maximal ellipsoid within the intersection of all the local estimation sets with an aim to improve the difference of the local estimate at each time instant. Sufficient conditions for providing a global estimate under both complete and incomplete measurement transmissions are derived. Third, as an application, a modified distributed photovoltaic grid-connected generation system is provided to verify the effectiveness of the developed set-membership global estimation approach. Furthermore, an islanding fault detection scheme is derived based on the calculated global ellipsoidal estimate. Finally, simulation verification of the obtained theoretical results on the distributed generation system is presented. [ABSTRACT FROM AUTHOR]

Most of the existing localization schemes necessitate a priori statistical characteristic of measurement noise, which may be unrealistic in practical applications. This article addresses the problem of indoor localization by implementing distributed set-membership filtering based on a received signal strength indicator (RSSI) under unknown-but-bounded process and measurement noises. First, the transmit power and the path-loss exponent are estimated by a novel least-squares curve fitting (LSCF) method in RSSI-based localization. Since the localization process of trilateration is susceptible to inaccuracy caused by the noise-affected distance measurements, a convex optimization method is then developed to obtain the state ellipsoid estimation under the unknown-but-bounded noises. Third, a recursive algorithm is established to compute the global ellipsoid that guarantees to locate the true target at every time step. Finally, experimental validation is presented to demonstrate the accuracy and effectiveness of the proposed set-membership filtering method for indoor localization. [ABSTRACT FROM AUTHOR]

This brief concerns the problem of false data injection (FDI) attacks against partial sensor measurements of a networked stochastic system. For a Kalman filter based output tracking control system with a residual-based anomaly detector, a partial FDI attack strategy is presented to deteriorate the system performance by injecting false signals into the feedback communication channel to tamper partial sensor measurements. The stealthiness condition of the attack as well as its impact on the closed-loop system is derived, which are quite different from those of the FDI attack against all sensor measurements given in the existing work. This may be helpful for guaranteeing the secure control of a networked system by protecting partial critical sensor measurements from FDI attacks. Two numerical examples are included to verify the theoretical results. [ABSTRACT FROM AUTHOR]

The main purpose of this article is to investigate the consensus of linear multiagent networks with time-varying characteristics under sampled-data communications, where the time-varying characteristics include both time-varying topologies and the node’s linear time-varying dynamics. By using the decoupling method, we prove that the sampled-data consensus problem of multiagent networks is equal to the stability problem of sampled-data systems. Then, the globally asymptotical consensus is investigated for multiagent networks with time-varying characteristics by virtue of the Lyapunov function method. It should be noted that when the Lyapunov function method is utilized to investigate the stability problem of control systems, it is always assumed that the derivative of the constructed Lyapunov function is not more than zero. This assumption is removed here and as a replacement, the average value of the derivative of the Lyapunov function in a period to be negative is needed. [ABSTRACT FROM AUTHOR]

This article investigates the problem of finite-time consensus tracking for incommensurate fractional-order nonlinear multiagent systems (MASs) with general directed switching topology. For the leader with bounded but arbitrary dynamics, a neighborhood-based saturated observer is first designed to guarantee that the observer’s state converges to the leader’s state in finite time. By utilizing a fuzzy-logic system to approximate the heterogeneous and unmodeled nonlinear dynamics, an observer-based adaptive parameter control protocol is designed to solve the problem of finite-time consensus tracking of incommensurate fractional-order nonlinear MASs on directed switching topology with a restricted dwell time. Then, the derived result is further extended to the case of directed switching topology without a restricted dwell time by designing an observer-based adaptive gain control protocol. By artfully choosing a piecewise Lyapunov function, it is shown that the consensus tracking error converges to a small adjustable residual set in finite time for both the cases with and without a restricted dwell time. It should be noted that the proposed adaptive gain consensus tracking protocol is completely distributed in the sense that there is no need for any global information. The effectiveness of the proposed consensus tracking scheme is illustrated by numerical simulations. [ABSTRACT FROM AUTHOR]

The rapid development of artificial intelligence, especially deep learning technology, has advanced autonomous driving systems (ADSs) by providing precise control decisions to counterpart almost any driving event, spanning from antifatigue safe driving to intelligent route planning. However, ADSs are still plagued by increasing threats from different attacks, which could be categorized into physical attacks, cyberattacks and learning-based adversarial attacks. Inevitably, the safety and security of deep learning-based autonomous driving are severely challenged by these attacks, from which the countermeasures should be analyzed and studied comprehensively to mitigate all potential risks. This survey provides a thorough analysis of different attacks that may jeopardize ADSs, as well as the corresponding state-of-the-art defense mechanisms. The analysis is unrolled by taking an in-depth overview of each step in the ADS workflow, covering adversarial attacks for various deep learning models and attacks in both physical and cyber context. Furthermore, some promising research directions are suggested in order to improve deep learning-based autonomous driving safety, including model robustness training, model testing and verification, and anomaly detection based on cloud/edge servers. [ABSTRACT FROM AUTHOR]

This article is concerned with the $H_{\infty }$ cluster formation control of a multiagent system (MAS) with stochastic sampling in network environments. First, based on a directed communication topology with acyclic partition, agents are separated into several clusters. The agents moving in the same cluster are expected to achieve a desired formation collaboratively, while the agents in different clusters have different formation patterns. Second, the external disturbance for each agent is taken into account. The associated $H_{\infty }$ cluster formation control, whose performance bound can be obtained by considering both formation information and cluster characteristics, is introduced to measure the disturbance attenuation ability. Third, by casting a stochastic sampled-data-based $H_{\infty }$ cluster formation problem into an $H_{\infty }$ control problem of a stochastic system, an $H_{\infty }$ cluster formation criterion is derived for the MAS with external disturbance. Finally, a lower-dimensional cluster formation criterion is obtained for the disturbance-free MAS. Cluster formation performance analysis testifies the effectiveness of the proposed design methods. [ABSTRACT FROM AUTHOR]