Showing papers by "Peng Shi published in 2020"
TL;DR: In this paper, the consensus tracking problem is investigated for a class of continuous switched stochastic nonlinear multiagent systems with an event-triggered control strategy and a new protocol design framework is proposed for the underlying systems.
Abstract: In this paper, the consensus tracking problem is investigated for a class of continuous switched stochastic nonlinear multiagent systems with an event-triggered control strategy. For continuous stochastic multiagent systems via event-triggered protocols, it is rather difficult to avoid the Zeno behavior by the existing methods. Thus, we propose a new protocol design framework for the underlying systems. It is proven that follower agents can almost surely track the given leader signal with bounded errors and no agent exhibits the Zeno behavior by the given control scheme. Finally, two numerical examples are given to illustrate the effectiveness and advantages of the new design techniques.
223 citations
TL;DR: A novel adaptive protocol is proposed for the switched nonlinear MASs based on the developed design framework and the neural network method and a numerical example is presented to demonstrate the effectiveness of the proposed control scheme.
Abstract: In this brief, the practical finite-time consensus (FTC) problem is investigated for the second-order heterogeneous switched nonlinear multi-agent systems (MASs), where the subsystems and the switching signal for each agent are different. Mainly due to that agents’ dynamics are switched and the unknown nonlinearities in the systems are more general, the practical FTC problem of the MASs is rather difficult to be solved by existing methods. As such, a new protocol design framework for the FTC problem is developed. Then, a novel adaptive protocol is proposed for the switched nonlinear MASs based on the developed design framework and the neural network method. The sufficient conditions for the practical FTC of nonlinear MASs under arbitrary switching are given. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed control scheme.
189 citations
TL;DR: A sustainable SEI was designed rationally by combining fluorinated co-solvents with sustained-release additives in response to challenges from practical conditions, affords a fresh guidance to the design principles of SEI in practical Li metal batteries.
Abstract: High-energy-density Li metal batteries suffer from a short lifespan under practical conditions, such as limited lithium, high loading cathode, and lean electrolytes, owing to the absence of appropriate solid electrolyte interphase (SEI). Herein, a sustainable SEI was designed rationally by combining fluorinated co-solvents with sustained-release additives for practical challenges. The intrinsic uniformity of SEI and the constant supplements of building blocks of SEI jointly afford to sustainable SEI. Specific spatial distributions and abundant heterogeneous grain boundaries of LiF, LiNx Oy , and Li2 O effectively regulate uniformity of Li deposition. In a Li metal battery with an ultrathin Li anode (33 μm), a high-loading LiNi0.5 Co0.2 Mn0.3 O2 cathode (4.4 mAh cm-2 ), and lean electrolytes (6.1 g Ah-1 ), 83 % of initial capacity retains after 150 cycles. A pouch cell (3.5 Ah) demonstrated a specific energy of 340 Wh kg-1 for 60 cycles with lean electrolytes (2.3 g Ah-1 ).
182 citations
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TL;DR: A complete survey of studies on the application of DL techniques for COVID-19 diagnostic and automated segmentation of lungs is discussed, concentrating on works that used X-Ray and CT images.
Abstract: Coronavirus, or COVID-19, is a hazardous disease that has endangered the health of many people around the world by directly affecting the lungs. COVID-19 is a medium-sized, coated virus with a single-stranded RNA. This virus has one of the largest RNA genomes and is approximately 120 nm. The X-Ray and computed tomography (CT) imaging modalities are widely used to obtain a fast and accurate medical diagnosis. Identifying COVID-19 from these medical images is extremely challenging as it is time-consuming, demanding, and prone to human errors. Hence, artificial intelligence (AI) methodologies can be used to obtain consistent high performance. Among the AI methodologies, deep learning (DL) networks have gained much popularity compared to traditional machine learning (ML) methods. Unlike ML techniques, all stages of feature extraction, feature selection, and classification are accomplished automatically in DL models. In this paper, a complete survey of studies on the application of DL techniques for COVID-19 diagnostic and automated segmentation of lungs is discussed, concentrating on works that used X-Ray and CT images. Additionally, a review of papers on the forecasting of coronavirus prevalence in different parts of the world with DL techniques is presented. Lastly, the challenges faced in the automated detection of COVID-19 using DL techniques and directions for future research are discussed.
156 citations
TL;DR: A command filtered adaptive neural networks (NNs) control method is presented with regard to the MIMO systems by designing the virtual controllers and error compensation signals to conquer the shortcoming of the dynamic surface method.
Abstract: In this paper, the tracking control problem is considered for a class of multiple-input multiple-output (MIMO) nonlinear systems with input saturation and unknown direction control gains. A command filtered adaptive neural networks (NNs) control method is presented with regard to the MIMO systems by designing the virtual controllers and error compensation signals. First, the command filtering is used to solve the “explosion of complexity” problem in the conventional backstepping design and the nonlinearities are approximated by NNs. Then, the error compensation signals are developed to conquer the shortcoming of the dynamic surface method. In addition, the Nussbaum-type functions are utilized to cope with the unknown direction control gains. The effectiveness of the proposed new design scheme is illustrated by simulation examples.
132 citations
TL;DR: The problem of input-to-state stability (ISS) is systematically investigated for nonlinear systems with stochastic impulses and an example of coordination of multi-agent systems is provided to illustrate the effectiveness of the proposed new stability criteria.
123 citations
118 citations
TL;DR: Sufficient conditions are developed to guarantee the existence of the reliable SOF controller against actuator faults, and an iterative algorithm is designed to determine the controller gains, which avoids the conservatism brought by the traditional singular value decomposition method.
Abstract: This paper is focused on the static output feedback (SOF) control problem for a class of switched nonlinear systems with actuator faults. By means of the Takagi–Sugeno fuzzy model, the switched nonlinear plant is described by a family of switched fuzzy systems. Considering transmission failures may occur between controller and actuator, a reliable SOF controller against actuator faults is designed. Sufficient conditions are developed to guarantee the existence of the reliable SOF controller. Furthermore, an iterative algorithm is designed to determine the controller gains, which avoids the conservatism brought by the traditional singular value decomposition method. To validate the effectiveness of the proposed approach, a numerical example is exploited and simulation results are also presented.
118 citations
TL;DR: The cooperative control problem of nonlinear multiagent systems is studied and based on the Lyapunov stability theory and algebraic graph theory, the stability analysis of the resulting closed-loop system is provided.
Abstract: The cooperative control problem of nonlinear multiagent systems is studied in this paper. The followers in the communication network are subject to unmodeled dynamics. A fully distributed neural-networks-based adaptive control strategy is designed to guarantee that all the followers are asymptotically synchronized to the leader, and the synchronization errors are within a prescribed level, where some global information, such as minimum and maximum singular value of graph adjacency matrix, is not necessarily to be known. Based on the Lyapunov stability theory and algebraic graph theory, the stability analysis of the resulting closed-loop system is provided. Finally, an numerical example illustrates the effectiveness and potential of the proposed new design techniques.
113 citations
TL;DR: Understanding the initiation, progression, and resolution of inflammation will provide insights into the mechanisms of scar formation and is useful for developing effective treatments for suppressing inflammation and limiting progression to scar.
Abstract: The underlying mechanisms of wound healing are complex but inflammation is one of the determining factors. Besides its traditional role in combating against infection upon injury, the characteristics and magnitude of inflammation have dramatic impacts on the pathogenesis of scar. Keloids and hypertrophic scars are pathological scars that result from aberrant wound healing. They are characterized by continuous local inflammation and excessive collagen deposition. In this review, we aim at discussing how dysregulated inflammation contributes to the pathogenesis of scar formation. Immune cells, soluble inflammatory mediators, and the related intracellular signal transduction pathways are our three subtopics encompassing the events occurring in inflammation associated with scar formation. In the end, we enumerate the current and potential medicines and therapeutics for suppressing inflammation and limiting progression to scar. Understanding the initiation, progression, and resolution of inflammation will provide insights into the mechanisms of scar formation and is useful for developing effective treatments.
108 citations
TL;DR: This paper studies the problem of event-triggered secure consensus for multiagent systems subject to periodic energy-limited denial-of-service (DoS) attacks, where DoS attacks usually prevent agent-to-agent data transmission.
Abstract: This paper studies the problem of event-triggered secure consensus for multiagent systems subject to periodic energy-limited denial-of-service (DoS) attacks, where DoS attacks usually prevent agent-to-agent data transmission. The DoS attacks are assumed to occur periodically based on the time-sequence way and the period of DoS attacks and the uniform lower bound of the communication areas are predetected by some devices. Based on the above assumptions, an event-based protocol consisting of two different measurements corresponding to leader–followers and follower–follower is presented to schedule communications between agents, which can reduce the update frequency of the controller. Then, the stability of the resultant error system is analyzed to derive sufficient conditions of achieving secure consensus by employing the Lyapunov function and the inductive approach. Besides, positive low bounds on any two consecutive intervals of events generated by individual events are calculated to eliminate “Zeno behavior” under the developed triggering condition and event-triggered protocol. Simulation result is provided to verify the theoretical analysis.
TL;DR: This work provokes the vital insights into the role of the organic components of SEI in the protection of the Li anode in practical Li-S batteries by employing 3,5-bis(trifluoromethyl)thiophenol as an electrolyte additive.
Abstract: The lithium-sulfur (Li-S) battery is regarded as a promising high-energy-density battery system, in which the dissolution-precipitation redox reactions of the S cathode are critical. However, soluble Li polysulfides (LiPSs), as the indispensable intermediates, easily diffuse to the Li anode and react with the Li metal severely, thus depleting the active materials and inducing the rapid failure of the battery, especially under practical conditions. Herein, an organosulfur-containing solid electrolyte interphase (SEI) is tailored for the stabilizaiton of the Li anode in Li-S batteries by employing 3,5-bis(trifluoromethyl)thiophenol as an electrolyte additive. The organosulfur-containing SEI protects the Li anode from the detrimental reactions with LiPSs and decreases its corrosion. Under practical conditions with a high-loading S cathode (4.5 mgS cm-2 ), a low electrolyte/S ratio (5.0 µL mgS -1 ), and an ultrathin Li anode (50 µm), a Li-S battery delivers 82 cycles with an organosulfur-containing SEI in comparison to 42 cycles with a routine SEI. This work provokes the vital insights into the role of the organic components of SEI in the protection of the Li anode in practical Li-S batteries.
TL;DR: The problem of sliding mode observer design is investigated for a class of repeated scalar nonlinear systems via dynamic event-triggered approach and an event- triggered controller is designed to ensure that the closed-loop system trajectories are restricted to the pre-specified sliding region.
TL;DR: This paper is concerned with the problem of asynchronous and reliable filter design with performance constraint for nonlinear Markovian jump systems which are modeled as a kind of Takagi–Sugeno fuzzy switched systems.
Abstract: This paper is concerned with the problem of asynchronous and reliable filter design with performance constraint for nonlinear Markovian jump systems which are modeled as a kind of Takagi–Sugeno fuzzy switched systems. The nonstationary Markov chain is adopted to represent the asynchronous situation between the designed filter and the considered system. By using the mode-dependent Lyapunov function approach and the relaxation matrix technique, a sufficient condition is proposed to ensure the filtering error system, which is a dual randomly switched system, is stochastically stable and satisfies a given ${{l}_{{2}}}{{-}}{{l}_{{\infty }}}$ performance index simultaneously. Two different approaches are developed to construct the asynchronous and reliable filter. Owing to the Finsler’s lemma, the second approach has fewer decision variables and less conservatism than the first one. Finally, two examples are provided to show the correctness and effectiveness of the proposed methods.
TL;DR: A novel distributed fault-tolerant controller is developed and an auxiliary variable is introduced in the distributed estimation algorithm to construct a data matrix, which is used to learn the system matrix of the exosystem for each subsystem.
Abstract: In this article, a new distributed learning control approach is proposed to address the cooperative fault-tolerant output regulation problem for linear multiagent systems with actuator faults. First, a distributed estimation algorithm with an online learning mechanism is presented to identify the system matrix of the exosystem and to estimate the state of the exosystem. In particular, an auxiliary variable is introduced in the distributed estimation algorithm to construct a data matrix, which is used to learn the system matrix of the exosystem for each subsystem. In addition, by resetting the state of the estimator and by using the identified matrix to update the estimator, all subsystems can reconstruct the state of the exosystem at an initial period of time, which is used for the neighbor subsystem to learn the system matrix of the exosystem. Based on the designed estimator, a novel distributed fault-tolerant controller is developed. Compared with the existing cooperative output regulation results, the system matrix of the exosystem considered in this article is unknown for all subsystems. Finally, a simulation example is provided to show the effectiveness of the obtained new design techniques.
TL;DR: A neural-network-adaptive technology is proposed for MIMO systems with input backlash via FT convergence and it is shown that desired tracking performance can be implemented in finite time.
Abstract: This article considers the problem of finite-time (FT) tracking control for a class of uncertain multi-input-multioutput (MIMO) nonlinear systems with input backlash. A modified FT command filter is designed in each step of backstepping, which ensures the output of the filter can faster approximate the derivatives of virtual signals, suppress chattering, and relax the input signal limit of the Levant differentiator. Then, the corresponding improved FT error compensation mechanism is adopted to reduce the negative impact of filtering errors. Furthermore, a neural-network-adaptive technology is proposed for MIMO systems with input backlash via FT convergence. It is shown that desired tracking performance can be implemented in finite time. The simulation example is presented to illustrate the effectiveness and advantages of the new design method.
TL;DR: This paper design Kalman-like estimators in a recursive form for networked linear stochastic systems by means of the innovation analysis approach and orthogonal projection principle, and verifies the effectiveness and superiority of the designed algorithm.
Abstract: This paper concentrates on the linear least mean square (LLMS) filtered and smoothed estimators for networked linear stochastic systems. Multiple packet losses, Markovian communication constraints, and superposed process noise are considered simultaneously. In order to reduce the channel load during communication, at every step, just one transmission node is permitted to send data packets. Hence, a Markovian communication protocol is utilized to arrange the packets of these transmission nodes. Moreover, multiple data packet dropouts occur during transmission due to an imperfect communication channel. Therefore, the global observation information cannot be obtained by the state estimator. The real state of Markov chain is assumed to be unknown to the estimator except the transition probability matrix. By means of the innovation analysis approach and orthogonal projection principle, we design Kalman-like estimators in a recursive form. Finally, through simulation experiments, we verify the effectiveness and superiority of the designed algorithm.
TL;DR: In this paper, the authors proposed a method for the use of green chemical reaction engineering and technology at the Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing 10 0 081, China.
TL;DR: The problem of asynchronous output feedback control is investigated for a class of Takagi–Sugeno fuzzy switched systems subject to intermittent measurements and sufficient conditions for the existence of an asynchronous controller are proposed, which ensure the stochastic stability of the closed-loop system with desired extended dissipative performance.
Abstract: In this paper, the problem of asynchronous output feedback control is investigated for a class of Takagi–Sugeno fuzzy switched systems subject to intermittent measurements. The Bernoulli process is employed to model the phenomenon of stochastic intermittent measurements. Based on the hidden Markov model and output measurements, an asynchronous controller is designed. Then, sufficient conditions for the existence of an asynchronous controller are proposed, which ensure the stochastic stability of the closed-loop system with desired extended dissipative performance. Finally, an example is presented to illustrate the effectiveness and advantages of the proposed new design techniques.
TL;DR: A robust adaptive control algorithm is developed to deal with the system uncertainties and to provide a smooth estimation of delayed reference signals and generates chattering-free torques which is one of the practical considerations for robotic applications.
Abstract: This paper proposes a robust adaptive algorithm that effectively copes with time-varying delay and uncertainties in Internet-based teleoperation systems. Time-delay induced by the communication network, as a major problem in teleoperation systems, along with uncertainties in modeling of robotic manipulators and remote environment warn the stability and performance of the system. A robust adaptive control algorithm is developed to deal with the system uncertainties and to provide a smooth estimation of delayed reference signals. The proposed control algorithm generates chattering-free torques which is one of the practical considerations for robotic applications. In addition, the achieved input-to-state stability gains do not necessarily require high gain control torques to retain the system’s stability. Experimental simulation studies validate the effectiveness of the proposed control strategy on a teleoperation system consisting of a Phantom Omni Haptic device and SimMechanics model of the industrial manipulator UR10. The validation of the proposed control methodology was executed through a real-time Internet-based communication established over 4G mobile networks between Australia and Scotland.
TL;DR: This paper investigates the event-triggered dissipative filtering issue for discrete-time singular neural networks with time-varying delays and Markovian jump parameters by employing filter equivalent technique, codesigned filter gains, and event- triggered matrices to make sure that the augmented SJNN model is SASSD.
Abstract: This paper investigates the event-triggered dissipative filtering issue for discrete-time singular neural networks with time-varying delays and Markovian jump parameters. Via event-triggered communication technique, a singular jump neural network (SJNN) model of network-induced delays is first given, and sufficient criteria are then provided to guarantee that the resulting augmented SJNN is stochastically admissible and strictly stochastically dissipative (SASSD) with respect to $(\mathcal {X}_{\iota },\mathcal {Y}_{\iota },\mathcal {Z}_{\iota },\delta)$ by using slack matrix scheme. Furthermore, employing filter equivalent technique, codesigned filter gains, and event-triggered matrices are derived to make sure that the augmented SJNN model is SASSD with respect to $(\mathcal {X}_{\iota },\mathcal {Y}_{\iota },\mathcal {Z}_{\iota },\delta)$ . An example is also given to illustrate the effectiveness of the proposed method.
TL;DR: A novel event-triggered fixed-time distributed observer and a novel fixed- time controller are presented, which can reduce frequency of communication and control update, avoid continuous monitor, exclude zeno behavior, eliminate the effect of mismatched disturbance caused by observation error, and achieve practicalFixed-time output consensus tracking of high-order MAS under directed interaction graphs.
Abstract: This article investigates the problem of fixed-time event-triggered output consensus tracking for high-order multiagent systems (MASs) under directed interaction graphs. First, a fixed-time event-triggered distributed observer and triggering functions are proposed. Next, fixed-time convergence of the presented distributed observer is proved by the Lyapunov function approach, and an analysis is conducted to show the proposed distributed observer excludes zeno behavior. Then, an event-triggered adaptive dynamic surface fixed-time controller is designed to stabilize the tracking error system. Finally, simulation results are given to show the effectiveness and superiority of the consensus scheme developed. The contribution of this article is to present a novel event-triggered fixed-time distributed observer and a novel fixed-time controller, which can reduce frequency of communication and control update, avoid continuous monitor, exclude zeno behavior, eliminate the effect of mismatched disturbance caused by observation error, and achieve practical fixed-time output consensus tracking of high-order MAS under directed interaction graphs.
TL;DR: An energy management scheme in fuel cell vehicle systems is designed by using optimal control principle to reduce hydrogen consumption while maintaining battery state of charge under practical operating constraints and uncertain future power demand.
TL;DR: In this paper, a quasi-time-dependent Lyapunov function was proposed for switched Takagi-Sugeno (T-S) fuzzy systems with asynchronous switching between subsystems and candidate filters.
Abstract: In this paper, asynchronous $\mathcal {H}_{\infty }$ 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 $\ell _{2}$ -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 $\mathcal {H}_{\infty }$ performance. At last, an illustrative example is provided to demonstrate the potentials and advantages of the proposed filtering scheme.
TL;DR: Based on sensors’ own measurements and their neighbors’ local information, a novel distributed estimation model against two-channel stochastic attacks is presented and the distributed estimator gains are designed by solving a linear matrix inequality.
Abstract: This paper is concerned with the distributed estimation problem in sensor networks subjected to unknown attacks. Network attacks are considered to exist in two classes of channels: 1) communication channels from the plant to sensors and 2) communication channels among sensors. The status of an attack is viewed as a stochastic phenomenon, and the transmitted information will be affected when the attacker successfully carries out an attack on the related data packet. Based on the sensors’ own measurements and their neighbors’ local information, a novel distributed estimation model against two-channel stochastic attacks is presented. A sufficient condition on the existence of the desired distributed ${H} _{\boldsymbol {\infty }}$ estimators is derived and the distributed estimator gains are designed by solving a linear matrix inequality. Two illustrative examples are provided to demonstrate the effectiveness of the new design techniques.
TL;DR: Under this framework, a new sufficient condition is proposed to ensure that the augmented system is stochastically mean-square stable with a specified level of $H_\infty$ performance.
Abstract: This paper studies the problem of model reduction for nonhomogeneous Markovian jump systems. The transition probability matrix of the nonhomogeneous Markovian chain has the characteristic of a polytopic structure. An asynchronous reduced-order model is considered, and the asynchronization is modeled by a hidden Markov model with a partially unknown conditional probability matrix. Under this framework, a new sufficient condition is proposed to ensure that the augmented system is stochastically mean-square stable with a specified level of $H_\infty$ performance. Finally, a numerical example is provided to show the effectiveness and advantages of the theoretic results obtained.
TL;DR: In this article, the effect of transition metal ions, e.g., Mn ions, dissolved from the cathode on the failure of lithium anodes was investigated in a working cell, and a graphene-coated separator was proposed to obstruct Mn ions by adsorption for lithium protection.
Abstract: Lithium–metal batteries (LMBs) comprising a lithium anode and high-specific-capacity manganese (Mn)-based cathode provide a promising high-energy-density system. However, this full cell suffers from poor cycling life under practical conditions. In this contribution, the effect of transition metal ions, e.g., Mn ions, dissolved from the cathode on the failure of lithium anodes was investigated in a working cell. Mn ions are involved in the formation of the solid electrolyte interphase (SEI), inducing the emergence of Mn content and a decrease in the Li2O and LiF components in the SEI; this results in inhomogeneous lithium nucleation. Furthermore, the direct chemical reaction between Mn ions and lithium anodes results in anode corrosion. For the crossover shielding of Mn ions, a graphene-coated separator was proposed to obstruct Mn ions by adsorption for lithium protection, prolonging the lifespan of LMBs under harsh conditions. This study not only highlights the impact of dissolved transition metal ions, such as Mn ions, on the stability of lithium anodes but also affords a practical strategy to shield the crossover of transition metal ions for anodic protection in both present lithium-ion and next-generation batteries.
TL;DR: The results provided a theoretical basis for assessing C balance in terrestrial ecosystems and showed that soil respiration in the rainy season was significantly higher than that in the dry season (P < .05).
TL;DR: This article introduces a hidden semi-Markov model and uses a stochastic process as a switching signal of the filter to observe the system modes and develops a Lyapunov function approach and linear matrix inequality method to ensure the filtering error dynamics is stable with a prescribed energy-to-peak performance index.
Abstract: In this article, the problem of energy-to-peak filtering problem is studied for a class of continuous-time semi-Markov jump systems with mismatched modes. We consider the scenario where the mode of the system is not always instantaneously accessible and mismatches the mode of the filter. To cope with this asynchronous phenomenon, we introduce a hidden semi-Markov model and use a stochastic process as a switching signal of the filter to observe the system modes. By the Lyapunov function approach and linear matrix inequality method, sufficient conditions are developed to ensure the filtering error dynamics is stable with a prescribed energy-to-peak performance index. Two examples are given to illustrate the effectiveness of the proposed design technique.
TL;DR: A model-free cooperative adaptive sliding-mode-constrained-control strategy is proposed considering the input magnitude and rate constraints which may cause the problem of actuator and integral saturation in the multiple linear induction traction systems.
Abstract: In order to deal with the speed cooperative control problem in the multiple linear induction traction systems consists of multiple linear induction motors, a model-free cooperative adaptive sliding-mode-constrained-control strategy is proposed considering the input magnitude and rate constraints which may cause the problem of actuator and integral saturation. First, the equivalent circuit topology of the single motor in the system is investigated. Besides, the system is considered as the multiagent system with fixed communication topology due to the interaction between adjacent motors. Then, the output observer is presented to estimate the output and the estimation algorithm of pseudo-partial derivative parameter and uncertainties is proposed. Based on the above, the proposed control scheme is presented by designing an integral sliding-mode surface containing the systematic error and an anti-windup compensator is added to eliminate the saturation. Finally, the simulations of the proposed control strategy for multiagent systems are carried out to demonstrate the effectiveness and superiority of the proposed control strategy.