Fixed-Time Output Consensus Tracking for High-Order Multi-Agent Systems With Directed Network Topology and Packet Dropout

This paper studies the problem of fixed-time output consensus tracking for high-order multi-agent systems(MASs)with directed network topology with consideration of data packet dropout.First,a predictive compensation based distributed observer is presented to compensate for packet dropout and estimate the leader’s states.Next,stability analysis is conducted to prove fixed time convergence of the developed distributed observer.Then,adaptive fixed-time dynamic surface control is designed to counteract mismatched disturbances introduced by observation error,and stabilize the tracking error system within a fixed time,which overcomes explosion of complexity problem and singularity problem.Finally,simulation results are provided to verify the effectiveness and superiority of the consensus tracking strategy proposed.The contribution of this paper is to provide a fixed-time distributed observer design method for high-order MAS under directed graph subject to packet dropout,and a novel fixed-time control strategy which can handle mismatched disturbances and overcome explosion of complexity and singularity problem.     

切换拓扑下非线性多智能体系统自适应神经网络一致性

本文研究一类具有未知控制系数的非线性多智能体系统自适应神经网络分布式控制策略.首先,针对切换拓扑下具有未知控制系数的非线性多智能体系统一致性问题,提出一类自适应神经网络一致性控制算法.其中,采用神经网络函数逼近方法解决系统中的不确定性问题,并设计一项自适应光滑项处理有界扰动和神经网络函数逼近误差.随后,证明了切换拓扑下具有未知控制系数的非线性多智能体系统的一致性,并保证了闭环系统的有界性.此外,本文把相关的一致性算法扩展到了一般有向图含有一个有向生成树的情形.最后,通过仿真实例验证了本文所提算法的有效性.     

Observer-based fault tolerant control for a class of nonlinear multi-agent systems with sensor faults

This article focuses on the robust fault tolerant control (FTC) problem for a class of Lipschitz nonlinear multi-agent systems(MASs) subject to sensor faults. Firstly, sensor faults are transformed into actuator faults via introducing a new intermediate auxiliary state variable, and a distributed adaptive fault estimation observer is designed to estimate the state information and the concerned faults by using the relative output estimation error. Then, the sufficient existence conditions for the observer to satisfy the robust performance index are given. Thirdly, based on the results of observer design, a new design method of dynamic output feedback controller is proposed to implement consensus of MASs and ensure the desired disturbance rejection performance. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.     

Distributed fuzzy adaptive event-triggered finite-time consensus tracking control for uncertain nonlinear multi-agent systems with asymmetric output constraint

This article investigates the consensus problem for uncertain nonlinear multi-agent systems (MASs) with asymmetric output constraint. Different from BLF-based constraint consensus tracking control, a novel approach based on nonlinear state-dependent function is proposed to solve the asymmetric output constraint, which need not convert output constraint into tracking error bound. First-order sliding mode differentiator is incorporated into each step of backstepping control design to reduce computation burden. Further, in combination of proposed event-triggered mechanism based on time-varying threshold, a distributed fuzzy adaptive event-triggered finite-time consensus method is developed. It can ensure that the consensus tracking error tends to a small neighbor in a finite time and the asymmetric output constraint of each subsystem is not violated. Two simulations are given to demonstrate the effectiveness of control method.     

基于有限时间指令滤波的非线性系统固定时间预设性能控制

针对一类严格反馈非线性系统,提出一种基于有限时间指令滤波的自适应固定时间预设性能控制策略.首先,引用非线性映射技术及适当的误差变换,建立等效的误差模型;其次,综合利用反步法、固定时间控制和自适应控制等方法,设计一种基于有限时间指令滤波的预设性能跟踪控制器.该策略应用指令滤波器解决了反步法中对虚拟控制律反复求导问题,减轻了计算负担.此外,预设性能控制和固定时间控制保证了系统的跟踪误差能够在固定时间内收敛到预设性能函数限定的范围内,其收敛时间与系统初始条件无关,且确保系统中全部信号在有限时间均达到有界区域.理论分析与仿真验证均表明了所提出设计方法的有效性.     

Adaptive neural practical fixed-time command filtered control for multi-input and multi-output nonlinear systems with dead zones input and unknown control direction

In this article, under the circumstance of dead zones input and unknown control direction, the adaptive practical fixed-time control strategy is presented for a general class of multi-input and multi-output (MIMO) nonlinear systems. The inherent explosion of computational complexity difficulty is eliminated by adopting a command filter technique and the universal approximation properties of radial basis function neural networks (RBFNNs) are applied to model the unknown nonlinear functions. The difficulties of the dynamic surface method and unknown directions can be handled by invoking error compensation mechanism and Nussbaum-type functions, respectively. The uniqueness of the presented control scheme is that the tracking system can achieve the fixed-time stability without relying on the boundedness of dead-zone parameters. The fixed-time convergence of the output tracking error and the semiglobally fixed-time stable of closed-loop system are assured via the developed adaptive fixed-time command filtered controller. Finally, a practical example is supplied to further validate the availability of the presented theoretic result.     

Adaptive Finite-time Consensus for Second-order Nonlinear Multi-agent Systems with Input Quantization

In this paper, the adaptive finite-time consensus (FTC) control problem of second-order nonlinear multi-agent systems (MASs) with input quantization and external disturbances is studied. With the help of finite time control technology, a novel distributed adaptive control protocol is constructed to achieve FTC performance for second-order nonlinear MASs by using the recursive method. The control input is quantized through a hysteresis quantizer, which reduces the communication rate of arbitrary two agents. The unknown functions are approximated by adopting the radial basis function neural networks. Under the consensus protocols and adaptive laws, it can be proved that velocity errors of arbitrary two agents reach a small region of zero in finite time as well as position errors. Finally, the effectiveness of the proposed method is illustrated via a simulation example.

     

连续搅拌反应釜的固定时间命令滤波跟踪控制

针对一类连续搅拌反应釜系统的跟踪控制问题,提出一种基于反步法和模糊逻辑系统的自适应固定时间命令滤波控制方法.利用命令滤波器引入误差补偿机制消除滤波误差的影响,并解决反步法虚拟控制信号重复求导的问题;采用模糊逻辑系统对系统中存在的非线性部分进行逼近;利用固定时间控制方法使系统跟踪误差更迅速收敛至较小邻域内,且收敛时间不依赖系统初始状态;通过Lyapunov定理证明连续搅拌反应釜系统的闭环稳定性;利用Matlab/Simulink仿真实验验证所提出控制方法的有效性.与现有控制方法相比,该控制方法具有控制器结构简单、收敛速度快、控制精度高、无超调等优点.     

Active fault‐tolerant consensus control of Lipschitz nonlinear multiagent systems

This article investigates the active fault‐tolerant consensus problem for Lipschitz nonlinear multiagent systems under detailed balanced directed graph and actuator faults. First, a fault detection filter for each agent is designed, and all agents can be divided into two categories: healthy agents and possibly faulty agents. Second, fully distributed adaptive fault‐tolerant consensus protocols for healthy and possibly faulty agents are proposed to achieve state consensus. Third, based on the fault detection method and fault‐tolerant consensus protocols, active fault‐tolerant consensus algorithms are given. Simulation examples are presented to verify the effectiveness of the proposed active fault‐tolerant algorithms.     

Fully distributed consensus for fuzzy multiagent systems with jointly connected topology

This paper investigates the problem of fully distributed consensus for polynomial fuzzy multiagent systems (MASs) under jointly connected topologies. First, a polynomial fuzzy modeling method is presented to characterize the error dynamics that is constructed by one leader and multiple followers. Then, using the relative state information and the agents' dynamics, a distributed adaptive protocol is designed to guarantee that MASs under jointly connected topologies can achieve consensus in a fully distributed fashion. Utilizing the Lyapunov technique, a relaxed sufficient criterion is proposed to ensure consensus for fuzzy MASs under jointly connected topologies. Moreover, the adaptive coupling weights between neighboring agents can converge to certain values. The derived condition is transformed into a sum-of-squares form, which can be solved numerically. We provide an example to illustrate the proposed distributed adaptive consensus technique's validity.     

Fixed-time Group Consensus of Nonlinear Multi-agent Systems via Pinning Control

This paper deals with the fixed-time group consensus problem for multi-agent systems (MASs) subjected to exogenous disturbances. Firstly, two pinning control algorithms are constructed for MASs, which not only reduce the number of controllers but also achieve expected tracking consensus. Secondly, fixed-time group consensus is ensured by utilizing the algebraic graph theory, Lyapunov stability and fixed-time control technique. Finally, simulations are finally given for demonstrate the availability of the derived results.

     

Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

This paper considers the human-in-the-loop leader-following consensus control problem of multi-agent systems (MASs) with unknown matched nonlinear functions and actuator faults. It is assumed that a human operator controls the MASs via sending the command signal to a non-autonomous leader which generates the desired trajectory. Moreover, the leader’s input is nonzero and not available to all followers. By using neural networks and fault estimators to approximate unknown nonlinear dynamics and identify the actuator faults, respectively, the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is designed. It is proved that the state of each follower can synchronize with the leader’s state under a directed graph and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately bounded. Finally, simulation results are presented for verifying the effectiveness of the proposed control method.      

一类非线性系统模糊自适应固定时间量化反馈控制

研究了一类严格反馈不确定非线性系统的模糊自适应实际固定时间量化反馈控制问题. 基于李雅普诺夫有限时间稳定理论、自适应模糊控制理论及反演控制算法, 提出了一种非线性系统模糊自适应实际固定时间量化反馈跟踪控制方案. 所设计的控制方案能够保证闭环系统的输出跟踪误差在固定时间内收敛于原点的一个充分小邻域内, 且闭环系统内所有信号均有界. 最后, 数值示例验证了设计方案的有效性.     

Adaptive fuzzy leader-follower consensus control using sliding mode mechanism for a class of high-order unknown nonlinear dynamic multi-agent systems

In this article, a distributed leader-follower consensus approach is developed for a class of high-order unknown nonlinear dynamic multi-agent systems (MASs). Because every agent of the MAS contains multiple state variables, the existing consensus methods are not completely applicable for it. In order to find the qualified consensus protocol for this high-order MAS, sliding mode mechanism can be naturally considered for designing the consensus control because it can manage multiple state variables with the help of a constructed hyperplane. To this consensus control design, the sliding mode term is composed of all tracking error variables. Since the method does not require the switching control term around sliding surface, it can avoid the chattering phenomenon, which exits in most of the published sliding mode controls (SMCs). Furthermore, to handle the unknown nonlinear dynamic problem, the adaptive approximation strategy is implemented by employing fuzzy logic system (FLS). In the light of Lyapunov stability analysis, it is demonstrated that the proposed control approach can accomplish the consensus tasks. Finally, a numerical example is implemented to further show the desired results.     

Adaptive Consensus of Non-Strict Feedback Switched Multi-Agent Systems With Input Saturations

This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems (MASs) with non-strict feedback forms and input saturations under unknown switching mechanisms. First, in virtue of Gaussian error functions, the saturation nonlinearities are represented by asymmetric saturation models. Second, neural networks are utilized to approximate some unknown packaged functions, and the structural property of Gaussian basis functions is introduced to handle the non-strict feedback terms. Third, by using the backstepping process, a common Lyapunov function is constructed for all the subsystems of the followers. At last, we propose an adaptive consensus protocol, under which the tracking error under arbitrary switching converges to a small neighborhood of the origin. The effectiveness of the proposed protocol is illustrated by a simulation example.      

Encryption–decryption-based event-triggered consensus control for nonlinear MASs under DoS attacks

In this article, the consensus tracking problem is discussed for a class of discrete-time nonlinear multi-agent systems (MASs) subject to denial-of-service (DoS) attacks. The individual agents interact with each other via communication network whose topology is assumed to be time-varying and strongly connected. Two techniques are employed to deal with the network-induced complexities. On one hand, an event-triggering scheme is adopted to regulate the data transmission among agents with the purpose of making full utilization of the limited communication resources; and on the other hand, an encryption–decryption mechanism is designed with the aim to provide compensation, thereby mitigating the DoS attack effects. It is the objective of the addressed problem to develop a distributed model-free adaptive control law to enforce the MASs achieve desirable consensus performance. By using a specific projection algorithm in combination with a dynamic linearization method, the desired control protocol is formulated explicitly, whose effectiveness and applicability are demonstrated via an illustrative numerical example.     

Zero-error tracking control of uncertain nonlinear systems in the presence of actuator hysteresis

In this paper, the problem of adaptive tracking control is addressed for a class of nonlinear systems with unknown constant parameters and unknown actuator nonlinearity. The actuator nonlinearity is modelled as the backlash-like hysteresis, which is described by a differential model. The prior knowledge on the control gain sign is not required, and only the assumption on the reference signal is made. By combining the adaptive backstepping technique with the Nussbaum gain approach, an adaptive compensation controller design approach is developed. It is proved that the proposed control approach can guarantee that all the signals in the closed-loop system are bounded, and the tracking error can converge to zero asymptotically despite the presence of the actuator hysteresis. Two simulation examples are included to illustrate the effectiveness of the proposed approach.     

Event-triggered adaptive consensus control of nonlinear multi-agent systems with unknown control directions and actuator saturation

This article addresses the event-triggered adaptive consensus control of nonlinear multi-agent systems with unknown control direction and actuator saturation. A new robust adaptive control algorithm based on an event-triggered mechanism is designed. The smooth Lipschitz function approximates the saturated nonlinear function, while the Nussbaum function handles unknown control directions and residual terms. The event-triggered mechanism is designed to determine the time of communication, significantly reducing the communication burden. An additional estimator is utilized to deal with unknown parameters involved in neighbor dynamics and prevent information exchange to consistency errors between connected subsystems. The results show that all the signals of the closed-loop system are uniformly bounded, and the consensus tracking error converges to a bounded set. Meanwhile, Zeno's behavior is eliminated. Simulation results confirm the superiority of the proposed method.     

Robust adaptive actuator failure compensation for a class of uncertain nonlinear systems

This paper presents a robust adaptive state feedback control scheme for a class of parametric-strict-feedback nonlinear systems in the presence of time varying actuator failures. The designed adaptive controller compensates a general class of actuator failures without any need for explicit fault detection. The parameters, times, and patterns of the considered failures are completely unknown. The proposed controller is constructed based on a backstepping design method. The global boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighborhood of the origin. The proposed approach is employed for a two-axis positioning stage system as well as an aircraft wing system. The simulation results show the correctness and effectiveness of the proposed robust adaptive actuator failure compensation approach.     

Fully distributed robust consensus control of multi-agent systems with heterogeneous unknown fractional-order dynamics

This paper investigates the robust consensus control problem of heterogeneous unknown nonlinear fractional-order multi-agent systems (FOMASs) without leader and with multiple leaders of bounded inputs. More specifically, FOMASs with nonidentical unknown coupling nonlinearities and external disturbances are considered in this paper, which takes the first-order MASs as its special case. Based on the σ-modification adaptive control technique, some class of discontinuous robust adaptive control protocols are proposed to solve the leaderless consensus problem and containment consensus problem, respectively. By means of the set-valued maps theory and by artfully choosing Lyapunov function, it is shown that the proposed consensus protocols are user friendly in that they are capable of compensating uncertain coupling nonlinearities, rejecting disturbances, rendering smaller control gains and thus requiring smaller amplitude on the control input while preserving global consensus convergence. All of the proposed robust adaptive consensus protocols are independent of any global and unknown information and thus are fully distributed. Some numerical simulations are provided to validate the correctness of the obtained results.