带有完全分布式观测器的多智能体系统自适应容错一致性

针对一类同时带有执行器故障,未知非线性动态和非匹配干扰的多智能体系统,本文提出一种新的自适应容错控制方案.首先,设计一种适用于有向切换拓扑的完全分布式观测器估计领导者的信息,将一致性问题转化为局部的信号跟踪问题.其次,拆解转化后的误差系统为两个耦合的子系统,实现非匹配干扰与匹配因子分离.然后,利用径向基神经网络近似非线...     

Fault-tolerant Consensus of Leader-following Multi-agent Systems Based on Distributed Fault Estimation Observer

International Journal of Control, Automation and Systems - This paper is concerned with the fault-tolerant consensus control problem for leader-following multi-agent systems with actuator faults...     

Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults

In this paper, a distributed output feedback consensus tracking control scheme is proposed for second-order multi-agent systems in the presence of uncertain nonlinear dynamics, external disturbances, input constraints, and partial loss of control effectiveness. The proposed controllers incorporate reduced-order filters to account for the unmeasured states, and the neural networks technique is implemented to approximate the uncertain nonlinear dynamics in the synthesis of control algorithms. In order to compensate the partial loss of actuator effectiveness faults, fault-tolerant parts are included in controllers. Using the Lyapunov approach and graph theory, it is proved that the controllers guarantee a group of agents that simultaneously track a common time-varying state of leader, even when the state of leader is available only to a subset of the members of a group. Simulation results are provided to demonstrate the effectiveness of the proposed consensus tracking method.     

不确定非线性多智能体系统的分布式容错协同控制

针对一类存在未知非线性的多智能体系统,研究具有执行器故障的“领导-跟随”协同控制问题。利用模糊逻辑系统逼近系统的未知非线性,通过设计故障估计器辨识系统的故障。在“跟随者”之间的通信网络为单向连通的情况下,提出分布式模糊容错协同控制器的设计方案,实现“跟随者”的状态跟踪“领导者”的状态。基于Lyapunov稳定性理论,证明系统的跟踪误差一致最终有界。仿真结果验证了所提出设计方法的有效性。     

Command-filter-based distributed containment control of nonlinear multi-agent systems with actuator failures

In this paper, the problem of distributed containment fault-tolerant control for a class of nonlinear multi-agent systems in strict-feedback form is studied. The considered nonlinear multi-agent systems are subject to unknown nonlinear functions and actuator faults with loss of effectiveness and lock-in-place. By resorting to the universal approximation capability of fuzzy logical systems, the command filtered backstepping technique and nonlinear fault-tolerant control theory, distributed controllers are designed recursively. From the Lyapunov stability theory, it is proved that all signals of the resulting closed-loop systems are cooperatively semi-globally uniformly ultimately bounded and the containment errors converge to a small neighbourhood of origin by properly tuning the design parameters. Finally, a numerical example is provided to show the effectiveness of the proposed control method.     

Event-triggered Sliding Mode Fault-tolerant Consensus for a Class of Leader-follower Multi-agent Systems

This paper concerns with the robust sliding mode fault-tolerant consensus problem for a class of undertain second-order leader-follower multi-agent systems based on event-triggering strategies. First, a sliding mode fault-tolerant controller which uses the bound information of actuator failure rate and the event-triggering threshold is designed to ensure the robust consensus of the multi-agent systems, and the range of the sliding mode band is also shown. Second, by constructing an equivalent relationship, the upper bound of robust consensus error is also given. Third, the minimum event-triggered execution time for the second-order leader-follower multi-agent systems is calculated. Finally, the simulation results verify the effectiveness of the proposed event-triggered sliding mode fault-tolerant consensus algorithm.

     

带有智能领导者的网络系统分群投影一致性

针对多智能体系统在分群结构下投影一致性问题,引入了一种新的领导者称之为智能领导者。与传统的领导者相比,智能领导者可以获取和利用相邻跟随者位置信息,这些信息是否会用于调整智能领导者的控制算法由事件触发函数决定,从而很大程度上提高了系统的鲁棒性和容错性。设计了一个新颖的分布式控制协议;利用矩阵理论和Lyapunov稳定性理论,给出了系统在分群结构下实现投影一致性的充分条件;基于拉普拉斯变换性质,分析了当一些跟随者发生执行器故障时,系统能够保证跟踪误差有界;最后数值仿真验证了结果的有效性。     

Cooperative control for consensus of multi-agent systems with actuator faults

Consensus tracking problem in multi-agent systems with both outage and partial loss of effectiveness types of actuator faults is investigated in this paper. By adopting the virtual actuator technique based on the obtained fault estimates, the effects of possible actuator faults can be effectively compensated in each individual agent. Based on this, a distributed control strategy is developed by using locally available information. It is shown that the tracking error of each fault-free agent can converge to zero and the tracking errors of the faulty agents can remain bounded if the fault estimates are accurate. Moreover, a sufficient condition for achieving bounded tracking errors for all the followers is derived in terms of the fault estimation error. The sliding mode observer is utilized to estimate the faults. Simulation results are given to show the effectiveness of the proposed approach.     

预设跟踪性能下车辆队列执行器故障主动容错控制

研究预设跟踪性能下的车辆队列执行器故障主动容错控制问题.考虑执行器部分失效和偏移故障情形,设计Luenberger观测器和自适应残差阈值以实现执行器故障检测.在此基础上,为了确保执行器故障下的车辆队列暂态和稳态性能,在预设跟踪性能框架下,设计基于反步法的主动容错控制算法,在满足预设性能的前提下,实现车辆队列跟踪误差有界,且车辆间距满足安全性和紧凑性约束.仿真结果验证了所提出主动容错控制算法的有效性.     

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.      

Modified leader-following consensus of time-delay multi-agent systems via sampled control and smart leader

In this paper, the consensus problems of multiple agents with continuous-time single-integrator dynamics are studied, where each agent can obtain the position data of its neighboring agents at discrete-time points by using the periodic sampling technology and zero-order hold circuit. The smart leader is introduced, which can adjust the interaction strength between itself and the target point according to the state errors between itself and its neighboring followers. The modified leader-following consensus problem is defined as the leader-following consensus problem when the smart leader is adopted. Different leader-following consensus protocols are obtained for the multi-agent systems with or without sampling delays. The theoretical results, which are analysed with Lyapunov stability theory, can decrease the tracking error of the system, especially for the multi-agent systems with disturbance generated by actuator faults. Some simulation examples and real experiments are presented for illustration.     

Detection,isolation and handling of actuator faults in distributed model predictive control systems

In this work, we focus on monitoring and reconfiguration of distributed model predictive control systems applied to general nonlinear processes in the presence of control actuator faults. Specifically, we consider nonlinear process systems controlled with a distributed control scheme in which two Lyapunov-based model predictive controllers manipulate two different sets of control inputs and coordinate their actions to achieve the desired closed-loop stability and performance specifications. To deal with control actuator faults which may reduce the ability of the distributed control system to stabilize the process, a model-based fault detection and isolation and fault-tolerant control system which detects and isolates actuator faults and determines how to reconfigure the distributed control system to handle the actuator faults while maintaining closed-loop stability is designed. A detailed mathematical analysis is carried out to determine precise conditions for the stabilizability of the fault detection and isolation and fault-tolerant control system. A chemical process example, consisting of two continuous stirred tank reactors and a flash tank separator with a recycle stream and involving stabilization of an unstable steady-state, is used to demonstrate the approach.     

Distributed Adaptive Fault-Tolerant Output Regulation of Heterogeneous Multi-Agent Systems With Coupling Uncertainties and Actuator Faults

In this paper, we consider the distributed adaptive fault-tolerant output regulation problem for heterogeneous multiagent systems with matched system uncertainties and mismatched coupling uncertainties among subsystems under the influence of actuator faults. First, distributed finite-time observers are proposed for all subsystems to observe the state of the exosystem. Then, a novel fault-tolerant controller is designed to compensate for the influence of matched system uncertainties and actuator faults. By using the linear matrix inequality technique, a sufficient condition is provided to guarantee the solvability of the considered problem in the presence of mismatched coupling uncertainties. Moreover, it is shown that the system in closed-loop with the developed controller can achieve output regulation by using the Lyapunov stability theory and cyclic-small-gain theory. Finally, a numerical example is given to illustrate the effectiveness of the obtained result.      

带有输出约束条件的随机多智能体系统容错控制

在有向通讯拓扑图下,针对一类具有输出约束和执行器偏差增益故障的非严格反馈随机多智能体系统,提出一种自适应神经网络容错控制设计方案.采用神经网络逼近未知非线性函数,构造障碍李雅普诺夫函数处理系统的输出约束问题,以反步法和动态面技术为框架,结合Nussbaum函数设计自适应神经网络容错控制方法.基于李雅普诺夫稳定性理论,证明所有跟随者输出与领导者输出达到一致,闭环系统的所有信号依概率半全局一致最终有界且系统输出限制在给定紧集内.论文最后通过仿真实验验证所给出控制方案的有效性.     

Adaptive fault-tolerant control for multiple Euler–Lagrange systems considering time delays and output constraints

Considering the existence of communication delays, the adaptive fault-tolerant control problems for constrained multiple Euler–Lagrange systems are considered in this paper. First, a communication delays observer is utilized to enable all followers can acquire the leader's state information. Second, based on neural network technique, two distributed coordinated control schemes are designed to make every follower can track the leader. Compared with the first control algorithm, the adaptive fault-tolerant control problem is further considered in the second control algorithm. The proposed algorithm can simultaneously compensate the actuator bias faults and the partial loss of actuation effectiveness faults. At the same time, a tan-type barrier Lyapunov function is used to constrain the tracking errors of all followers and the leader. Finally, the simulations show the effectiveness of the proposed control schemes.     

Predefined-time control for Euler–Lagrange systems with model uncertainties and actuator faults

A novel adaptive predefined-time tracking control algorithm is proposed for the Euler–Lagrange systems (ELSs) with model uncertainties and actuator faults. Compared with traditional finite-time and fixed-time studies, the system output tracking error under the proposed predefined-time controller converges to a small neighborhood of zero in finite time, whose upper bound is exactly a design parameter in the control algorithm. For the uncertain model, radial-based function neural network (RBFNN) is utilized to approximate the continuous uncertain dynamics. To deal with the actuator faults, an adaptive control law is involved in the fault-tolerant controller. In order to achieve the predefined-time bounded, a novel predefined-time sliding mode surface is designed. It is proved that the tracking error vector trajectory of closed-loop system is semi-globally uniformly ultimately predefined-time bounded, and the upper bounds of both the system settling time and the corresponding output tracking error can be adjusted with a simple parameter. Simulation examples finally demonstrate the effectiveness of the proposed control algorithm.     

Adaptive quantised fault-tolerant tracking control of uncertain nonlinear systems with unknown control direction and the prescribed accuracy

In this paper, the problem of adaptive fault-tolerant tracking control for a class of uncertain nonlinear systems in the presence of input quantisation and unknown control direction is considered. By choosing a class of particular Nussbaum functions, an adaptive fault-tolerant control scheme is designed to compensate actuator faults and input quantisation while the control direction is unknown. Compared with the existing results, the proposed controller can directly compensate for the nonlinear term caused by actuator faults and the nonlinear decomposition on the quantiser without estimating its bound. Furthermore, via Barhalant's Lemma, it is proven that all the signals of the closed-loop system are globally uniformly bounded and the tracking error converges into a prescribed accuracy in prior. Finally, an illustrative example is used for verifying effectiveness of the proposed approach.     

基于学习的线性多智能体系统弹性最优协同容错控制

针对一类线性多智能体系统,研究其在网络间歇性拒绝服务攻击下的最优同步控制问题.首先,在时变非对称通讯网络拓扑结构下,提出一种弹性最优协同容错控制策略,并优化多智能体的合作二次性能指标,然后证明全局跟踪误差在出现执行器故障和网络攻击时仍然渐进收敛.进一步,当考虑多智能体子系统模型参数未知,同时系统发生执行器故障的情况下,提出利用局部系统状态和输入信息的自学习迭代算法求解代数Riccati方程,计算子系统的反馈控制器增益,实现弹性协同容错控制目标.最后,通过Chua电路网络仿真算例验证所提出的控制方法的有效性.