Data‐driven optimal event‐triggered consensus control for unknown nonlinear multiagent systems with control constraints

This paper considers optimal consensus control problem for unknown nonlinear multiagent systems (MASs) subjected to control constraints by utilizing event‐triggered adaptive dynamic programming (ETADP) technique. To deal with the control constraints, we introduce nonquadratic energy consumption functions into performance indices and formulate the Hamilton‐Jacobi‐Bellman (HJB) equations. Then, based on the Bellman's optimality principle, constrained optimal consensus control policies are designed from the HJB equations. In order to implement the ETADP algorithm, the critic networks and action networks are developed to approximate the value functions and consensus control policies respectively based on the measurable system data. Under the event‐triggered control framework, the weights of the critic networks and action networks are only updated at the triggering instants which are decided by the designed adaptive triggered conditions. The Lyapunov method is used to prove that the local neighbor consensus errors and the weight estimation errors of the critic networks and action networks are ultimately bounded. Finally, a numerical example is provided to show the effectiveness of the proposed ETADP method.     

Consensus problem for continuous‐time multiagent systems with nonconvex control input and velocity constraints

In this work, a consensus problem with nonconvex control input and velocity constraints is studied for continuous‐time multiagent systems. In order to solve this problem, a fully distributed nonlinear algorithm is provided and an analysis approach is proposed based on the contraction property of an equivalent time‐varying system after a model transformation. It is shown that consensus can be achieved under the condition that there exists a directed spanning tree in the union of the communication graphs in each certain time interval. A numerical simulation is provided to show the obtained result.     

Neuroadaptive containment control of nonlinear multiagent systems with input saturations

This paper investigates the output containment tracking problem of nonlinear multiagent systems with mismatched uncertain dynamics and input saturations. A neural network–based distributed adaptive command filtered backstepping (CFB) scheme is given, which can guarantee that the containment tracking errors reach to the desired neighborhood of origin and all signals in the closed‐loop system are bounded. Note that error compensation system and virtual control laws established in CFB only use local information, so the given scheme is completely distributed. Moreover, the applied sliding mode differentiator (SMD) can make the outputs of SMD fast approximate the virtual signal and its derivative at each step of backstepping, which can further improve the control quality. Finally, a simulation example is given to show the effectiveness of the proposed scheme.     

Adaptive leaderless consensus control of uncertain multiagent systems with unknown control directions

This article solves the leaderless consensus problem of a class of uncertain nonlinear multiagent systems with unknown control directions and unknown system parameters. Without using the Nussbaum function approach, a novel control scheme is proposed by means of the switching mechanism. The control algorithm guarantees that consensus errors converge to the origin asymptotically, and the amplitude of the control signals is much smaller compared with those using Nussbaum functions. The simulation results illustrate the effectiveness of the proposed algorithm.     

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

This article investigates the leader‐follower consensus problem of a class of non‐strict‐feedback nonlinear multiagent systems with asymmetric time‐varying state constraints (ATVSC) and input saturation, and an adaptive neural control scheme is developed. By introducing the distributed sliding‐mode estimator, each follower can obtain the estimation of leader's trajectory and track it directly. Then, with the help of time‐varying asymmetric barrier Lyapunov function and radial basis function neural networks, the controller is designed based on backstepping technique. Furthermore, the mean‐value theorem and Nussbaum function are utilized to address the problems of input saturation and unknown control direction. Moreover, the number of adaptive laws is equal to that of the followers, which reduces the computational complexity. It is proved that the leader‐follower consensus tracking control is achieved without violating the ATVSC, and all closed‐loop signals are semiglobally uniformly ultimately bounded. Finally, the simulation results are provided to verify the effectiveness of the control scheme.     

Distributed consensus of second‐order multiagent systems with nonconvex input constraints

This paper addresses the input constrained consensus of second‐order multiagent systems with nonconvex constraints. A new update law is proposed to make the position states of all agents converge to a common point and the velocities converge to zero, while the input of each agent stays in a certain constraint set. The closed‐loop system is first converted to an equivalent system by taking a novel coordinate transformation. Then, it is proved that the input constrained consensus can be achieved if the graphs jointly have directed spanning trees by using the Metzler matrix theory. Finally, simulations are provided to demonstrate the effectiveness of the proposed algorithm.     

Formation control of singular multiagent systems with switching topologies

This paper is concerned with the time‐varying formation control problem for singular multiagent systems with switching topologies. First, in order to eliminate the pulse solution of singular systems and extend the formation function set, the distributed formation controller has been formulated based on the output information of the agents. Then, the explicit expression of formation position function is presented based on the impulse free and the equivalent transformation of singular multiagent systems. Next, the sufficient and necessary conditions of the feasibility of the formation function are provided. Moreover, the sufficient conditions of formation control of singular multiagent systems with switching topologies are presented and the algorithm is designed to solve the distributed controller. Finally, the validity of the proposed approaches is verified by numerical simulation in this paper.     

Distributed containment control for nonlinear multiagent systems in pure‐feedback form

In this paper, the problem of distributed containment control for pure‐feedback nonlinear multiagent systems under a directed graph topology is investigated. The dynamics of each agent are molded by high‐order nonaffine pure‐feedback form. Neural networks are employed to identify unknown nonlinear functions, and dynamic surface control technique is used to avoid the problem of explosion of complexity inherent in backstepping design procedure. The Frobenius norm of the ideal neural network weighting matrices is estimated, which is helpful to reduce the number of the adaptive tuning law and alleviate the networked communication burden. The proposed distributed containment controllers guarantee that all signals in the closed‐loop systems are cooperatively semiglobally uniformly ultimately bounded, and the outputs of followers are driven into a convex hull spanned by the multiple dynamic leaders. Finally, the effectiveness of the developed method is demonstrated by simulation examples.     

Model‐free adaptive formation control for unknown multiinput‐multioutput nonlinear heterogeneous discrete‐time multiagent systems with bounded disturbance

Based on the model‐free adaptive control, the distributed formation control problem is investigated for a class of unknown heterogeneous nonlinear discrete‐time multiagent systems with bounded disturbance. Two equivalent data models to the unknown multiagent systems are established through the dynamic linearization technique considering the circumstances with measurable and unmeasurable disturbances. Based on the obtained data models, two distributed controllers are designed with only using the input/output and disturbance data of the neighbor agents system. The tracking error of the closed‐loop system driven by the proposed controllers is shown to be bounded by the contraction mapping principle and inductive methods. An example illustrates the effectiveness of the proposed two distributed controllers.     

Adaptive cooperative output regulation of nonlinear multiagent systems with arbitrarily large parametric uncertainties and an uncertain leader

This paper extends the result for cooperative output regulation problem for uncertain nonlinear multiagent systems in output feedback form in the sense that the exosystem generating leader's signal and disturbance is allowed to contain unknown parameter, and all parameters in the whole multiagent system can be arbitrarily large. Since only the information of itself and its neighbors is available, constructing a distributed control law is necessary for the asymptotic tracking of the uncertain leader's signal and the rejection of unknown external disturbances, which is also the main challenge here. A series of simulations are conducted to illustrate the efficiency and advantage of our designs together with the comparison of the design in the existing work.     

Stability analysis of nonholonomic multiagent coordinate‐free formation control subject to communication delays

This paper investigates the convergence of nonholonomic multiagent coordinate‐free formation control to a prescribed target formation subject to communication delays by means of Lyapunov‐Krasovskii approach and smooth state‐feedback control laws. As a result, an iterative algorithm based on linear matrix inequalities is provided to obtain the worst‐case point‐to‐point delay under which the multiagent system is guaranteed to be stable. It is worth mentioning that: (i) the given algorithm holds for any connected communication topology and (ii) the formation control is coordinate‐free, that is, a common frame is not required to be shared between agents. The effectiveness of the given method is illustrated through simulation results.     

基于自适应分布式滤波观测器的多智能体系统编队控制

本文考虑了全局指令系统输出信息受到信道扰动情况下线性多智能体系统的编队控制问题.首先,基于协作式输出调节理论框架对线性多智能体系统的编队控制问题进行数学建模.其次,针对受到信道扰动的全局指令系统输出信息,提出了一类基于受扰输出的自适应分布式滤波观测器,在降低网络信息交换量的同时消除扰动的影响.最后,设计了输出反馈确定等价控制律,解决了线性多智能体系统的分布式编队控制问题.给出了数值仿真结果检验控制性能.     

Distributed control of uncertain multiagent systems for tracking a leader with unknown fractional‐order dynamics

This paper proposes distributed adaptive cooperative control algorithms for second‐order agents to track a leader with unknown dynamics. The models of the followers and the leader are composed of uncertain nonlinear components. The order of the leader's dynamics is unknown and can be fractional. Only the single output information is shared among neighbored agents. To simplify the control design, linearly parameterized neural networks are used to approximate the unknown functions. We first present an adaptive control for leaderless consensus and then extend the method to the tracking problem. Thorough theoretical proofs as well as numerical simulation are included to verify the results. Compared with relevant literature, the new approach applies to a larger variety of systems because (i) knowledge about the structure of leader's model is unnecessary; (ii) the unknown functions in different agents' dynamics can be diverse and arbitrary, in other words, the algorithms apply to heterogeneous agents; (iii) the results can be simply used without parameter calculations.     

Distributed fixed‐time consensus for multiagent systems with unknown control directions

This paper investigates the consensus problem for high‐order multiagent systems with unknown control directions and directed communication constraints. To handle the problem of unknown control directions, a logic switching rule is established in the framework of fixed‐time stability. Then, the consensus is achieved in two steps. A group of distributed fixed‐time observers is designed to estimate the reference signals first. Based on these estimates and the designed logic switching rule, a novel control protocol is proposed for each follower system. Different from the existing results, the consensus is achieved with a fixed‐time convergence rate, and the unknown control directions are allowed to be nonidentical for each agent. Finally, simulation results are given to exhibit the validity of the proposed method.     

Adaptive consensus control for stochastic nonlinear multiagent systems with full state constraints

In this paper, the consensus tracking problem is investigated for stochastic nonlinear multiagent systems with full state constraints and time delays. The barrier Lyapunov functions proposed for single‐agent constrained systems are constructively extended to solve the consensus problem for multiagent systems with the full state constraints. Some Lyapunov‐Krasovskii functionals are introduced to compensate for state time delays, which are inherent in the complicated nonlinear systems. Based on the variable separation technique, the difficulty arising from the nonstrict‐feedback structure is overcome. Under a directed communication topology, the distributed neuroadaptive control protocols are proposed to guarantee that all the follower agents follow the trajectory of the leader agent and the full state constraints are not violated. The effectiveness of the proposed distributed adaptive control approach is verified via simulation examples.     

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.     

Consensus control of output‐constrained multiagent systems with unknown control directions under a directed graph

This paper presents a novel distributed adaptive control algorithm for uncertain higher‐order nonlinear multiagent systems subject to output constraints and unknown control directions. Regarding the latter, a generic class of cases is considered, allowing completely unknown and even nonidentical control directions. Furthermore, the communication topology is only required to contain a fixed directed spanning tree. To guarantee the output constraints and address the asymmetric directed communication topology, a new reference output using the transformation strategy is introduced for each agent, benefiting from which the consensus problem of the multiagent system is recast as local tracking control problems of single agents. Then, the distributed control algorithm is recursively established based on the backstepping technique and the Nussbaum‐type function. By leveraging the unique properties of the Laplacian matrix on directed graphs and matrix theory, it is shown that, under the proposed distributed algorithm, uniform boundedness of all closed‐loop signals can be ensured, and asymptotic consensus is achieved without violation of the output constraints. Finally, simulation studies on the angle control of single‐link robots are given to verify the effectiveness of the proposed algorithm.     

Decentralized event‐triggered circle formation control for multiagent systems via synchronous periodic event detection

This paper investigates circle formation problem of multiagent systems over a kind of strongly connected and weight‐unbalanced directed graphs. To solve the concerned problem, decentralized periodic event‐triggered algorithms subject to or not to time delays are proposed, which have the advantages of decreasing the overall burden of the network in terms of finite communication and control input updates. In such algorithms, each agent independently evaluates whether the locally sampled information of itself should be broadcasted to or not to its neighbors. Furthermore, another advantage of our proposed algorithms is to automatically exclude Zeno behavior, which should be seriously considered in a variety of event‐based network systems. Sufficient conditions on circle formation control are derived under which the states of all agents can be ensured to converge to some desired equilibrium point. Simulation results are given to validate the effectiveness of the proposed methods.     

一类非线性多自主体系统的实用脉冲一致性

针对一类非线性多自主体系统,研究基于实用脉冲控制的一致性协议设计问题.引入脉冲调制间歇控制策略,利用峰值很大,持续时间很短的信号代替理想脉冲信号,设计实用脉冲一致性协议.首先给出一类连续―间歇型实用脉冲协议.利用李雅普诺夫函数方法,图论和间歇控制理论,证明了在该协议下,多自主体系统可以实现渐近一致性.在连续—间歇型实用脉冲协议实施中,需在控制作用区间连续量测自主体状态.针对此局限,提出了采样―间歇型实用脉冲协议.通过采样和间歇控制理论,建立了多自主体系统实现渐近一致性的充分条件.进一步地,分析了当控制作用区间等于采样周期时,采样—间歇型实用脉冲协议退化为周期采样控制协议,而当控制作用区间趋于0时,其退化为脉冲控制协议.揭示了所提出的采样―间歇型实用脉冲协议同周期采样控制协议,脉冲控制协议之间的关系.     

Sliding mode coordination control for multiagent systems with underactuated agent dynamics

In this paper, we develop a new integrated coordinated control and obstacle avoidance approach for a general class of underactuated agents. We use graph-theoretic notions to characterise communication topology in the network of underactuated agents as determined by the information flow directions and captured by the graph Laplacian matrix. Obstacle avoidance is achieved by surrounding the stationary as well as moving obstacles by elliptical or other convex shapes that serve as stable periodic solutions to planar systems of ordinary differential equations and using transient trajectories of those systems to navigate the agents around the obstacles. Decentralised controllers for individual agents are designed using sliding mode control approach and are only based on data communicated from the neighbouring agents. We demonstrate the efficacy of our theoretical approach using an example of a system of wheeled mobile robots that reach and maintain a desired formation. Finally, we validate our results experimentally.