Explore the vast range of titles available.

This article addresses the distributed containment control problem in a group of agents governed by second‐order dynamics with directed network topologies. Considering there are multiple leaders, we study a general second‐order containment controller which can realize several different consensus modes by adjusting control gains. A necessary and sufficient condition on the control gains of the general containment controller is provided. Moreover, the delay sensitivity of the closed‐loop multiagent system under the general containment controller is studied; the maximal upper bound of the constant delays is obtained. Finally, several numerical examples are used to illustrate the theoretical results. © 2015 Wiley Periodicals, Inc. Complexity 21: 112–120, 2016

In this paper, we propose a vehicle platooning method based on pinning consensus control and its cyber attack detection. The consensus problem, in which the state of each agent is matched through communications, is a well-known control problem. Pinning control is a method of adding external control inputs to pre-specified agents called pinning agents. This control method can set the state of an agent to a value other than its initial average value or increase the rate at which it converges. Model predictive control (MPC) involves obtaining control inputs by solving the finite-time optimal control problem at each discrete time. Using pinning consensus control and MPC, we consider vehicle group control, in which multiple vehicles are controlled as a single group. In addition, a method for detecting cyber attacks on pinning agents is also proposed.

In this paper, an adaptive fixed/arbitrary‐time distributed cooperative guidance law is proposed to solve the three‐dimensional simultaneous attack problem. Firstly, with undirected topologies, a second‐order leader‐following consensus protocol, integral sliding mode, and adaptive law are implemented to construct an adaptive fixed‐time cooperative control law for intercepting a maneuvering target. Range‐to‐go is chosen as the consensus variable instead of time‐to‐go, and simultaneous arrival of multiple missiles is achieved for the incoming target despite the variations in velocity magnitude. Meanwhile, a robust fast fixed‐time observer is designed to estimate target accelerations, and an arbitrary‐time sliding mode manifold is constructed and maintained across the entire time domain, while a continuous adaptive sliding mode control law is formulated through synergistic integration of adaptation law and quasiswitching function. The settling time of the closed‐loop guidance system can be precisely chosen by a predetermined time constant, and LOS angular rates can be effectively steered to the equilibrium point. By relying on the position and velocity of the incoming target, normal acceleration and longitudinal acceleration can achieve a simultaneous hit‐to‐kill attack with the desired impact angles, while fast fixed/arbitrary‐time stability is proved through the Lyapunov theory. Finally, numerical simulations are performed to validate the feasibility and effectiveness of the theoretical results.

The problem of collision avoidance of an unmanned aerial vehicle (UAV) group is studied in this paper. A collision avoidance method of UAV group formation based on second-order consensus algorithm and improved artificial potential field is proposed. Based on the method, the UAV group can form a predetermined formation from any initial state and fly to the target position in normal flight, and can avoid collision according to the improved smooth artificial potential field method when encountering an obstacle. The UAV group adopts the “leader–follower” strategy, that is, the leader UAV is the controller and flies independently according to the mission requirements, while the follower UAV follows the leader UAV based on the second-order consensus algorithm and formations gradually form during the flight. Based on the second-order consensus algorithm, the UAV group can achieve formation maintenance easily and the Laplacian matrix used in the algorithm is symmetric for an undirected graph. In the process of obstacle avoidance, the improved artificial potential field method can solve the jitter problem that the traditional artificial potential field method causes for the UAV and avoids violent jitter. Finally, simulation experiments of two scenarios were designed to verify the collision avoidance effect and formation retention effect of static obstacles and dynamic obstacles while the two UAV groups fly in opposite symmetry in the dynamic obstacle scenario. The experimental results demonstrate the effectiveness of the proposed method.

This paper studies the second-order consensus in multi-agent systems with sampled position and velocity data via pinning control. The distributed pinning consensus protocols with second-order dynamics are designed, where both sampled position and velocity data are employed. Necessary and sufficient conditions are derived for reaching second-order consensus by combining the algebraic graph theory and the analytical method. According to the obtained consensus criteria, the second-order leader-following consensus can be reached if and only if the sampling period, the coupling gain, and the pinning gains satisfy some derived algebraic inequalities. Moreover, it is found that second-order consensus in multi-agent systems cannot be reached with only sampled position data in the pinning controllers. Finally, the effectiveness and correctness of our theoretical findings are demonstrated by some numerical examples.

This paper aims at investigating the second-order consensus problem of the multi-agent systems with nonlinear dynamics. Since it is more difficult to obtain the velocity information compared with the position information in practical application, a very simple sufficient condition for updating the coupling gain of the velocity information exchange between each agent is firstly derived to achieve asymptotic consensus. Furthermore, communication delay of each agent is considered for velocity information exchange. The velocity signal from a virtual leader is introduced to reach the second-order consensus. All the above fundamental consensus criteria are guaranteed base on algebraic graph theory, matrix theory, and Lyapunov stability method. Two simulation examples are provided to demonstrate the effectiveness of the analytical results. The results obtained in this paper can be easily applied to various cases, which can facilitate practical designs for the second-order consensus.

In this study, the consensus problem of second-order multi-agent systems (MAS) with position-only information is studied. Allowable sampling period for which second-order consensus can be achieved is obtained with two impulsive consensus algorithms. It is shown that if there is at least one eigenvalue of the Laplcian matrix with a non-zero imaginary part, consensus cannot be achieved for sufficiently small or large impulsive periods for both algorithms. Furthermore, the convergence performance of the MAS is optimised. Convergence speed, asymptotical decay factor and per-step decay factor of the error energy are utilised to investigate the convergence performance, and the relationship among impulsive period, topology structure and convergence performance is derived. Finally, numerical examples are given to validate our theoretical results.

This study is concerned with the problem of dynamical distributed consensus for multi-agent systems with nonlinear dynamics. Following the nearest neighbour rule, an adaptive consensus protocol is designed for such systems without using any global information, where the coupling weight of an agent from its neighbours adaptively updates according to the differences from the mean activity of the agent and its neighbours. The analysis shows that, under some mild assumptions, the adaptive law can achieve local and global consensus for any network with connected communication graph. Numerical simulations, illustrated by a common second-order consensus example, are performed to demonstrate the effectiveness of the presented results.

This paper focuses on the analytical study of final consensus convergence state of multi-agent dynamical systems by using a kind of generalized linear local interaction protocols. All the agents in the fixed directed network topology are governed by double-integrator dynamics. Almost all the existing linear local interaction consensus protocols can be considered as special cases of the present paper. By combining the algebraic graph theory and the matrix theory, some necessary and sufficient conditions are derived for reaching the second-order consensus. Moreover, the finial consensus convergence states of all agents are also be analytically determined. According to the obtained results, it is found that both the linear gains and the eigenvalues of the Laplacian matrix associated with the directed network topology play key roles in reaching consensus. Finally, the effectiveness and correctness of our theoretical findings are demonstrated by some numerical examples.

This study studies second-order consensus of multi-agent systems with noise in a leaderless architecture. Two distributed consensus algorithms are designed and sufficient conditions are established, which character how much the noise intensity or the delay multi-agent systems can stand such that second-order consensus can be reached almost surely for a given coupling strength and topology structure. Simulations are given to illustrate the effectiveness of the proposed consensus algorithms.