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This article investigates distributed optimization of high‐order nonlinear multi‐agent systems (MASs) with disturbance under switching topologies. First, we propose a class of new distributed control algorithms for high‐order MASs under switching topologies, such that all agents asymptotically reach consensus at the unique minimizer of the sum of cost functions. Then, by constructing disturbance observer, the proposed algorithms are extended to address distributed optimization problems for high‐order nonlinear MASs with disturbance under switching topologies. In particular, both of new presented methods do not require optimal reference signal generator, which can save the computational resources of systems. In final, simulations are conducted to validate the theoretical results. [ABSTRACT FROM AUTHOR]

Existing distributed finite‐time optimization algorithms for continuous‐time multi‐agent systems require either undirected graphs or weight balanced digraphs, and distributed finite‐time optimization problems for weight unbalanced digraphs are still great challenging. Thus, the distributed finite‐time optimization problems for continuous‐time multi‐agent systems with strongly convex local cost functions are investigated under directed graphs in this article. First, a distributed finite‐time gradient estimator is constructed by using non‐smooth analysis and algebraic graph theory, then distributed finite‐time optimization algorithms and piecewise distributed finite‐time optimization algorithms are proposed based on the designed gradient estimator. The new proposed distributed finite‐time optimization algorithms which only require strongly connected graphs relax the balanced requirement. Furthermore, the communication bandwidth of systems could be saved by deploying the proposed piecewise distributed finite‐time optimization algorithms since the information exchange in the optimization process is reduced. Finally, simulation examples are given to verify the effectiveness of proposed distributed optimization algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with distributed finite-time optimisation of multi-agent systems with unknown high-frequency gain signs under switching digraphs. First, a distributed finite-time gradient estimator-based optimal signal generator is constructed by adopting finite-time stability theory and graph theory. Then, considering the existence of unknown high-frequency gain signs in multi-agent systems, we propose new distributed asymptotic optimisation algorithms via the Nussbaum-type function. Additionally, in order to accelerate convergence, the novel distributed finite-time optimisation algorithms are presented. Both of the newly proposed algorithms can realise optimal consensus of multi-agent systems with unknown high-frequency gain signs under switching digraphs. Finally, two simulation examples are illustrated to verify the proposed algorithms. [ABSTRACT FROM AUTHOR]

In this article, the adaptive output consensus problem of high-order nonlinear heterogeneous agents is addressed using only delayed, sampled neighbor output measurements. A class of auxiliary variables is introduced which are $n$ -times differentiable functions and include the agent’s output along with delayed, sampled output neighbor measurements. It is proven that if these variables are bounded and regulated to zero then asymptotic consensus among all agent outputs is ensured. In view of this property, an adaptive distributed backstepping design procedure is presented that guarantees boundedness and regulation of the proposed variables. This design procedure ensures not only the desired asymptotic output consensus but also the uniform boundedness of all closed-loop variables. The main feature of our approach is that, in the proposed control law for each agent, the entire state vector of the neighbors is not needed and only delayed sampled measurements of the neighbors’ outputs are utilized. The simulation results are also presented that verify our theoretical analysis. [ABSTRACT FROM AUTHOR]

Existing results for cooperative control of high-order agents mainly employ the Nussbaum-type function to cope with unknown control directions and mostly require an assumption that the control directions are identical and unknown. This paper proposes a class of algorithms with nonlinear PI functions to relax such an assumption and make them suitable for nonidentical unknown control directions. It is proven that if the distributed nonlinear PI functions are suitably selected, the proposed algorithms can achieve consensus for high-order agents under strongly connected topologies and switching topologies with a jointly strongly connected basis (JSCB). Furthermore, we extend the consensus results to the case of time-varying topologies described by $\delta $ -connected, continuous graphs. As a special case, the consensus of high-order agents under the directed graph having a spanning tree is also investigated. Finally, illustrative simulations are presented to indicate the efficiency of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the adaptive cooperative control problem with guaranteed convergence for a class of nonlinear multiagent systems with unknown control directions and time-varying topologies. A key lemma is first derived which involves dynamically changing interaction topologies, and then a new kind of distributed control algorithms with Nussbaum-type functions are proposed based on this lemma. It is proven that if the topologies are time varying with integral weight uniform upper bound and reciprocity, then convergence is guaranteed with the proposed algorithms for nonlinear multiagent systems with nonidentical unknown control directions. An important feature of this paper is that, under time-varying topologies, the designed algorithms can deal with nonidentical unknown control directions by using classical Nussbaum-type functions. Moreover, with the proposed algorithms, we extend the adaptive cooperative control results to the case of $\delta $ -connected graphs. In particular, the adaptive leaderless consensus of high-order nonlinear agents with nonidentical unknown control directions and a directed graph having a spanning tree is also tackled as a special case. Finally, theoretical results are illustrated by a group of Genesio–Tesi systems with distributed control algorithms under time-varying topologies and some special network topologies. [ABSTRACT FROM AUTHOR]

This paper solves the adaptive consensus problem for first-order linearly parameterized agents with completely nonidentical unknown high-frequency gain signs under directed graphs. A new class of Nussbaum-type function-based algorithms are proposed to handle the unknown high-frequency gain signs adaptively and cooperatively. It is shown that if the underlying topology is a fixed graph with strongly connected or switching topologies having a jointly strongly connected basis, the first-order linearly parameterized agents with nonidentical unknown high-frequency gain signs can achieve asymptotic consensus. Finally, the effectiveness of proposed algorithms are verified by one simulation example. [ABSTRACT FROM AUTHOR]

This paper solves the robust output synchronization problem for a group of linear agents subject to constant disturbances on directed graphs. A new distributed control protocol with integral action is first proposed with the assumption that each agent has access to its own state. Then, an observer-based implementation of the control protocol is illustrated for the case that the agents do not have access to their states. Compared with existing methods, the new distributed protocol does not require exchanging of the controller states or output states among neighboring agents. Finally, simulation results of a group of low-speed experimental unmanned aerial vehicles show the effectiveness of the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper addresses the exponential consensus problem of single-integrator agents with saturated protocols on directed graphs. By employing an integral Lyapunov function, the exponential consensus problem of single-integrator agents is solved under the directed graph with strongly connected or a spanning tree. The main contribution is that under the directed graph, some conditions for exponential consensus with saturated protocols are first obtained. Finally, two examples are used to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of leader‐following consensus of single‐integrator agents subject to saturation constraints. Global leader‐following consensus protocol is developed with proper choice of the relative coupling gain. Both the case of input saturation and the case of actuator saturation are considered. It is shown that global consensus of the multiagent system can be reached under the general undirected graph provided that its augmented graph contains a directed spanning tree. Numerical examples are provided to demonstrate the theoretical results. [ABSTRACT FROM AUTHOR]