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1.
This paper addresses the challenging problem of decentralized adaptive control for a class of coupled hidden leader-follower multi-agent systems, in which each agent is described by a nonlinearly parameterized uncertain model in discrete time and can interact with its neighbors via the history information from its neighbors. One of the agents is a leader, who knows the desired reference trajectory, while other agents cannot receive the desired reference signal or are unaware of existence of the leader. In order to tackle unknown internal parameters and unknown high-frequency gains, a projection-type parameter estimation algorithm is proposed. Based on the certainty equivalence principle and neighborhood history information, the decentralized adaptive control is designed, under which, the boundedness of identification error is guaranteed with the help of the Lyapunov theory. Under some conditions, it is shown that the multi-agent system eventually achieves synchronization in the presence of strong couplings. Finally, a simulation example is given to support the results of the proposed scheme.  相似文献   

2.
In this paper, the containment control problem of heterogeneous uncertain high-order linear Multi-Agent Systems (MASs) is addressed and solved via a novel fully-Distributed Model Reference Adaptive Control (DMRAC) approach, where each follower computes its adaptive control action on the basis of local measurements, information shared with neighbors (within the communication range) and the matching errors w.r.t. its own reference model, without requiring any previous knowledge of the global directed communication topology structure. The approach inherits the robustness of the direct model reference adaptive control (MRAC) scheme and allows all agents converging towards the convex hull spanned by leaders while fulfilling at the same time local additional performance requirements at single-agent level, such as prescribed settling time, overshoot, etc. The asymptotic stability of the whole closed-loop network is analytically derived by exploiting the Lyapunov theory and the Barbalat lemma, hence proving that each follower converges to the convex hull spanned by the leaders, as well as the boundedness of the adaptive gains. Extensive numerical analysis for heterogeneous MAS composed of stable, unstable and oscillating agent dynamics are presented to validate the theoretical framework and to confirm the effectiveness of the proposed approach.  相似文献   

3.
In this paper, we study the cooperative consensus control problem of mixed-order (also called hybrid-order) multi-agent mechanical systems (MMSs) under the condition of unmeasurable state, unknown disturbance and constrained control input. Here, the controlled mixed-order MMSs are consisted of the mechanical agents having heterogeneous nonlinear dynamics and even non-identical orders, which means that the agents can be of different types and their states to be synchronized can be not exactly the same. In order to achieve the ultimate synchronization of all mixed-order followers, we present a novel distributed adaptive tracking control protocol based on the state and disturbance observations. Wherein, a distributed state observer is used to estimate the followers’ and their neighbors’ unmeasurable states. And, a novel estimated-state-based disturbance observer (DOB) is proposed to reduce the effect of unknown lumped disturbance for the mixed-order MMSs. The proposed control protocol and observers are fully distributed and can be calculated for each follower locally. Lyapunov theory is used for proving the stability of the proposed control algorithm and the convergence of the cooperative tracking errors. A practical cooperative longitudinal landing control example of unmanned aerial vehicles (UAVs) is given to illustrate the effectiveness of the presented control protocol.  相似文献   

4.
《Journal of The Franklin Institute》2023,360(13):10100-10126
This paper studies the distributed optimal coordinated control problem for Euler–Lagrange multi-agent systems with connectivity preservation. The aim is to force agents to achieve the optimal solution minimizing the sum of the local objective functions while guaranteeing the connectivity of the communication graph. For practical purposes, the gradient vector of the local objective function is allowed to use only at the real-time generalized position instead of at the auxiliary system state. To make the control parameters independent of the global information and guarantee the fully distributed manner of controller, the adaptive control is introduced to update the coupling weights of the relative states among neighbors. Moreover, to reduce the resource for control updates, the event-driven communication is employed for the updates of both the relative states and the gradient of the connectivity-preserving potential function. Based on the Lyapunov analysis framework, it is proved that agents can converge to the optimal solution with connectivity preservation and Zeno behavior is excluded for the two event-triggering conditions. Finally, the effectiveness of the proposed method is verified by a numerical simulation example.  相似文献   

5.
In this paper, we investigate the output synchronization of networked SISO nonlinear systems that can be transformed into semi-strict feedback form. Due to parameter uncertainty, the agents have heterogeneous dynamics. Combined backstepping method together with graph theory, we construct an augmented Laplacian potential function for analysis and a distributed controller is designed recursively for each agent such that its output can be synchronized to its neighbors' outputs. The distributed controller of each agent has three parts: state feedback of itself, neighborhood information transmitted through the network and adaptive parameter updaters both for itself and its neighbors. Moreover, distributed tuning function is designed to minimize the order of the parameter updater. It is proved that when the undirected graph is connected, all agents’ outputs in the network can be synchronized, i.e., cooperative output synchronization of the network is realized. Simulation results are presented to verify the effectiveness of the proposed controllers.  相似文献   

6.
《Journal of The Franklin Institute》2019,356(18):11581-11604
A solution is provided in this paper for the adaptive approximate consensus problem of nonlinear multi-agent systems with unknown and non-identical control directions assuming an underlying graph topology having a spanning tree. This is achieved with the introduction of a novel variable transformation called PI consensus error transformation. The new variables include the position error of each agent from some reference trajectory chosen by him, which represents the agent’s selection for the desired swarm trajectory, along with an integral term of the weighted total displacement of the agent’s position from all neighbor positions. It is proven that if these new variables are bounded and regulated to zero, then asymptotic approximate consensus among all agents is ensured. Using classical Nussbaum gain based techniques, distributed controllers are designed to regulate the PI consensus error variables to zero and ultimately solve the approximate agreement problem. The proposed approach also allows for a specific calculation of the final consensus trajectory based on the controller parameter selection and the associated graph topology. It is shown that all agent positions converge towards a neighborhood of the weighted average of all agents reference trajectories. Simulation results verify our theoretical derivations.  相似文献   

7.
This paper investigates the problem of cooperative tracking for Lur’e systems under directed spanning tree topology. First, a control protocol is proposed to achieve cooperative tracking consensus by a distributed observer, which utilizes only the states of neighboring agents based on the event-triggering conditions with mixed node and edge. Then, an improved tracking protocol is developed by considering the case that only the outputs of neighbors can be obtained. With the aid of adaptive updating parameters, the two protocols do not utilize the minimum eigenvalue of Laplacian matrix, and can deal with the nonlinear dynamics of Lur’e systems in a fully distributed manner. Moreover, with the Lyapunov analysis framework, the tracking errors can be proved to converge to zero in both cases. Zeno behavior is excluded from the event-triggering conditions containing states and outputs of neighbors. Finally, the effectiveness of the proposed protocols is verified by two numerical simulations.  相似文献   

8.
This paper studies the cooperative fault-tolerant formation control problem of tracking a dynamic leader for heterogeneous multiagent systems consisting of multipile unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults under switching directed interaction topologies. Based on local neighborhood formation information, the distributed fault-tolerant formation controllers are constructed to ensure that all follower UAVs and UGVs can accomplish the demanding formation configuration in the state space and track the dynamic leader’s trajectory. By incorporating the sliding mode control and adaptive control technique, the actuator faults and unknown parameters of follower agents can be compensated. Through the theoretical analysis, it is proved that the cooperatively semiglobally uniformly ultimately boundedness of the closed-loop system is guaranteed, and the formation tracking errors converge to a small adjustable neighborhood of the origin. A simulation example is introduced to show the validity of the proposed distributed fault-tolerant formation control algorithm.  相似文献   

9.
In this paper, we consider the distributed optimization problems with linear coupling constraint of general homogeneous and heterogeneous linear multi-agent systems under weighted-balanced and strongly connected digraphs. In order to control all agents converge to the optimal output, we propose distributed control laws, therein, the optimal output can make the global cost function reach minimum. Then we guarantee the convergence of the proposed algorithms by the properties of Laplacian matrix and Lyapunov stability theorem. Furthermore, we extend the result of heterogeneous linear multi-agent system to the case that dynamics of agents are subject to external disturbances, and prove that the algorithm designed by internal model principle can make all agents reach the optimal output exactly. Finally, we provide examples to illustrate the effectiveness of the proposed distributed algorithms.  相似文献   

10.
This paper considers the distributed adaptive fault-tolerant control problem for linear multi-agent systems with matched unknown nonlinear functions and actuator bias faults. By using fuzzy logic systems to approximate the unknown nonlinear function and constructing a local observer to estimate the states, an effective distributed adaptive fault-tolerant controller is developed. Furthermore, different from the traditional method to estimate the weight matrix, only the weight vector needs to be estimated by exchanging the order of weight vectors and fuzzy basis functions in the fuzzy logic systems. In contrast to the existing results, the assumption that the dimensions of input vector and output vector are equal is removed. In addition, it is proved that the proposed control protocol guarantees all signals in the closed-loop systems are bounded and all agents converge to the leader with bounded residual errors. Finally, simulation examples are given to illustrate the effectiveness of the proposed method.  相似文献   

11.
This paper develops a new dual ML-ADHDP method to solve the optimal consensus problem (OCP) of a class of heterogeneous discrete-time nonlinear multi-agent systems (MASs) with unknown dynamics and time delay. A hierarchical and distributed control strategy is used to transform the original problem into nonlinear model reference adaptive control (MRAC) problems and an OCP of virtual linear MASs. For the nonlinear MRAC problems, a new multi-layer action-dependent heuristic dynamic programming (ML-ADHDP) method is developed to overcome the unknown dynamics and neural network estimation errors, which has higher control accuracy. In order to solve the OCP of virtual linear MASs and improve the convergence speed, a new multi-layer performance index is proposed. Then the ML-ADHDP method is used to solve the coupled Hamiltonian–Jacobi–Bellman equation and obtain the optimal virtual control. Theoretical analysis proves that the original MASs can achieve Nash equilibrium, and simulation results show that the developed dual ML-ADHDP method ensures better convergence speed and higher control accuracy of original MASs.  相似文献   

12.
In this paper, the distributed adaptive fault estimation issue using practical fixed-time design is investigated for attitude synchronization control systems. A distributed fault estimation observer is proposed based on the fixed-time technique. Meanwhile, a novel fixed-time adaptive fault estimation algorithm is also constructed to guarantee convergence rate and improve estimation rapidity. The fault estimation error is uniformly ultimately bounded and is practically fixed-time stable, which converges to the neighborhood of the origin in a fixed time. Finally, simulation results of an attitude synchronization control system are presented to verify the effectiveness of proposed techniques.  相似文献   

13.
Time-varying edge weights represent dynamical interactions between any two nodes in multi-agent systems (MASs). In this paper, we consider a synchronization problem for heterogeneous MASs over directed graphs with time-varying edge weights from a control-theoretic perspective. We seek for an adaptive control protocol that drives the synchronization error in the presence of time-varying edge weights to converge in terms of asymptotic stability. We propose a class of observer networks for estimating leaders and output regulation equation solvers built on directed graphs with time-varying edge weights. Finally, we use a simulation study to verify the effectiveness of the proposed protocol.  相似文献   

14.
This paper discusses adaptive synchronization control for complex networks interacted in an undirected weighted graph, and aims to provide a novel and general approach for the design of distributed update laws for adaptively adjusting coupling weights. The proposed updating laws are very general in the sense that they encompass most weight update laws reported in the literature as special cases, and also provide new insights in the analysis of network system evolution and graph weight convergence. We show a rigorous proof for the synchronization stability of the overall complex network to a synchronized state, and demonstrate the convergence of adaptive weights for each edge to some bounded constants. A detailed comparison with available results is provided to elaborate the new features and advantages of the proposed adaptive strategies as compared with conventional adaptive laws. The effectiveness of the proposed approach is also validated by several typical simulations.  相似文献   

15.
This paper addresses the problem of bipartite output consensus of heterogeneous multi-agent systems over signed graphs. First, under the assumption that the sub-graph describing the communication topology among the agents is connected, a fully distributed protocol is provided to make the heterogeneous agents achieve bipartite output consensus. Then for the case that the topology graph has a directed spanning tree, a novel adaptive consensus protocol is designed, which also avoids using any global information. Each of these two protocols consists of a solution pair of the regulation equation and a homogeneous compensator. Numerical simulations show the effectiveness of the proposed approach.  相似文献   

16.
The tracking problem of high-order nonlinear multi-agent systems (MAS) with uncertainty is solved by designing adaptive sliding mode control. During the tracking process, node failures are possible to occur, a new agent replaces the failed one. Firstly, a distributed nonsingular terminal sliding mode(NTSM) control scheme is designed for the tracking agents. A novel continuous function is designed in the NTSM to eliminate the singularity and meanwhile guarantee the estimation of finite convergence time. Secondly, the unknown uncertainties in the tracking agents are compensated by proposing an adaptive mechanism in the NTSM. The adaptive mechanism adjusts the control input through estimating the derivative bound of the unknown uncertainties dynamically. Thirdly, the tracking problem with node failures and agent replacements is further investigated. Based on the constructed impulsive-dependent Lyapunov function, it is proved that the overall system will track the target in finite time even with increase of jump errors. Finally, comparison simulations are conducted to illustrate the effectiveness of proposed adaptive nonsingular terminal sliding mode control method for tracking systems suffering node failures.  相似文献   

17.
This article investigates the rendezvous problem of heterogeneous multi-agent systems against Denial-of-Service attacks with preserving initial connectivity under a dynamic communication topology. The algorithm of resisting Denial-of-Service attack is first introduced to connectivity-preserving rendezvous problem of heterogeneous multi-agent systems. First of all, in order to observe the information of the leader, the distributed observers are designed to estimate the state of the leader with the communication network in the presence of Denial-of-Service attack by adaptive algorithm. Then, a switching system model is constructed by taking into account the influence of Denial-of-Service attacks. By means of the obtained model combined with a artificial potential function technique, the proposed distributed control algorithm allows all agents to accomplish rendezvous assignment with connectivity preservation as well as resisting Denial-of-Service attacks. Finally, detailed simulation validates the effectiveness of the proposed distributed observer and controller algorithm.  相似文献   

18.
《Journal of The Franklin Institute》2019,356(17):10196-10215
This paper deals with the large category of convex optimization problems on the framework of second-order multi-agent systems, where each distinct agent is assigned with a local objective function, and the overall optimization problem is defined as minimizing the sum of all the local objective functions. To solve this problem, two distributed optimization algorithms are proposed, namely, a time-triggered algorithm and an event-triggered algorithm, to make all agents converge to the optimal solution of the optimization problem cooperatively. The main advantage of our algorithms is to remove unnecessary communications, and hence reduce communication costs and energy consumptions in real-time applications. Moreover, in the proposed algorithms, each agent uses only the position information from its neighbors. With the design of the Lyapunov function, the criteria about the controller parameters are derived to ensure the algorithms converge to the optimal solution. Finally, numerical examples are given to illustrate the effectiveness of the proposed algorithms.  相似文献   

19.
This paper investigates the problem of complete synchronization of chaotic systems with unknown parameters. An adaptive control scheme based on a feedback passivity approach is proposed. The convergence of the synchronization error is guaranteed. The unified chaotic and hyperchaotic Lü systems are taken as illustrative examples. The feasibility and effectiveness of the proposed scheme are demonstrated through numerical simulations.  相似文献   

20.
This paper studies the problem of composite synchronization and learning of multiple coordinated robot manipulators subject to heterogeneous nonlinear uncertain dynamics under the leader-follower framework. A new two-layer distributed adaptive learning control scheme is proposed, which consists of the first-layer distributed cooperative estimator and the second-layer decentralized deterministic learning controller. The first layer aims to enable each robotic agent to estimate the leader’s information. The second layer is responsible for not only controlling each individual robotic agent to track over desired reference trajectory, but also accurately identifying/learning each robot’s nonlinear uncertain dynamics. Design and implementation of this two-layer distributed controller can be carried out in a fully-distributed manner, which do not require any global information including global connectivity of the communication network. The Lyapunov method is applied to rigorously analyze stability and parameter convergence of the resulting closed-loop system. Numerical simulations on a team of two-degree-of-freedom robot manipulators have been conducted to demonstrate the effectiveness of the proposed results.  相似文献   

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