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1.
This paper deals with the problem of iterative learning control algorithm for a class of multi-agent systems with distributed parameter models. And the considered distributed parameter models are governed by the parabolic or hyperbolic partial differential equations. Based on the framework of network topologies, a consensus-based iterative learning control protocol is proposed by using the nearest neighbor knowledge. When the iterative learning control law is applied to the systems, the consensus errors between any two agents on L2 space are bounded, and furthermore, the consensus errors on L2 space can converge to zero as the iteration index tends to infinity in the absence of initial errors. Simulation examples illustrate the effectiveness of the proposed method.  相似文献   

2.
In this paper, we apply iterative learning control to both linear and nonlinear fractional-order multi-agent systems to solve consensus tacking problem. Both fixed and iteration-varying communicating graphs are addressed in this paper. For linear systems, a PDα-type update law with initial state learning mechanism is introduced by virtue of the memory property of fractional-order derivative. For nonlinear systems, a Dα-type update law with forgetting factor and initial state learning is designed. Sufficient conditions for both linear and nonlinear systems are established to guarantee all agents achieving the asymptotic output consensus. Simulation examples are provided to verify the proposed schemes.  相似文献   

3.
This paper is concerned with the distributed H∞-consensus control problem over the finite horizon for a class of discrete time-varying multi-agent systems with random parameters. First, by utilizing the proposed information matrix, a new formula is established to calculate the weighted covariance matrix of random matrix. Next, by allowing every agent to track the average of the neighbor agents, a novel local H∞-consensus performance constraint is presented to cater to the local performance analysis. Then, by means of the proposed definition of the stochastic vector dissipativity-like over the finite horizon, a set of sufficient conditions for every agent is obtained such that the controlled outputs of the closed-loop multi-agent systems satisfy the proposed H∞-consensus performance constraint. As a result, the proposed consensus control algorithm can be executed on each agent in an indeed distributed manner. Finally, a simulation example is employed to verify the effectiveness of the proposed algorithm.  相似文献   

4.
This work presents a framework of iterative learning control (ILC) design for a class of nonlinear wave equations. The main contribution lies in that it is the first time to extend the idea of well-established ILC for lumped parameter systems to boundary tracking control of nonlinear hyperbolic distributed parameter systems (DPSs). By fully utilizing the system repetitiveness, the proposed control algorithm is capable of dealing with time-space-varying and even state-dependent uncertainties. The convergence and robustness of the proposed ILC scheme are analyzed rigorously via the contraction mapping methodology and differential/integral constraints without any system dynamics simplification or discretization. In the end, two examples are provided to show the efficacy of the proposed control scheme.  相似文献   

5.
The finite-time positiveness and distributed control problem is studied for a class of Lipschitz nonlinear multi-agent systems. The objective is to design a suitable distributed controller which makes the closed-loop multi-agent systems be positive and finite-time stabilizable and satisfy the given H∞ performance index. Sufficient conditions are initially established on the existence of the finite-time distributed controller by using proper multiple Lyapunov functions and the design criteria are presented in the form of linear matrix inequalities. Finally, an example of multi-agent systems with six agents is presented to illustrate the feasibility and validity of the proposed methods.  相似文献   

6.
This paper investigates the consensus tracking problem of leader-follower multi-agent systems. Different from most existing works, dynamics of all the agents are assumed completely unknown, whereas some input-output data about the agents are available. It is well known from the Willems et al. Fundamental Lemma that when inputs of a linear time-invariant (LTI) system are persistently exciting, all possible trajectories of the system can be represented in terms of a finite set of measured input-output data. Building on this idea, the present paper proposes a purely data-driven distributed consensus control policy which allows all the follower agents to track the leader agent’s trajectory. It is shown that for a linear discrete-time multi-agent system, the corresponding controller can be designed to ensure the global synchronization with local data. Even if the data are corrupted by noises, the proposed approach is still applicable under certain conditions. Numerical examples corroborate the practical merits of the theoretical results.  相似文献   

7.
This paper considers distributed consensus problem of multi-agent systems consisting of general linear dynamics with a time-invariant communication topology. A distributed full-order observer type consensus protocol based on relative output measurements of neighbor agents is proposed. It is found that the consensus problem of linear multi-agent systems with a directed communication topology having a spanning tree can be solved if and only if all subsystems are asymptotically stable. Some necessary and sufficient conditions are obtained for ensuring consensus in multi-agent systems. The design technique is based on algebraic graph theory, Riccati inequality and linear control theory. Finally, simulation example is given to illustrate the effectiveness of the theoretical results.  相似文献   

8.
This study investigates the consensus tracking problem for unknown multi-agent systems (MASs) with time-varying communication topology by using the methods of data-driven control and model predictive control. Under the proposed distributed iterative protocol, sufficient conditions for reducing tracking error are analyzed for both time invariable and time varying desired trajectories. The main feature of the proposed protocol is that the dynamics of the multi-agent systems are not required to be known and only local input-output data are utilized for each agent. Numerical simulations are presented to illustrate the effectiveness of the derived consensus conditions.  相似文献   

9.
For multi-agent system (MAS), most of existing iterative learning control (ILC) algorithms consider about the tracking of reference defined over the whole trial interval, while the point-to-point (P2P) task, where the emphasis is placed on the tracking of intermediate time points, has not been explored. Thus, a distributed ILC method is proposed, in which each agent updates the feedforward control input by learning from the experience of itself and its neighbors in previous repeated tasks to achieve the goal of improving performance. In addition, for the sake of reducing the burden of data transmission in MAS, effective data quantization is essential. In this case, the quantitative measurement of the error of the tracking time points is further used in the ILC updating law. In order to accommodate this requirement, a distributed point-to-point iterative learning control (P2PILC) with tracking error quantization for MAS is first proposed in this paper. A necessary and sufficient condition is presented for the asymptotical stability of the proposed algorithm, and simulation results show the effectiveness of it finally.  相似文献   

10.
This paper investigates the leader-following consensus problem of time-invariant linear multi-agent systems with limited data rate. Based on the idea of assigning a priority level for each agent of the concerned multi-agent system, a novel distributed control law has been proposed. The proposed control law has two distinctive advantages. That is, it is fully distributed in the sense that it does not rely on the eigenvalues of the Laplace matrix associated with the topology. Moreover, the required data rate is independent of the number of agents and remains small even if the number of the agents in multi-agent systems is large. An example is finally given to illustrate the effectiveness of the proposed controller.  相似文献   

11.
This paper addresses the problem of cluster lag consensus for first-order multi-agent systems which can be formulated as moving agents in a capacity-limited network. A distributed control protocol is developed based on local information, and the robustness of the protocol is analyzed by using tools of Frobenius norm, Lyapunov functional and matrix theory. It is shown that when the root agents of the clusters are influenced by the active leader and the intra-coupling among agents is stronger enough, the multi-agent system will reach cluster lag consensus. Moreover, cluster lag consensus for multi-agent systems with a time-varying communication topology and heterogeneous multi-agent systems with a directed topology are studied. Finally, the effectiveness of the proposed protocol is demonstrated by some numerical simulations.  相似文献   

12.
The problem of finite-time consensus of linear multi-agent systems subject to input saturation is investigated and two control protocols are presented for leaderless and leader-following cases, respectively. The leaderless multi-agent systems with proposed non-smooth protocol can achieve consensus in finite time. The consensus protocol designed for leader-following case with directed topology can solve the finite-time consensus problem, where a priori constraint is adopted to deal with input saturation. Furthermore, the settling time is explicitly derived using finite-time Lyapunov theory. Finally, the effectiveness of the theoretical results is illustrated with several numerical simulations.  相似文献   

13.
This paper is concerned with a leader-follower consensus problem for networked Lipschitz nonlinear multi-agent systems. An event-triggered consensus controller is developed with the consideration of discontinuous state feedback. To further enhance the robustness of the proposed controller, modeling uncertainty and switching topology are also considered in the stability analysis. Meanwhile, a time-delay equivalent approach is adopted to deal with the discrete-time control problem. Particularly, a sufficient condition for the stochastic stabilization of the networked multi-agent systems is proposed based on the Lyapunov functional method. Furthermore, an optimization algorithm is developed to derive the parameters of the controller. Finally, numerical simulation is conducted to demonstrate the effectiveness of the proposed control algorithm.  相似文献   

14.
An improvement on the transient response of tracking for the sampled-data system based on an improved PD-type iterative learning control (ILC) is proposed in this paper. The developed analog ILC method and the high-gain property tracker design methodology are first combined to significantly reduce learning epochs and overcome the initial condition shift problem and discontinuous reference input in the traditional ILC. Besides, the proposed ILC improves the transient response and decreases the rate of weighting matrices QQ to RR under the traditional linear quadratic tracker design. First, the off-line observer/Kalman filter identification (OKID) is used to determine the appropriate (low-) order system parameters and state estimator for the physical system with unknown system equation, so that the model-based PD-type ILC can be implemented for practical applications. Then, to improve the transient response and decrease the control effort, the proportional difference type (PD-type) ILC algorithm is combined with the high-gain property linear quadratic tracker (LQT) design to construct the high performance tracker for the model-based sampled-data systems. Furthermore, the discrete-time version high performance tracker design for the unknown stochastic sampled-data system via the iterative learning control method is proposed in this paper based on the Euler method and the digital redesign approach. Finally, some examples are given for illustrating the effectiveness of the proposed method.  相似文献   

15.
In this work, a lifted event-triggered iterative learning control (lifted ETILC) is proposed aiming for addressing all the key issues of heterogeneous dynamics, switching topologies, limited resources, and model-dependence in the consensus of nonlinear multi-agent systems (MASs). First, we establish a linear data model for describing the I/O relationships of the heterogeneous nonlinear agents as a linear parametric form to make the non-affine structural MAS affine with respect to the control input. Both the heterogeneous dynamics and uncertainties of the agents are included in the parameters of the linear data model, which are then estimated through an iterative projection algorithm. On this basis, a lifted event-triggered learning consensus is proposed with an event-triggering condition derived through a Lyapunov function. In this work, no threshold condition but the event-triggering condition is used which plays a key role in guaranteeing both the stability and the iterative convergence of the proposed lifted ETILC. The proposed method can reduce the number of control actions significantly in batches while guaranteeing the iterative convergence of tracking error. Both rigorous analysis and simulations are provided and confirm the validity of the lifted ETILC.  相似文献   

16.
In this paper, the distributed consensus problem of leader-follower multi-agent systems with unknown time-varying coupling gains and parameter uncertainties are investigated, and the fully distributed protocols with the adaptive updating laws of periodic time-varying parameters are designed by using a repetitive learning control approach. By virtue of algebraic graph theory, Barbalat’s lemma and an appropriate Lyapunov-Krasovskii functional, it is shown that each follower agent can asymptotically track the leader even though the dynamic of the leader is unknown to any of them, i.e., the global asymptotic consensus can be achieved. At last, a simulation example is given to illustrate the feasibility and efficiency of the proposed protocols.  相似文献   

17.
This paper studies the consensus problem for a class of nonlinear multi-agent systems with asymmetric time-varying output constraints and completely unknown non-identical control directions. Firstly, in order to deal with the problem of asymmetric time-varying output constraints, the original output-constrained multi-agent systems are transformed into new unconstrained multi-agent systems by constructing the state transformation for each agent. Secondly, the emergence of multiple Nussbaum-type function terms is avoided by introducing novel sliding-mode-esque auxiliary variables and consensus estimate variables, which allows the control directions to be completely unknown non-identical. Thirdly, a novel control strategy is proposed by combining novel variables with state transformation method for the first time, which makes the design of distributed consensus protocol more concise. Through Lyapunov stability analysis, the proposed distributed protocol ensures that the output constraints are never violated and the consensus can be achieved asymptotically. Finally, a practical simulation example is given to demonstrate the effectiveness of the proposed distributed consensus protocol.  相似文献   

18.
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19.
《Journal of The Franklin Institute》2021,358(18):10004-10028
In this paper, the consensus problem is considered for multi-agent systems with input constraint under directed graphs, including leaderless and leader-following cases. Different from existing related works, the distinct feature of this paper is that both the amplitude and rate of the agents’ input are ensured in the given ranges. For the leaderless case, the saturation control strategy is designed and employed for multi-agent systems consensus with the aid of a novel saturation function. For the leader-following case, the saturation-function-based distributed observer as well as the observer-based saturation controller are proposed to achieve consensus. Finally, simulation results show the effectiveness of the designed methods.  相似文献   

20.
In this paper, a finite-horizon H∞ consensus control problem is studied for multi-agent systems under the limited energy constraint. Due to the limited energy, only a part of agents can use high energy to transmit information infallibly, and the remaining agents are randomly allocated low energy with several levels, which may lead to packet loss in some sense. Different levels result in different packet dropout probability. The purpose of this paper is to design a probability-dependent controller such that, for all probabilistic energy allocation and packet dropout, the H∞ consensus performance can be guaranteed for multi-agent systems over a finite horizon. To this end, a stochastic and high-availability energy allocation method is first presented via stratified multi-objective optimization methods and stochastic analysis methods. Based on this novel allocation, a H∞ consensus controller depending on the varying energy allocation is established. Furthermore, in terms of the probability information of both energy allocation and packet dropout, important results are obtained to guarantee the desired performance of the designed probability-dependent controller, and the controller are explicitly parameterized by means of the solutions to a set of linear matrix inequalities. Finally, a simulation example is utilized to illustrate the usefulness of the proposed controller design method.  相似文献   

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