首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 343 毫秒
1.
This paper considers a trilayer Stackelberg game problem for nonlinear system with three players. A novel performance function is defined for each player, which depends on the coupling relationships with the other two players. The coupled Hamilton–Jacobi–Bellman (HJB) equations are built from the performance functions, and the optimal control polices of three players are obtained based on the Bellman’s principle of optimality. Because of the nonlinearity and coupling characteristics, a policy iteration (PI) algorithm with a three-layer decision-making framework is developed to online learn the coupled HJB equations. In order to implement the algorithm, we construct a critic-action neural network (NN) structure and design a NN approximation-based iteration algorithm. Finally, a simulation example is presented to verify the effectiveness of the proposed method.  相似文献   

2.
《Journal of The Franklin Institute》2023,360(14):10564-10581
In this work, we investigate consensus issues of discrete-time (DT) multi-agent systems (MASs) with completely unknown dynamic by using reinforcement learning (RL) technique. Different from policy iteration (PI) based algorithms that require admissible initial control policies, this work proposes a value iteration (VI) based model-free algorithm for consensus of DTMASs with optimal performance and no requirement of admissible initial control policy. Firstly, in order to utilize RL method, the consensus problem is modeled as an optimal control problem of tracking error system for each agent. Then, we introduce a VI algorithm for consensus of DTMASs and give a novel convergence analysis for this algorithm, which does not require admissible initial control input. To implement the proposed VI algorithm to achieve consensus of DTMASs without information of dynamics, we construct actor-critic networks to online estimate the value functions and optimal control inputs in real time. At last, we give some simulation results to show the validity of the proposed algorithm.  相似文献   

3.
This paper investigates the consensus of fractional-order multiagent systems via sampled-data event-triggered control. Firstly, an event-triggered algorithm is defined using sampled states. Thus, Zeno behaviors can be naturally avoided. Then, a distributed control protocol is proposed to ensure the consensus of fractional-order multiagent systems, where each agent updates its current state based on its neighbors’ states at event-triggered instants. Furthermore, the pinning control technology is taken into account to ensure all agents in multiagent systems reach the specified reference state. With the aid of linear matrix inequalities (LMI), some sufficient conditions are obtained to guarantee the consensus of fractional-order multiagent system. Finally, numerical simulations are presented to demonstrate the theoretical analysis.  相似文献   

4.
This paper considers the problem of the leader-following consensus of generally nonlinear discrete-time multi-agent systems with limited communication channel capacity over directed fixed communication networks. The leader agent and all follower agents are with multi-dimensional nonlinear dynamics. We propose a novel kind of consensus algorithm for each follower agent based on dynamic encoding and decoding algorithms and conduct a rigorous analysis for consensus convergence. It is proved that under the consensus algorithm designed, the leader-following consensus is achievable and the quantizers equipped for the multi-agent systems can never be saturated. Furthermore, we give the explicit forms of the data transmission rate for the connected communication channel. By properly designing the system parameters according to restriction conditions, we can ensure the consensus and communication efficiency with merely one bit information exchanging between each pair of adjacent agents per step. Finally, simulation example is presented to verify the validity of results obtained.  相似文献   

5.
In this paper, a novel backstepping-based adaptive dynamic programming (ADP) method is developed to solve the problem of intercepting a maneuver target in the presence of full-state and input constraints. To address state constraints, a barrier Lyapunov function is introduced to every backstepping procedure. An auxiliary design system is employed to compensate the input constraints. Then, an adaptive backstepping feedforward control strategy is designed, by which the tracking problem for strict-feedback systems can be reduced to an equivalence optimal regulation problem for affine nonlinear systems. Secondly, an adaptive optimal controller is developed by using ADP technique, in which a critic network is constructed to approximate the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation. Therefore, the whole control scheme consists of an adaptive feedforward controller and an optimal feedback controller. By utilizing Lyapunov's direct method, all signals in the closed-loop system are guaranteed to be uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed strategy is demonstrated by using a simple nonlinear system and a nonlinear two-dimensional missile-target interception system.  相似文献   

6.
In the present paper, we study stochastic boundary control problems where the system dynamics is a controlled stochastic parabolic equation with Neumann boundary control and boundary noise. Under some assumptions, the continuity and differentiability of the value function are proved. We also define a new type of Hamilton–Jacobi–Bellman (HJB) equation and prove that the value function is a viscosity solution of this HJB equation.  相似文献   

7.
In this work, we consider an optimal control problem of a class of stochastic differential equations driven by additive noise with aftereffect appearing in control. We develop a semigroup theory of the driving deterministic neutral system and identify explicitly the adjoint operator of the corresponding infinitesimal generator. We formulate the time delay equation under consideration into an infinite dimensional stochastic control system without time lag by means of the adjoint theory established. Consequently, we can deal with the associated optimal control problem through the study of a Hamilton–Jacob–Bellman (HJB) equation. Last, we present an example whose optimal control can be explicitly determined to illustrate our theory.  相似文献   

8.
This paper considers the finite-time bipartite consensus problem governed by linear multiagent systems subject to input saturation under directed interaction topology. Due to the existence of input saturation, the dynamic performance of linear multiagent systems degrades significantly. For the improvement of the dynamic performance of systems, a dynamic gain scheduling control approach is proposed to design a dynamic Laplacian-like feedback controller, which can be obtained from the analytical solution of a parametric Lyapunov equation. Suppose that each agent is asymptotically null controllable with bounded control, and that the corresponding interaction topology of the signed directed graph with a spanning tree is structurally balanced. Then the dynamic Laplacian-like feedback control can ensure that linear multiagent systems will achieve the finite time bipartite consensus. The dynamic gain scheduling control can better improve the bipartite consensus performance of the linear multiagent systems than the static gain scheduling control. Finally, two examples are provided to show the effectiveness of the proposed control design method.  相似文献   

9.
In this paper, the data-driven adaptive dynamic programming (ADP) algorithm is proposed to deal with the optimal tracking problem for the general discrete-time (DT) systems with delays for the first time. The model-free ADP algorithm is presented by using only the system’s input, output and the reference trajectory of the finite steps of historical data. First, the augmented state equation is constructed based on the time-delay system and the reference system. Second, a novel data-driven state equation is derived by virtue of the history data composed of input, output and reference trajectory, which is considered as a state estimator.Then, a novel data-driven Bellman equation for the linear quadratic tracking (LQT) problem with delays is deduced. Finally, the data-driven ADP algorithm is designed to solve the LQT problem with delays and does not require any system dynamics. The simulation result demonstrates the validity of the proposed data-driven ADP algorithm in this paper for the LQT problem with delays.  相似文献   

10.
The goal of this paper is to propose an optimal fault tolerant control (FTC) approach for multi-agent systems (MASs). It is assumed that the agents have identical affine dynamics. The underlying communication topology is assumed to be a directed graph. The concepts of both inverse optimality and partial stability are further employed for designing the control law fully developed in the paper. Firstly, the optimal FTC problem for linear MASs is formulated and then it is extended to MASs with affine nonlinear dynamics. To solve the Hamilton-Jacobi-Bellman (HJB) equation, an Off-policy Reinforcement Learning is used to learn the optimal control law for each agent. Finally, a couple of numerical examples are provided to demonstrate the effectiveness of the proposed scheme.  相似文献   

11.
In this paper, a distributed control protocol is presented for discrete-time heterogeneous multi-agent systems in order to achieve formation consensus against link failures and actuator/sensor faults under fixed and switching topologies. A model equivalent method is proposed to deal with the heterogeneous system consists of arbitrary order systems with different parameters. Based on graph theory and Lyapunov theory, stability conditions to solve formation consensus problem are developed for the underlying heterogeneous systems with communication link failures. In order to tolerate actuator/sensor faults, a distributed adaptive controller is proposed based on fault compensation. The desired control is designed by linear matrix inequality approach together with cone complementarity linearisation algorithm. After applying the new control scheme to heterogeneous systems under the directed topologies with link failures and faults, the resulting closed-loop heterogeneous system is validated to be stable. The effectiveness of the new formation consensus control strategy and its robustness are verified by simulations.  相似文献   

12.
In this paper, the consensus tracking problem is studied for a group of nonlinear heterogeneous multiagent systems with asymmetric state constraints and input delays. Different from the existing works, both input delays and asymmetric state constraints are assumed to be nonuniform and time-varying. By introducing a nonlinear mapping to handle the problem caused by state constraints, not only the feasibility condition is removed, but also the restriction on the constraint boundary functions is relaxed. The time-varying input delays are compensated by developing an auxiliary system. Furthermore, by utilizing the dynamic surface control method, neural network technology and the designed finite-time observer, the distributed adaptive control scheme is developed, which can achieve the synchronization between the followers’ output and the leader without the violation of full-state constraints. Finally, a numerical simulation is provided to verify the effectiveness of the proposed control protocol.  相似文献   

13.
This paper deals with the leader-follower finite-time consensus problem for multiagent systems with nonlinear dynamics via intermittent protocol. The topological structure of the followers is undirected or balanced digraph. Different from most existing works concerning nonlinear dynamics (satisfies Lipschitz continuity), the nonlinear dynamics of each agent satisfies Hölder continuity in this paper. In light of the finite-time control technique, the intermittent control protocol is designed to reach accurate leader-follower finite-time consensus. It is justified that the leader-follower finite-time consensus can be realized if the length of communication is greater than a critical value by using limit theory. Finally, two numerical examples are exhibited to validate the effectiveness of the proposed scheme.  相似文献   

14.
A distributed linear-quadratic-regulator (LQR) semistability theory for discrete-time systems is developed for designing optimal semistable controllers for discrete-time coupled systems. Unlike the standard LQR control problem, a unique feature of the proposed optimal control problem is that the closed-loop generalized discrete-time semistable Lyapunov equation can admit multiple solutions. Necessary and sufficient conditions for the existence of solutions to the generalized discrete-time semistable Lyapunov equation are derived and an optimization-based design framework for distributed optimal controllers is presented.  相似文献   

15.
This paper investigates adaptive finite-time practical consensus protocols for a class of second-order multiagent systems with a positive odd power, nonsymmetric input dead zone and uncertain dynamics under a directed communication topology. In this study, three major steps are employed to address the existence of the positive odd power, nonsymmetric input dead zone and uncertain dynamics. Overall, based on the technique of adding one power integrator, useful preliminary results are obtained by configuring a suitable fraction power. Furthermore, to circumvent input dead-zone nonlinearity, an adaptive fuzzy logic (FL) method is used to estimate the width of the dead zone. Finally, the difficulty in designing finite-time practical consensus protocols for the multiagent systems with uncertain dynamics is handled by using radial basis function neural networks (RBFNNs) to approximate the related unknown nonlinear functions. Then, given some reasonable assumptions, it is shown that finite-time practical consensus of the second-order multiagent systems is obtained by using the proposed distributed control protocols and adaptive laws. In addition, the proper approach for selecting parameters is provided such that the neighborhood position error and parameter estimate errors for each agent converge to predesigned small regions of the origin in a finite time. The effectiveness of the developed algorithm is finally validated through a numerical simulation.  相似文献   

16.
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   

17.
This paper investigates the consensus problem of discrete-time networked multi-agent systems (DNMASs) with a directed topology and communication delay, where exact state and output of each agent are not measured, and yet output differences between agent and its neighboring ones (relative outputs for short) are available. Based on the networked predictive control scheme and relative output data, a novel protocol is proposed to overcome the effect of delay on the consensus actively. Moreover, for the DNMASs with a fixed topology and constant communication delay, delay-independent necessary and/or sufficient conditions of achieving consensus are obtained, which reveal that the essence of dominating the consensus is agents' dynamics and communication topology. Simulation results further demonstrate the effectiveness of theoretical results.  相似文献   

18.
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   

19.
Maintaining the given operational area is critical in guaranteeing the safety of nonlinear second-order multiple autonomous agents. The properties of multiagent systems and several physical constraints, including bounded modeling error and actuator saturation, dramatically affect the maneuverability of multiagent systems inside the specified operational area. Moreover, the existing safety control algorithms heavily rely on the boundaries of the operational area. To overcome this issue, by constructing a novel scalable control technique, the safety area for multiagent systems can be transformed into input-constrained control barriers along each coordinate of motion for agents. It is shown that the safety of each agent and the global asymptotic stability are guaranteed under the proposed distributed control algorithm. The asymmetrical closed-form scheme for the agent's safety rule is built by applying the adjustable low and high bounds of the control signals associated with the actual control inputs, which are repeatedly computed by using new local measurements as the agents move, and the saturated control inputs with asymmetrical constraints are ensured. The absolute values of the modeling errors and external disturbances can be tracked by the proposed safety controller. Super-twisting control (STC) is employed to address the formation constraint problem of multiagent systems, where the effect that arises from uncertain nonlinear complexity of the agents and external disturbances is eliminated. Moreover, finite-time convergence, a desirable robust behavior of multiagent systems, and the formation constraint are simultaneously achieved. Furthermore, the stability of the proposed integrated control strategy for multiagent systems is analyzed, which reveals that the proposed distributed safety control can seamlessly integrate with the robust control protocol with minimum modification under the directed information interaction topology. Safety formation control calibration and tuning are carried out, and comparative simulation results are provided to illustrate the effective performance of the obtained theoretical results.  相似文献   

20.
This paper deals with the leader-following consensus problem of multi-agent systems with the consideration that each agent can only transmit its position state to the neighbors at irregular discrete sampling times. In the proposed algorithm, a continuous-discrete time observer is designed for the continuous estimation of both position and velocity from the discrete position information of the neighbors. These estimated states are then used for designing a continuous control law which solves the leader-following consensus problem. Moreover, the dynamics of the leader is not fixed and can be controlled through an external input. The stability analysis has been carried out by employing the Lyapunov approach which provides sufficient conditions to tune the parameters according to the maximum allowable sampling period. The developed algorithm has been simulated and then tested on an actual multi-robot system consisting of three differential drive wheeled robots. Both simulation and hardware results validate the effectiveness of the control algorithm.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号