In this paper, an online optimal distributed learning algorithm is proposed to solve leader-synchronization problem of nonlinear multi-agent differential graphical games. Each player approximates its optimal control p...In this paper, an online optimal distributed learning algorithm is proposed to solve leader-synchronization problem of nonlinear multi-agent differential graphical games. Each player approximates its optimal control policy using a single-network approximate dynamic programming(ADP) where only one critic neural network(NN) is employed instead of typical actorcritic structure composed of two NNs. The proposed distributed weight tuning laws for critic NNs guarantee stability in the sense of uniform ultimate boundedness(UUB) and convergence of control policies to the Nash equilibrium. In this paper, by introducing novel distributed local operators in weight tuning laws, there is no more requirement for initial stabilizing control policies. Furthermore, the overall closed-loop system stability is guaranteed by Lyapunov stability analysis. Finally, Simulation results show the effectiveness of the proposed algorithm.展开更多
The problem of stabilizing multiple independent linear systems sharing one common network cable is presented and solved. Both the quantization and time sequencing are studied in the field of control over networks by p...The problem of stabilizing multiple independent linear systems sharing one common network cable is presented and solved. Both the quantization and time sequencing are studied in the field of control over networks by providing the formulated stabilizing sufficient condition which illustrates the relationship between the system instability, quantization and time sequencing,and the data rate is also presented in terms of the quantization and time sequencing. A numerical example is given to illustrate the result.展开更多
文摘In this paper, an online optimal distributed learning algorithm is proposed to solve leader-synchronization problem of nonlinear multi-agent differential graphical games. Each player approximates its optimal control policy using a single-network approximate dynamic programming(ADP) where only one critic neural network(NN) is employed instead of typical actorcritic structure composed of two NNs. The proposed distributed weight tuning laws for critic NNs guarantee stability in the sense of uniform ultimate boundedness(UUB) and convergence of control policies to the Nash equilibrium. In this paper, by introducing novel distributed local operators in weight tuning laws, there is no more requirement for initial stabilizing control policies. Furthermore, the overall closed-loop system stability is guaranteed by Lyapunov stability analysis. Finally, Simulation results show the effectiveness of the proposed algorithm.
基金This work was financially supported by China Scholarship Council (21937016)
文摘The problem of stabilizing multiple independent linear systems sharing one common network cable is presented and solved. Both the quantization and time sequencing are studied in the field of control over networks by providing the formulated stabilizing sufficient condition which illustrates the relationship between the system instability, quantization and time sequencing,and the data rate is also presented in terms of the quantization and time sequencing. A numerical example is given to illustrate the result.
