Liu Derong

Policy iteration optimal tracking control for chaotic systems by using an adaptive dynamic programming approach

A policy iteration algorithm of adaptive dynamic programming (ADP) is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then, the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks, the developed optimal tracking control scheme for chaotic systems is verified by a simulation.

Consensus protocol for multi-agent continuous systems ⁄

Based on the algebraic graph theory, the networked multi-agent continuous systems are investigated. Firstly, the digraph (directed graph) represents the topology of a networked system, and then a consensus convergence criterion of system is proposed. Secondly, the issue of stability of multi-agent systems and the consensus convergence problem of information states are all analysed. Furthermore, the consensus equilibrium point of system is proved to be global and asymptotically reach the convex combination of initial states. Finally, two examples are taken to show the efiectiveness of the results obtained in this paper.

An adaptive control method for a class of uncertain nonlinear systems with ferromagnetic hysteresis nonlinearity

This paper deals with the tracking problem of a class of uncertain nonlinear systems with ferromagnetic hysteresis nonlinearity, in which the adaptive backstepping control method is presented. The ferromagnetic hysteresis model is approximated using a linear input and a bounded nonlinear disturbance of which the bound is unknown. The designed controller guarantees that the output of the system tracks a desired signal and the tracking error converges to a small bound. The stability of the closed loop system is proved under the Lyapunov stability theory. Simulation example is given to illustrate the effectiveness of the scheme.