Based on the strategy of information feedback from followers to the leader, flocking control of a group of agents with a leader is studied. The leader tracks a pre-defined trajectory and at the same time the leader uses the feedback information from followers to the leader to modify its motion. The advantage of this control scheme is that it reduces the tracking errors and improves the robustness of the team cohesion to followers＇ faults. The results of simulation are provided to illustrate that information feedback can improve the performance of the system.
This paper proposes second-order consensus protocols and gives a measure of the robustness of the protocols to the time-delays existing in the dynamics of agents with second-order dynamics. By employing a frequency domain method, it is proven that the information states achieve second-order consensus asymptotically for appropriate time-delay if the topology of the network is connected. Particularly, a nonconservative upper bound on the fixed time-delay that can be tolerated is found. The consensus protocols are distributed in the sense that each agent only needs information from its neighboring agents, which makes the proposed protocols scalable. It reduces the complexity of connections among agents significantly. Simulation results are provided to verify the effectiveness of the theoretical results for second-order consensus in networks in the presence of time-delays existing in the dynamics of agents.
This paper deals with the problems of robust stochastic stabilization and H-infinity control for Markovian jump nonlinear singular systems with Wiener process via a fuzzy-control approach. The Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear singular system. The purpose of the robust stochastic stabilization problem is to design a state feedback fuzzy controller such that the closed-loop fuzzy system is robustly stochastically stable for all admissible uncertainties. In the robust H-infinity control problem, in addition to the stochastic stability requirement, a prescribed performance is required to be achieved. Linear matrix inequality (LMI) sufficient conditions are developed to solve these problems, respectively. The expressions of desired state feedback fuzzy controllers are given. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed method.
Aiqing ZHANG 1 , Huajing FANG 2 (1.College of Mathematics and Computer Science, Jianghan University, Wuhan Hubei 430056, China
