Northeastern University (China)

About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).

Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach

Abstract: In this paper, the inverse optimal approach is employed to design distributed consensus protocols that guarantee consensus and global optimality with respect to some quadratic performance indexes for identical linear systems on a directed graph The inverse optimal theory is developed by introducing the notion of partial stability As a result, the necessary and sufficient conditions for inverse optimality are proposed By means of the developed inverse optimal theory, the necessary and sufficient conditions are established for globally optimal cooperative control problems on directed graphs Basic optimal cooperative design procedures are given based on asymptotic properties of the resulting optimal distributed consensus protocols, and the multiagent systems can reach desired consensus performance (convergence rate and damping rate) asymptotically Finally, two examples are given to illustrate the effectiveness of the proposed methods

Stability Analysis of Markovian Jumping Stochastic Cohen–Grossberg Neural Networks With Mixed Time Delays

Abstract: In this letter, the global asymptotical stability analysis problem is considered for a class of Markovian jumping stochastic Cohen-Grossberg neural networks (CGNNs) with mixed delays including discrete delays and distributed delays. An alternative delay-dependent stability analysis result is established based on the linear matrix inequality (LMI) technique, which can easily be checked by utilizing the numerically efficient Matlab LMI toolbox. Neither system transformation nor free-weight matrix via Newton-Leibniz formula is required. Two numerical examples are included to show the effectiveness of the result.

Robust adaptive fault-tolerant control for uncertain linear systems with actuator failures

Abstract: This study is concerned with the robust adaptive fault-tolerant compensation control problem for linear systems with parameter uncertainty, disturbance and actuator faults including outage, loss of effectiveness and stuck. It is assumed that the lower and upper bounds of actuator efficiency factor, the upper bounds of disturbance and the unparametrisable time-varying stuck fault, are unknown. Then, according to the information from the adaptive mechanism, the effect of actuator fault, exogenous disturbance and parameter uncertainty can be eliminated completely by designing adaptive state feedback controller. Furthermore, it is shown that the solutions of the resulting adaptive closed-loop system are uniformly bounded, the states converge asymptotically to zero. Finally, two examples are given to illustrate the effectiveness and applicability of the proposed design method.