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Distributed Robust Control for Nonlinear Systems using Wireless Neural Control
Wen Ren,Bugong Xu 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.5
This paper is concerned with the synthesis of a class of nonlinear system over the wireless neural control network (WNCN) which refers to a group of neuron nodes interacting with each other by radio connection. The nonlinear system is modeled by a standard neural network model (SNNM) which is the interconnection of a linear dynamic system and bounded static nonlinear operators. The WNCN treats itself as a fully distributed nonlinear dynamic controller. The unreliable wireless communication links within WNCN are modeled by fading channels. By constructing appropriate discrete-time Lyapunov function, the global asymptotic stability of the closed-loop system is discussed in particular for the cases with stochastic perturbations induced by packet losses. The connection weights among the neuron nodes that guarantee stability of the system can be obtained by solving a convex optimization problem with some linear matrix inequality (LMI) constraints. A numerical example is given to illustrate the correctness and effectiveness of the theoretical results.
Zhijun Li,Kun Yang,Stjepan Bogdan,Bugong Xu 제어·로봇·시스템학회 2013 International Journal of Control, Automation, and Vol.11 No.6
Aiming for a better dynamic performance from the robot beyond the physical limits set by the manufacturers, in this paper we propose to integrate the robot dynamics into motion planning and then to approximate the robot joint torques using parameterized B-splines. By introducing a high-dimensional non-linear fitness function, we transform the motion planning problem into an optimiza-tion of a non-linear fitness function, and then we develop the approach based on Support Area Level Set Algorithm (SALAS). It integrates dual-stage sampling strategies to avoid early convergence in a small search field and to improve the rate of convergence to the potential solution. The effectiveness of the proposed approach has been verified by the simulation of a two-link robotic manipulator.
Junhua Huang,Liding Chen,Xuhuan Xie,Mufeng Wang,Bugong Xu 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.8
This paper investigates the distributed consensus problem for heterogeneous multi-agent systems via event-triggered scheme. To alleviate the communication burden, a distributed event-triggered consensus algorithm using an open-loo estimate and neighboring information is proposed. In the proposed event-triggered scheme, the control input of each agent is dependent on the estimate and information at discrete instants. Firstly, the novel event-triggered consensus algorithm is proposed for fixed topology, which involves the discrete communication between neighboring agents. Then, for the switching topology, the triggering condition is proposed by virtue of a topology-dependent dwell time approach. Further, the corresponding consensus procedures are given. Finally, the effectiveness of the proposed scheme is illustrated by numerical results.