网络约束环境下Lagrange系统多目标协调的分析与控制及其应用

The primary object of this project is devoted to analysis and control of multi-objective coordination in networked Lagrange systems under complex constrained environments and its applications. On the basis of our recent work related to coordinated dynamics and control in hybrid networked Lagrange systems, the main research issues are as follows: Firstly, based on the general structures and characteristics of agent's Lagrange dynamics, the project tries theoretically to establish the more general protocols and algorithms of group consensus or cluster synchronization in networked Lagrange systems over the communication and input constraints respectively, then deeply to explore the group or cluster coordination mechanism of the network systems and as well as its evolution rules. Secondly, by aiming at the flexible manipulator formulated by Lagrange dynamics from the view of application, the project intends to put forward the more effective distributed adaptive control strategies for the networked flexible manipulator systems subjected to the structure and target constraints, so as to implement the desired cooperative control task of trajectory tracking and path planning at all. Furthermore, it should be believed that the research of this project not only illustrate cooperative evolution mechanism and control coordinated principle of the representative robot networked systems described by Lagrange dynamics, but also will provide some new insights and methods for both novation and design of the modern intelligent robot systems in practical applications.

本项目主要研究复杂网络约束环境下Lagrange系统多目标协调动力学的分析与控制及其应用，在申请者近期关于混杂Lagrange 网络系统协调动力学与控制已有工作的基础上，从理论上基于一般Lagrange个体动力学结构和特征，在具有通讯和输入约束下建立网络化Lagrange系统分群一致性或者聚类同步协议和算法，探索系统分群或者聚类协调动力学机制及其演化规律，从应用上针对由Lagrange动力学所表征柔性机械手臂为对象，在不同结构和目标约束下设计有效分布式自适应控制策略，从而实施所期望的轨迹跟踪与路径规划的协同目标.本项目的研究有助于揭示以机器人为载体网络化Lagrange系统的合作演化机制与协调控制原理, 同时为应用到现代智能机器人系统创新与设计提供新的思想和新的方法.

本项目主要研究复杂网络环境约束下Lagrange 系统多目标协调动力学的分析、计算、控制和优化及其应用。本项目在网络化Lagrange 系统分群或者聚类协调动力学机制以及分布式区域路径规划和编队控制等方面取得一系列原创性的研究成果，本项目研究内容具体总结为如下几个方面: 一、网络化Lagrange系统分群一致性与聚类涌现机制，二、网络化Lagrange系统多目标协调区域可达控制，三、Lagrange系统分布式区域编队控制集群智能算法，四、多个非完整机器人系统自适应一致性追踪控制策略。此外，在具有miRNA 基因调控网络振荡表达的动力学机制以及复杂动力网络随机分布同步与控制等方面也取得了一些重要进展。本项目的研究有助于揭示以协作多机器人为载体网络化Lagrange系统的合作演化机制与协调控制原理, 同时为应用到现代智能机器人系统创新与设计提供新的思想和方法。