具有奇异特性的多模型混杂系统的神经网络控制研究

项目名称： 具有奇异特性的多模型混杂系统的神经网络控制研究

项目编号： No.61263005

项目类型： 地区科学基金项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 龙飞

作者单位： 贵州大学

项目金额： 44万元

中文摘要： 针对具有奇异特性的多模态混杂系统的本质特征（系统的当前状态可能会超出现有各子模态所构成的状态空间、各子模型之间进行确定切换或以概率转移以及随机的外部干扰等），利用神经网络强大的学习能力和非线性逼近能力，结合传统自适应控制和现有混杂控制理论和方法，研究具有奇异特性的多模态混杂系统的神经网络自适应混杂控制新理论和新方法。针对具有不同结构的奇异多态型混杂对象，设计合理的神经网络结构和自适应神经网络混杂控制算法，快速准确地对该类系统进行多模态建模和在线调整以及模型优化的研究；设计性能更好的、更具"自适应" 特性的新的多模态神经网络混杂控制系统；研究该类混杂控制系统中同时存在建模误差、切换脉冲和奇异特性等特征的自适应鲁棒混杂控制决策策略。通过本课题的研究，努力在理论上发展智能控制理论以及混杂系统新的控制方法和思想，对混杂系统的控制与设计起一定的推动作用。

中文关键词： 奇异特性；多模型；切换系统；神经网络控制；系统建模

英文摘要： For the essential characteristics of the multi-models hybrid systems with singular characteristics (for example, the current state of the system may be go beyond the sum of state space of existing every sub-model, certain switching or transferring in probability between from a sub-model to another, as well as randomly exterior disturbance, etc.), a new theory and method, which is with regard to neural network adaptive hybrid control of such system, is investigated via the combination of powerful learning and nonlinear approximation ability of neural network as well as the traditional adaptive control and existing hybrid control. Aim at Singular multi-models hybrid object with different structure, we will design the reasonable neural network architectures and adaptive neural network hybrid control algorithm so that such system can be modeled quickly and accurately, adjusted online and optimized; a new multi-modal neural network hybrid control system with better performance and more adaptive characteristics is designed; the adaptive robust hybrid control decision-making strategy of such hybrid control system, which exists in the modeling errors, switching impulsion and singular characteristics, is discussed in-depth. The development of intelligent control and hybrid systems control would be accelerated in theory v

英文关键词： Singular Characteristics；Multi-models；Switched Systems；Neural Networks Control；System Modelling