项目名称: 生物地理学智能同步优化算法及其在下肢假肢中的应用研究
项目编号: No.61305078
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 自动化技术、计算机技术
项目作者: 马海平
作者单位: 绍兴文理学院
项目金额: 24万元
中文摘要: 本项目旨在研究基于进化计算形成新的策略和理论,用于解决多关联复杂系统的优化问题,并应用于下肢假肢的智能同步优化设计。项目研究的内容包括:(1)实现生物地理学智能同步优化算法,建立其马尔科夫链模型,并在一定的假设条件下解决算法的收敛性和计算复杂度,建立算法的统计力学逼近模型,探索其潜在优化能力;(2)在马尔科夫链和统计力学逼近模型基础上,结合其它进化算法建立统一理论框架,比较分析各类算法的内在进化机理和优化性能;(3)实现下肢假肢的机械设计子系统和基于神经网络和模糊系统的智能控制子系统,并应用已建立的生物地理学智能同步优化算法对机械设计子系统和控制子系统进行同步优化和综合性能测试。项目的研究意义在于即丰富进化算法的理论知识,同时新的设计理论和方法能为截肢者设计出性能良好的下肢假肢,因此对改善残疾者生存条件具有非常重要的现实意义。
中文关键词: 进化计算;生物地理学;智能同步优化算法;马尔科夫链模型;下肢假肢
英文摘要: The goal of this proposed research is to develop new strategies and theories based on evolutionary computation for optimization of multiple related complex systems, and apply to intelligent synchronous optimization design of lower limb prosthesis. To achieve this goal, there are three specific objectives for the proposed research. The first objective is to set up biogeography-based intelligent synchronous optimization (BBISO) algorithm as a viable tool for the optimization of related complex systems, and establish its Markov chain model to solve convergence and computational complexity, and establish its statistical mechanics approximation model to explore potential performance. The second objective is to set up unified theoretical frameworks for various evolutionary algorithms based on Markov chain model and statistical mechanics approximation model to compare their essential evolving mechanisms and optimization performances. The third objective is to develop a mechanical design subsystem and an intelligent control subsystem based on neural networks and fuzzy logic for lower limb prosthesis, and apply the proposed BBISO algorithm to optimize synchronously these two subsystems, and achieve fabrication and test of prototype prosthesis. The most direct benefit of the proposed research is to enrich theoretical know
英文关键词: evolutionary computation;biogeography;intelligent synchronous optimization algorithm;Markov chain model;lower limb prosthesis