基于遗传算法的机器人负载重力补偿优化算法研究

航空航天装配领域,利用安装在机器人末端的六维力传感器来感知外力是实现工业机器人柔顺装配的关键技术之一,而负载的存在会干扰对外力的感知.针对工业机器人末端负载的重力补偿,提出一种基于遗传算法的重力补偿优化算法.此方法以误差平方和最小为目标建立了最优解模型,利用遗传算法求解,最终可以在不使用测量仪器的情况下,估计力传感器安...     

一种开放式数据清理框架

从提高制造业信息化中数据质量的角度出发,分析了建立基于规则库和算法库的可扩展数据清理框架的必要性,设计了一种基于多种规则结合不同算法以流程方式完成清理任务的可重构的数据清理框架。在框架的设计中,以实例方式总结了数据质量问题的分类,详细阐述了该框架的结构、组成部分以及工作流程。最后,通过数据清理实例说明了该框架中流程的实现及其工作过程。本文提出的数据清理框架功能将随着不同领域清理任务的完成而不断完善。     

基于遗传算法和序列二次规划法的结构稳健性优化设计方法

针对目前结构优化设计方法未考虑参数随机性的问题,提出基于遗传算法和序列二次规划法的结构稳健性优化设计方法。将结构产品的质量特性作为优化目标,性能函数的可靠度指标作为约束条件,建立稳健性优化设计模型。利用序列二次规划法计算其性能函数的可靠度指标,在此基础上,利用遗传算法进行迭代计算,得出最优设计结果。最后,将某型导引头导轨齿轮设计作为工程案例,验证了使用此结构稳健性优化设计方法能够降低产品重量,提高结构稳健性。     

Gaussian fitting based optimal design of aircraft mission success space using multi-objective genetic algorithm

In order to obtain the optimized aircraft design concept which meets the increasingly complex operation environment at the conceptual design stage, System-of-systems (SoS) engineering must be considered. This paper proposes a novel optimization method for the design of aircraft Mission Success Space (MSS) based on Gaussian fitting and Genetic Algorithm (GA) in the SoS area. First, the concepts in the design and evaluation of MSS are summarized to introduce the Contribution to System-of-Systems (CSS) by using a conventional effectiveness index, Mission Success Rate (MSR). Then, the mathematic modelling of Gaussian fitting technique is noted as the basis of the optimization work. After that, the proposed optimal MSS design is illustrated by the multi-objective optimization process where GA acts as the search tool to find the best solution (via Pareto front). In the case study, a simulation system of penetration mission was built. The simulation results are collected and then processed by two MSS design schemes (contour and neural network) giving the initial variable space to GA optimization. Based on that, the proposed optimization method is implemented under both schemes whose optimal solutions are compared to obtain the final best design in the case study.     

Optimum design and experiment of composite leaf spring landing gear for electric aircraft

The composite leaf spring landing gear of an electric aircraft is optimized. With the strength and workability as constraints and the minimum structural weight as an objective, the two-stage optimization of the leaf spring landing gear with glass fiber unidirectional prepreg is carried out using a genetic algorithm, namely, the optimization of continuous thickness of layup, and the optimization of the layup sequence and discrete thickness. In the optimization process, the ground loads are calculated according to the structural stiffness of each chromosome, thus the stiffness constraints are relaxed, and the optimization results are compared with those using stiffness constraints. The static experiment verification reveals that the numerical simulation and experimental results are consistent, that is, the optimized leaf spring meets the strength requirements. The results show that the leaf spring landing gear based on two-stage optimization method achieves the objective of weight reduction.     

A data transmission scheduling algorithm for rapid-response earth-observing operations

With the development of rapid-response Earth-observing techniques, the demand for reducing a requirements-tasking-effects cycle from 1 day to hours grows rapidly. For instance, a satellite user always wants to receive requested data in near real-time to support their urgent mis- sions, such as dealing with wildfires, volcanoes, flooding events, etc. In this paper, we try to reduce data transmission time for achieving this goal. The new feature of a responsive satellite is that users can receive signals from it directly. Therefore, the traditional satellite control and operational tech- niques need to be improved to accommodate these changes in user needs and technical upgrading. With that in mind, a data transmission topological model is constructed. Based on this model, we can deal with the satellite data transmission problem as a multi-constraint and multi-objective path- scheduling problem. However, there are many optional data transmission paths for each target based on this model, and the shortest path is preferred. In addition, satellites represent scarce resources that must be carefully scheduled in order to satisfy as many consumer requests as possible. To efficiently balance response time and resource utilization, a K-shortest path genetic algorithm is proposed for solving the data transmission problem. Simulations and analysis show the feasibility and the adaptability of the proposed approach.     

民用飞机飞行试验任务优化技术研究与实现

针对具有复杂耦合关系的试飞任务难以进行全局优化的问题,提出了一种计算机辅助任务优化方法,该方法将复杂的试飞任务优化问题分解为多项串联问题,然后采用启发式算法(A*算法)和遗传算法相结合的混合遗传算法获得试飞任务单的较优组合,并以此为基础实现对试飞任务进行全局优化。工程应用表明,通过使用该方法获得的试飞任务优化结果置信度高,可有效缩短飞行试验任务周期和降低试验成本。     

基于遗传算法的平流层飞艇航迹规划方法研究

文章针对平流层飞艇驻空阶段航迹规划问题进行研究和仿真分析.考虑平流层飞艇自身飞行的特点,建立其运动学方程和风场模型,并在适当假设基础上,构造能够反映其飞行能耗的代价函数.最后采用遗传算法进行算例计算,求解平流层飞艇最优轨迹.仿真结果表明,遗传算法能够有效、快速地收敛并稳定至问题的最优解;其所构造的代价函数能够反映飞艇自...     

基于遗传算法的高超声速曲面压缩进气道反设计

结合计算流体力学和遗传算法,建立了一种高超声速曲面压缩进气道的反设计方法。根据压力分布反设计了压缩型面。结果表明,该曲面压力分布与目标压力分布符合良好,从而验证了反设计方法的正确性。采用此反设计方法,设计了某高超声速曲面压缩进气道,并和等熵压缩二维进气道进行了比较。研究发现,在其它性能参数几乎相等情况下,曲面压缩进气道总压恢复较等熵压缩基准进气道提高9.7%,长度缩短5.6%。吞入23mm前体附面层后,基准进气道不起动,而曲面压缩进气道总压恢复系数仅下降5.4%,表现出良好的吞附面层能力。     

测量船工况智能设计策略

针对以往海上测控方案中测量船工况设计存在的不足及后续测控工作的需要，以测量船工作弧段要求及历史数据为前提，以天线增益、航线保障等多个约束条件为设计要素，结合设计流水线、知识表达、模糊综合评估、遗传算法等多种设计方法，提出了一种智能化的测量船工况设计策略。