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首页> 外文期刊>Mechatronics, IEEE/ASME Transactions on >Mechatronic Design and Optimization Using Knowledge-Based Engineering Applied to an Inherently Unstable and Unmanned Aerial Vehicle
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Mechatronic Design and Optimization Using Knowledge-Based Engineering Applied to an Inherently Unstable and Unmanned Aerial Vehicle

机译：基于知识工程的机电设计和优化应用于固有不稳定和无人飞行器

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摘要

A novel design method for mechatronic systems, based on knowledge-based engineering techniques, is proposed in this research study. The method is particularly suited for mechatronic vehicles which are inherently unstable and require control systems for stabilization. The method is implemented in a dedicated software tool in which physical entities of the product are defined as classes with attributes. Nonphysical elements of the system and procedures for the design and analysis of the system are defined as functions with variables. The method has two key features. First, multiphysics simulation models and associated analysis functions are generated automatically within a multidisciplinary analysis and optimization framework. These models are not restricted to geometrical aspects for mechanical design, but also include the system architecture, dynamics, aerodynamics, electronic control systems and associated software codes. Second, for each representation of a design, a dedicated control system is developed completely automatically, based on the multiphysics simulation model, using model inversion control. These two features make it possible to analyze the dynamics and performance of inherently unstable mechatronic vehicles already in the early design phases when the vehicle is still subject to large configuration design changes. The method is demonstrated for the design of a multirotor unmanned aerial vehicle. Thirty thousand possible design solutions are evaluated by the system without manual interference. For each design, a dedicated control system is created and five flight test maneuvers are simulated in order to assess the aircraft performance and flying qualities. A global optimization process is applied for two conflicting requirements and the process is convergent at two optimum solutions.
机译：本研究提出了一种基于知识工程技术的机电系统新型设计方法。该方法特别适合于固有地不稳定并且需要用于稳定的控制系统的机电车辆。该方法在专用软件工具中实现，其中将产品的物理实体定义为具有属性的类。系统的非物理元素以及用于系统设计和分析的过程定义为具有变量的函数。该方法具有两个关键特征。首先，在多学科分析和优化框架内自动生成多物理场仿真模型和相关的分析功能。这些模型不仅限于机械设计的几何方面，还包括系统架构，动力学，空气动力学，电子控制系统和相关的软件代码。其次，对于设计的每种表示形式，基于多物理场仿真模型，使用模型求逆控制，可以完全自动开发专用的控制系统。这两个特征使得可以在早期设计阶段就对固有不稳定的机电一体化车辆进行动力学和性能分析，而该阶段仍然需要对车辆进行大的外形设计更改。演示了该方法用于多旋翼无人机的设计。系统评估了3万种可能的设计解决方案，而无需人工干预。对于每种设计，都会创建一个专用的控制系统，并模拟五次飞行测试操作，以评估飞机的性能和飞行质量。全局优化过程适用于两个相互矛盾的需求，并且该过程收敛于两个最优解决方案。

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