Intelligent Automated Modular Design Synthesis of Mechatronic Systems

机电一体化设计是一门集多个工程学科于一体的学科，在科研和工业领域发挥着越来越重要的作用。在机电一体化系统中，多领域部件源于机械、电子和控制工程，在一个产品中形成特殊的集成和功能交互。多领域组件之间的集成要求使得工程师很难从整体上理解设计任务，并且这种固有的复杂性给他们的创造力带来了巨大的压力，因为他们需要不断开发新的和改进的产品。现有的计算机辅助设计（CAD）解决方案可以在一定程度上帮助他们；但它们仍然是被动的工具，主要依靠自己的知识。因此，更智能和动态的CAD支持是非常可取的，为此，人工智能可以通过设计自动化帮助实现这一目标。

Mechatronics design integrates several engineering disciplines in one system and plays an increasingly important role in both research and industry. In a mechatronic system, multi-domain components stem from mechanical, electronics and control engineering to form a special integration and a functional interaction in one product. The integration required among the multi-domain components makes it difficult for engineers to understand the design task as a whole, and this inherent complexity puts great strain on their creativity as they constantly need to develop new and improved products. Existing Computer Aided Design (CAD) solutions can help them to a certain extent; but they remain passive tools relying mainly on their own knowledge. Therefore, more intelligent and dynamic CAD support is highly desirable and to this end, Artificial Intelligence can help achieve this through design automation. The MAIN objective of this research program is to develop automated solutions based on artificial evolution to support mechatronics engineers in their design task. However, a major drawback lies in the fact that automatically generated solutions, while valid, are generally very complex and cumbersome and end up not being considered as usable design alternatives by engineers. The HYPOTHESIS underlying this research program is that simpler/more modular artificially evolved design candidates will be used by engineers as valid design alternatives. The added modularity would allow designers to shuffle between and re-use subsystems for increased design flexibility and product functionality. The FIRST axis of research in this program will provide optimized artificial evolution solutions that offer engineers new, simpler and usable design alternatives, and in order to mitigate models’ complexity levels, modularity principles will be integrated in the evolution. We will embed modularity as a full part of the artificial evolution of new design candidates trough the definition of new mechatronics-related modularity indexes. Additionally, Mechatronic systems models will be automatically generated using a building-block modular approach. The automated design support solutions will be using evolutionary computing techniques inspired from nature such as genetic programming and genetic algorithms in order to synthesis new mechatronic systems that meet design specifications subject to various constraints. Moreover, to reduce the design space to feasible solutions only, the developed evolutionary design solution will be constrained by an intelligent decision support system. This will allow the engineers to get more design alternatives in faster times. The constraining of the design candidates’ domain and the optimization of the artificial evolution performances represents the SECOND axis of this research program. Finally, the THIRD axis of this research program deals with validation. To this end, two relevant real-word examples will be investigated, in terms of Micro-Electro-Mechanical systems and a robotic arm manipulator. Our proposed approach offers excellent perceptive of success because it extends the spectrum of solutions for design engineers by offering new alternatives of mechatronic designs that are both feasible and simple enough to understand, use and re-use.