Cooperative and Adaptive Mechatronic Systems: Identification, Control, and Optimization

协作和自适应机电系统：识别、控制和优化

• 批准号: RGPIN-2016-04340
• 负责人: Fidan, Baris
• 金额: $ 2.11万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=638775
• 关键词: Cooperative; Adaptive; Mechatronic; Systems; Identification

The proposed research program focuses on distributed parameter identification, control and optimization of dynamic mechatronic systems, using novel cooperative and adaptive approaches for a class of tasks, including (i) on-line parameter identification of mechatronic systems, e.g. autonomous cars or mobile robotic platforms, via onboard sensor networks; (ii) coordination and control of mechatronic multi-agent (vehicle/robot/work unit) systems (MASs); (iii) extremum seeking. For such tasks, the program will develop widely applicable sets of (a) effective distributed high level algorithms, (b) sensor and actuator network architectures, and (c) low level practical controllers for running the algorithms on various mechatronic MASs. All outcomes will be produced with guaranteed stability, performance, and robustness, via constructive mathematical analysis and real-time testing and verification on automotive, multi-vehicle, reconfigurable robot, and sensor network test platforms.

该研究计划的重点是动态机电系统的分布式参数识别、控制和优化，采用新型的协作和自适应方法来完成一类任务，包括：（i）通过车载传感器网络在线识别机电系统的参数，例如自主汽车或移动的机器人平台;（ii）机电多智能体（车辆/机器人/工作单元）系统（MAS）的协调和控制;（iii）极值搜索。对于这些任务，该计划将开发广泛适用的（a）有效的分布式高级算法，（B）传感器和执行器网络架构，以及（c）用于在各种机电MAS上运行算法的低级实用控制器。所有结果都将通过在汽车、多车辆、可重构机器人和传感器网络测试平台上进行建设性的数学分析和实时测试与验证，确保稳定性、性能和鲁棒性。