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

该研究计划主要研究动态机电系统的分布式参数辨识、控制和优化，使用新的协作和自适应方法来处理一类任务，包括(I)通过车载传感器网络在线辨识机电系统的参数，例如自动汽车或移动机器人平台；(Ii)机电多智能体(车辆/机器人/工作单元)系统(MASS)的协调和控制；(Iii)极值搜索。对于这样的任务，该计划将开发一套广泛适用的(A)有效的分布式高级算法，(B)传感器和执行器网络体系结构，以及(C)用于在各种机电一体化质量上运行算法的低级实用控制器。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和验证，所有结果都将在保证稳定性、性能和健壮性的情况下产生。

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.