Fault-Diagnosis Applications;Model-Based Condition Monitoring;Actuators, Drives, Machinery, Plants, Sensors;

2020年nips model-based reinforcement learning相关论文集合

Systems and enterprises (often referred to as systems-of-systems) that employ multiple advanced technologies and achieve ever-higher levels of complexity have become mainstays of the modern world. Managing the complexity of these systems, especially to create solutions to the needs of system users and other stakeholders within acceptable cost and schedule, is a recurring challenge to the Systems Engineering (SE) community. Spectacular progress in mechanical and electronic devices, materials, sensors, energy generation and control, vehicles and propulsion, communications and networking, computing and software, and many other fields creates both new capabilities and new demands for tools and methods to effectively exploit them. Communities as diverse as the sciences, commercial enterprises, education, government, academia, and the military frequently report that programs aimed at delivering new capabilities based on advanced technology have overrun their budgets and schedules, failed to meet their objectives, or simply overwhelmed the capabilities of system developers and users.

系统性能和产品质量要求的不断提高和成本效率的不断提高，技术过程的复杂性和自动化程度不断提高。这一发展需要更多的系统安全性和可靠性。今天，围绕自动系统设计的一个最关键的问题是系统的可靠性。提高系统可靠性和可靠性的传统方法是提高单个系统组件（如传感器、执行器、控制器或计算机）的质量、可靠性和鲁棒性。即使如此，也无法保证系统的无故障运行。因此，过程监控和故障诊断正成为现代自动控制系统的组成部分，并且通常由立法机构规定。自20世纪70年代初开始，基于模型的故障诊断技术得到了显著的发展。在工业过程和自动控制系统中的大量成功应用证明了其在动态系统故障检测中的有效性。如今，基于模型的故障诊断系统已完全集成到车辆控制系统、机器人、运输系统、电力系统、制造业公共关系中。

Steven Ding_Model-based Fault Diagnosis Techniques 故障诊断经典参考资料

AADL Model-Based Engineering

滴滴在2017年KDD的论文，新鲜出炉的，和大家一起学习一下