基于概率盒演化的时变系统不确定性量化方法研究

为了研究时变系统的不确定性量化和传递问题,提出了一种概率盒演化方法。根据系统的时变规律,获取系统响应的累积分布函数随时间变化的规律。将认知不确定性参数和随机不确定性参数分离在外层和内层,用蒙特卡洛法量化外层的认知不确定性参数,用基于随机配点的非嵌入式混沌多项式法量化内层的随机不确定性参数,通过求取不同时刻系统响应的累积分布函数的上下边界,创建时变概率盒。最后,通过一延时电路性能退化算例,验证了该方法的有效性。研究表明,时变概率盒不仅表征了系统特定时刻的混合不确定性,而且反映了输出响应的时变规律和输出不确定性随时间变化的趋势。国家自然科学基金(Grant No.51505398);;\n国家自然科学基金委员会与中国工程物理研究院联合基金资助(Grant No.U1530122

The Machine that Lives Forever

Design an intelligent micromachine that can self-power and sustain from environmental energy scavenging to achieve an autonomous device that can communicate at will with peers indefinitely. Explore sleep/wake hibernation strategies coupled with food scavenging off-grid traits to identify the tightest work to sleep efficiency schedule, incorporating adaptive reconfiguration to manage significant environmental impacts. Capture, store and manage background radiations and stray RF signals to feed on in a continued effort to make intelligent survival decisions and oversee management protocols. Ensure that every micro Watt of usable energy gets extracted from every part of the harvest and then forward-scheduled it for productive use. Finally, employ natures tricks and experience to introduce essential personality traits, pursuing maximising survival numbers and increasing dispersal target area sizes of large self-sufficient wireless sensor deployments. This research intends to provide a closely coupled software-hardware foundation that aids implementers in intelligently harnessing and using tiny amounts of ambient energy in a highly autonomous way. This platform then continues on to explore ways of maximising the efficient usage of the harvested energy using various hibernation/wake strategies and then making objective comparisons with proposed intelligent energy management protocols. Finally, the protocol extends to enable the device to manage its personal survival possibilities so the devices can use an evolutional personality-based approach to deal with the unknown environmental situations they will encounter. This work examines a machine that can self-power and sustain from environmental energy scavenging with the aim to live forever. Living forever implies a brain (microcontroller) that can manage energy and budget for continuous faculty. With these objectives, sleep/wake/hibernation and scavenging strategies are examined to efficiently schedule resources within a transient environment. Example harvesting includes induced and background radiation. Intelligent, biologically-inspired strategies are adopted in forward-scheduling strategies given temporal energy relative to the machine’s function (the Walton)