報告時間：2023年12月19日（周二）上午10:00-12:00
報告地點(diǎn)：船電樓A306會議室
報告摘要： Physical attackers pose significant danger to the operation of intelligent vehicles, especially multiagent systems (MASs). Therefore, how to guarantee safety and performance of MAS in the presence of physical attackers is an important topic to be addressed. State-of-the-art literature on constrained multiagent system operations can only deal with constant or at best time-varying constraint requirements. Such constraint formulations cannot respond well to the dynamic environment and presence of physical attackers. In this work, we consider a formation tracking problem for a group of unmanned aerial vehicles (UAVs) in the presence of a physical attacker. The safety/performance constraint functions are environment-aware and dynamic in nature, whose formulation depends on certain path parameters and presence of the attacker. The dependence on path ensures adaptation to the dynamic operation environment. The dependence on the attacker ensures swift adjustment based on the relative distances between the attacker and agents. UAV desired paths and desired path speeds can also be both path- and attacker-dependent. A framework where composite barrier functions are incorporated with path parameter timing laws has been proposed to address the safety and performance considerations. Adaptive laws and neural networks are used to approximate unknown attacker velocity, unknown system parameters and external disturbances are estimated by adaptive laws. The proposed formation architecture can ensure formation tracking errors converge exponentially to small neighborhoods near the equilibrium, with all constraint requirements met. At the end a simulation study further illustrates the proposed scheme and demonstrates its efficacy.
報告專家簡介: 金旭博士，美國肯塔基大學(xué)助理教授、博士生導(dǎo)師。2013年獲得新加坡國立大學(xué)電子計(jì)算機(jī)專業(yè)一等榮譽(yù)學(xué)士學(xué)位，2015年獲得加拿大多倫多大學(xué)電子計(jì)算機(jī)專業(yè)碩士學(xué)位，2018年獲得美國佐治亞理工大學(xué)數(shù)學(xué)碩士學(xué)位，2019年獲得美國佐治亞理工大學(xué)航天工程博士學(xué)位。2019年至今在美國肯塔基大學(xué)機(jī)械工程系工作。發(fā)表論文60余篇，引用量3300余次。獨(dú)立主持美國國家自然科學(xué)基金（NSF）項(xiàng)目一項(xiàng)，并多次擔(dān)任美國國家自然科學(xué)基金委評審專家。另主持美國航空航天局（NASA）州級項(xiàng)目一項(xiàng)。金博士在各個領(lǐng)域?qū)W科綜合排名的斯坦福全球“2022年度科學(xué)影響力排行榜”排名7562。
船舶電氣工程學(xué)院
2023年12月18日
