An investigation into the aircraft flight simulation and control system is presented in this paper. The study was firstly focused on the establishment of an integrated hardware-in-the-loop（HITL） platform for aircraf...An investigation into the aircraft flight simulation and control system is presented in this paper. The study was firstly focused on the establishment of an integrated hardware-in-the-loop（HITL） platform for aircraft flight simulation based on MATLAB/Simulink ＋ dSPACE. The platform combines the abundant software and hardware resources of dSPACE simulation platform to simulate the flight attitude of an aircraft in six-DOF （ degree of freedom） motion. Based on the platform, the study was then focused on the flight numerical simulation by taking a loitering aerial vehicle as an example. An aircraft mathematical model was created for a modular design and off-line numerical simulation based on MATLAB/Simulink. Finally, the study was focused on the control system design of the loitering aerial vehicle and conduct of an HITL simulation experiment for the vehicle pitch control. The experiment verifies the system design and control effectiveness. Research results show that the dSPACE simulation system provides a real time good experimental platform to improve the efficiency of study and development of a flight control system.展开更多
文章探讨基于Diffusion Transformer(DiT)算法的生成式人工智能(AIGC)技术在微短剧创作中的应用及影响。研究发现,AIGC技术明显降低了影视创作门槛,推动了微短剧创作模式革新。然而,该技术的局限性限制了作品的艺术表现力。文章分析AIG...文章探讨基于Diffusion Transformer(DiT)算法的生成式人工智能(AIGC)技术在微短剧创作中的应用及影响。研究发现,AIGC技术明显降低了影视创作门槛,推动了微短剧创作模式革新。然而,该技术的局限性限制了作品的艺术表现力。文章分析AIGC技术与微短剧发展逻辑的契合点,明确其在成本控制、创作效率提升和叙事特点适配方面的优势。同时,探究AIGC技术引发的影视创作模式变革,强调“人在回路”(human in the loop,HITL)理念的重要性,并指出创作流程的非线性化对传统影视制作模式的冲击。研究结果表明,AIGC技术推动了创作团队架构的变革,催生了自组织行为、分布式决策和局部交互等“群集系统”特征,增强了创作的灵活性和抗干扰性。然而,其生成过程的随机性和对艺术修辞理解的不足,使得创作者难以精准把控视听语言,导致作品在情感表达和细节处理上存在不足。部分AIGC微短剧过度依赖视觉奇观和技术仪式感,忽视了故事内容的深度和情感共鸣,削弱了作品的艺术价值。AIGC技术虽为微短剧创作带来了便利,但其应用需在工具理性和艺术表达之间寻求平衡。技术应服务于艺术创作,而非主导创作。未来,创作者需不断探索技术与艺术的结合点,发挥AIGC技术的优势,打破其局限性,推动微短剧高质量发展,为文化传播提供创新路径。展开更多
To enhance the fidelity and accuracy of the simulation of communication networks,hardware-in-the-loop（HITL） simulation was employed.HITL simulation methods was classified into three categories,of which the merits an...To enhance the fidelity and accuracy of the simulation of communication networks,hardware-in-the-loop（HITL） simulation was employed.HITL simulation methods was classified into three categories,of which the merits and shortages were compared.Combing system-in-the-loop（SITL） simulation principle with high level architecture（HLA）,an HITL simulation model of asynchronous transfer mode（ATM） network was constructed.The throughput and end-to-end delay of all-digital simulation and HITL simulation was analyzed,which showed that HITL simulation was more reliable and effectively improved the simulation credibility of communication network.Meanwhile,HLA-SITL method was fast and easy to achieve and low-cost during design lifecycle.Thus,it was a feasible way to research and analyze the large-scale network.展开更多
In the large-scale distributed hardware-in-the-loop radar simulation system based on HLA, a new solution of processing after acquisition is proposed, which separates the software subsystem from the hardware jammer sub...In the large-scale distributed hardware-in-the-loop radar simulation system based on HLA, a new solution of processing after acquisition is proposed, which separates the software subsystem from the hardware jammer subsystem by a response database, so as to settle the problem, that the software subsystem can not meet the real-time need of the hardware, with very little increment of code. And the data completeness and feasibility of this solution are discussed.展开更多
The aim of this study is to improve the efficiency of external corrosion inspection of pipes in chemical plants.Currently,the preferred method involves manual inspection of images of corroded pipes;however,this places...The aim of this study is to improve the efficiency of external corrosion inspection of pipes in chemical plants.Currently,the preferred method involves manual inspection of images of corroded pipes;however,this places significant workload on human experts owing to the large number of required images.Furthermore,visual assessment of corrosion levels is prone to subjective errors.To address these issues,we developed an AI(artificial intelligence)-based corrosion-diagnosis system(AI corrosion-diagnosis system)and implemented it in a factory.The proposed system architecture was based on HITL(human-in-the-loop)ML(machine learning)[1].To overcome the difficulty of developing a highly accurate ML model during the PoC(proof-of-concept)stage,the system relies on cooperation between humans and the ML model,utilizing human expertise during operation.For instance,if the accuracy of the ML model was initially 60%during the development stage,a cooperative approach would be adopted during the operational stage,with humans supplementing the remaining 40%accuracy.The implemented system’s ML model achieved a recall rate of approximately 70%.The system’s implementation not only contributed to the efficiency of operations by supporting diagnosis through the ML model but also facilitated the transition to systematic data management,resulting in an overall workload reduction of approximately 50%.The operation based on HITL was demonstrated to be a crucial element for achieving efficient system operation through the collaboration of humans and ML models,even when the initial accuracy of the ML model was low.Future efforts will focus on improving the detection of corrosion at elevated locations by considering using video cameras to capture pipe images.The goal is to reduce the workload for inspectors and enhance the quality of inspections by identifying corrosion locations using ML models.展开更多
The dynamic event-triggered(DET)formation control problem of a class of stochastic nonlinear multi-agent systems(MASs)with full state constraints is investigated in this article.Supposing that the human operator sends...The dynamic event-triggered(DET)formation control problem of a class of stochastic nonlinear multi-agent systems(MASs)with full state constraints is investigated in this article.Supposing that the human operator sends commands to the leader as control input signals,all followers keep formation through network topology communication.Under the command-filter-based backstepping technique,the radial basis function neural networks(RBF NNs)and the barrier Lyapunov function(BLF)are utilized to resolve the problems of unknown nonlinear terms and full state constraints,respectively.Furthermore,a DET control mechanism is proposed to reduce the occupation of communication bandwidth.The presented distributed formation control strategy guarantees that all signals of the MASs are semi-globally uniformly ultimately bounded(SGUUB)in probability.Finally,the feasibility of the theoretical research result is demonstrated by a simulation example.展开更多
基金Sponsored by the Ministerial Level Advanced Research Foundation(A26020060253)
文摘An investigation into the aircraft flight simulation and control system is presented in this paper. The study was firstly focused on the establishment of an integrated hardware-in-the-loop（HITL） platform for aircraft flight simulation based on MATLAB/Simulink ＋ dSPACE. The platform combines the abundant software and hardware resources of dSPACE simulation platform to simulate the flight attitude of an aircraft in six-DOF （ degree of freedom） motion. Based on the platform, the study was then focused on the flight numerical simulation by taking a loitering aerial vehicle as an example. An aircraft mathematical model was created for a modular design and off-line numerical simulation based on MATLAB/Simulink. Finally, the study was focused on the control system design of the loitering aerial vehicle and conduct of an HITL simulation experiment for the vehicle pitch control. The experiment verifies the system design and control effectiveness. Research results show that the dSPACE simulation system provides a real time good experimental platform to improve the efficiency of study and development of a flight control system.
文摘文章探讨基于Diffusion Transformer(DiT)算法的生成式人工智能(AIGC)技术在微短剧创作中的应用及影响。研究发现,AIGC技术明显降低了影视创作门槛,推动了微短剧创作模式革新。然而,该技术的局限性限制了作品的艺术表现力。文章分析AIGC技术与微短剧发展逻辑的契合点,明确其在成本控制、创作效率提升和叙事特点适配方面的优势。同时,探究AIGC技术引发的影视创作模式变革,强调“人在回路”(human in the loop,HITL)理念的重要性,并指出创作流程的非线性化对传统影视制作模式的冲击。研究结果表明,AIGC技术推动了创作团队架构的变革,催生了自组织行为、分布式决策和局部交互等“群集系统”特征,增强了创作的灵活性和抗干扰性。然而,其生成过程的随机性和对艺术修辞理解的不足,使得创作者难以精准把控视听语言,导致作品在情感表达和细节处理上存在不足。部分AIGC微短剧过度依赖视觉奇观和技术仪式感,忽视了故事内容的深度和情感共鸣,削弱了作品的艺术价值。AIGC技术虽为微短剧创作带来了便利,但其应用需在工具理性和艺术表达之间寻求平衡。技术应服务于艺术创作,而非主导创作。未来,创作者需不断探索技术与艺术的结合点,发挥AIGC技术的优势,打破其局限性,推动微短剧高质量发展,为文化传播提供创新路径。
基金Supported by the National Natural Science Foundation of China (61101129)Specialized Research Fund for the Doctoral Program of Higher Education(20091101110019)
文摘To enhance the fidelity and accuracy of the simulation of communication networks,hardware-in-the-loop（HITL） simulation was employed.HITL simulation methods was classified into three categories,of which the merits and shortages were compared.Combing system-in-the-loop（SITL） simulation principle with high level architecture（HLA）,an HITL simulation model of asynchronous transfer mode（ATM） network was constructed.The throughput and end-to-end delay of all-digital simulation and HITL simulation was analyzed,which showed that HITL simulation was more reliable and effectively improved the simulation credibility of communication network.Meanwhile,HLA-SITL method was fast and easy to achieve and low-cost during design lifecycle.Thus,it was a feasible way to research and analyze the large-scale network.
基金the Ministerial Level Advanced Research Foundation
文摘In the large-scale distributed hardware-in-the-loop radar simulation system based on HLA, a new solution of processing after acquisition is proposed, which separates the software subsystem from the hardware jammer subsystem by a response database, so as to settle the problem, that the software subsystem can not meet the real-time need of the hardware, with very little increment of code. And the data completeness and feasibility of this solution are discussed.
文摘The aim of this study is to improve the efficiency of external corrosion inspection of pipes in chemical plants.Currently,the preferred method involves manual inspection of images of corroded pipes;however,this places significant workload on human experts owing to the large number of required images.Furthermore,visual assessment of corrosion levels is prone to subjective errors.To address these issues,we developed an AI(artificial intelligence)-based corrosion-diagnosis system(AI corrosion-diagnosis system)and implemented it in a factory.The proposed system architecture was based on HITL(human-in-the-loop)ML(machine learning)[1].To overcome the difficulty of developing a highly accurate ML model during the PoC(proof-of-concept)stage,the system relies on cooperation between humans and the ML model,utilizing human expertise during operation.For instance,if the accuracy of the ML model was initially 60%during the development stage,a cooperative approach would be adopted during the operational stage,with humans supplementing the remaining 40%accuracy.The implemented system’s ML model achieved a recall rate of approximately 70%.The system’s implementation not only contributed to the efficiency of operations by supporting diagnosis through the ML model but also facilitated the transition to systematic data management,resulting in an overall workload reduction of approximately 50%.The operation based on HITL was demonstrated to be a crucial element for achieving efficient system operation through the collaboration of humans and ML models,even when the initial accuracy of the ML model was low.Future efforts will focus on improving the detection of corrosion at elevated locations by considering using video cameras to capture pipe images.The goal is to reduce the workload for inspectors and enhance the quality of inspections by identifying corrosion locations using ML models.
基金supported in part by the National Natural Science Foundation of China(62121004,62033003,61973091,62203119)the Local Innovative and Research Teams Project of Guangdong Special Support Program(2019BT02X353)+1 种基金the Natural Science Foundation of Guangdong Province(2023A1515011527,2022A1515011506)the China National Postdoctoral Program(BX20220095,2022M710826).
文摘The dynamic event-triggered(DET)formation control problem of a class of stochastic nonlinear multi-agent systems(MASs)with full state constraints is investigated in this article.Supposing that the human operator sends commands to the leader as control input signals,all followers keep formation through network topology communication.Under the command-filter-based backstepping technique,the radial basis function neural networks(RBF NNs)and the barrier Lyapunov function(BLF)are utilized to resolve the problems of unknown nonlinear terms and full state constraints,respectively.Furthermore,a DET control mechanism is proposed to reduce the occupation of communication bandwidth.The presented distributed formation control strategy guarantees that all signals of the MASs are semi-globally uniformly ultimately bounded(SGUUB)in probability.Finally,the feasibility of the theoretical research result is demonstrated by a simulation example.
