A5083070928- Robotic Path Planning Algorithms
- Guidance and Control Systems
- Privacy-Preserving Technologies in Data
- Adaptive Control of Nonlinear Systems
- Adaptive Dynamic Programming Control
- Military Defense Systems Analysis
- Iterative Learning Control Systems
- Robotics and Sensor-Based Localization
- UAV Applications and Optimization
- Nuclear physics research studies
- Reinforcement Learning in Robotics
- Distributed Control Multi-Agent Systems
- Control and Dynamics of Mobile Robots
- Innovative Educational Techniques
- Dynamics and Control of Mechanical Systems
- Target Tracking and Data Fusion in Sensor Networks
- Indoor and Outdoor Localization Technologies
- Nuclear Physics and Applications
- Neutrino Physics Research
- Brain Tumor Detection and Classification
- Muscle activation and electromyography studies
- Stochastic Gradient Optimization Techniques
- Neural Networks Stability and Synchronization
- Advanced Algorithms and Applications
- Microwave Imaging and Scattering Analysis
Nanjing University of Aeronautics and Astronautics
2022-2025
Ministry of Industry and Information Technology
2023
Chinese Academy of Sciences
2023
Institute of Modern Physics
2018-2023
Nanchang Hangkong University
2020-2021
South China Normal University
2018
Anhui Agricultural University
2015
In recent years, stealth aircraft penetration path planning has been a significant research subject in the field of low altitude combat. However, previous works have mainly concentrated on for unmanned aerial vehicle(UAV) 2D static environment. contrast, this paper addresses novel real-time algorithm UAV to realize rapid penetration, which aims devise route strategy based improved A-Star address problems replanning 3D complex dynamic The proposed method introduces kinematic model and...
For stealth unmanned aerial vehicles (UAVs), path security and search efficiency of penetration paths are the two most important factors in performing missions. This article investigates an optimal planning method that simultaneously considers principles kinematics, dynamic radar cross-section UAVs, network system. By introducing threat estimation function a 3D bidirectional sector multilayer variable step strategy into conventional A-Star algorithm, modified algorithm was proposed which...
Task allocation is a key aspect of Unmanned Aerial Vehicle (UAV) swarm collaborative operations. With an continuous increase UAVs' scale and the complexity uncertainty tasks, existing methods have poor performance in computing efficiency, robustness, real-time allocation, there lack theoretical analysis on convergence optimality solution. This paper presents novel intelligent framework for distributed decision-making based evolutionary game theory to address task UAV system uncertain...
In order to solve the problem of unknown parameter drift in nonlinear pure-feedback system, a novel system is proposed which an unconventional coordinate transformation introduced and dynamic surface algorithm designed eliminate “calculation expansion” caused by use backstepping system. Meanwhile, sufficiently smooth projection suppress Simulation experiments demonstrate that controller ensures global ultimate boundedness all signals closed-loop appropriate parameters can make tracking error...
The new isotope $^{224}\mathrm{Np}$ was produced in the fusion-evaporation reaction of $^{40}\mathrm{Ar}+^{187}\mathrm{Re}$ and identified through evaporation residue (ER)--$\ensuremath{\alpha}$-decay correlation measurements using digital pulse processing technique. Two $\ensuremath{\alpha}$-decay branches with $\ensuremath{\alpha}$ energies 9137(20) 8868(62) keV were assigned to $^{224}\mathrm{Np}$, decaying two excited states $^{220}\mathrm{Pa}$. half-life deduced be...
This paper presents fixed-time adaptive neural tracking control for a class of uncertain nonlinear pure-feedback systems. To overcome the design difficulty arising from nonaffine structure systems, mean value theorem is introduced to separate appearance Radial basis function (RBF) networks are employed approximate designed unknown functions f̂ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> (Z ). By combining RBFs and Lyapunov functions,...
This paper presents the flight penetration path planning algorithm in a complex environment with Bogie or Bandit (BB) threats for stealth unmanned aerial vehicle (UAV). The emergence of rigorous air defense radar net necessitates efficient and replanning UAV concerning survivability ability. We propose improved A-Star based on multiple step search approach to deal this uprising problem. objective is achieve rapid environment. Firstly, combination single-base radar, dual-base BB adopted...
Electronic warfare plays an essential role in modern warfare. In this background, the multiple UAVs cooperative passive positioning technology, which has advantages of long operating distance and strong concealment, received significant attention. Considering scenario three attacking enemy surface ships a naval battle, paper proposes collaborative localization algorithm based on TDOA DOA to solve problem three-dimensional space. Firstly, we establish location model according time delay...
The $\ensuremath{\alpha}$ decay of $^{222}\mathrm{U}$ was reinvestigated using a general least-square superpulse fitting algorithm dedicated to resolving pileup signals in the very short-lived nuclei. $\ensuremath{\alpha}$-particle energy revised be 9246(8) keV, and precision improved significantly compared with previous result. Using present energy, anomaly systematics $\ensuremath{\alpha}$-decay reduced width ${\ensuremath{\delta}}^{2}$ observed at ${N}_{p}{N}_{n}$ scheme is solved, all...
This paper examines approximation-based fixed-time adaptive tracking control for a class of uncertain nonlinear pure-feedback systems. Novel virtual and actual controllers are designed that resolve the meaninglessness at origin in negative domain, sufficient condition system to have semiglobal stability is also provided. Radial basis function neural networks introduced approximate unknown functions solving problem systems, mean value theorem used solve nonaffine structure The this ensure all...
Aiming at the localization problem of moving targets in two-dimensional planar scenes, this paper proposes an improved compressive sensing algorithm for super-resolution targets. Firstly, a multi-target location model is presented scene according to detection principle frequency-modulated continuous wave radar (FMCW) and fast Fourier transform (FFT) method. Then, considering data characteristics IF signal group, multiple target transformed into optimization problems such as sparse recovery...
In this brief, we study the distributed adaptive fixed-time tracking consensus control problem for multiple strict-feedback systems with uncertain nonlinearities under a directed graph topology. It is assumed that leader’s output time varying and has been accessed by only small fraction of followers in group. The proposed to design local controllers order guarantee between leader ensure error convergence independent systems’ initial state. function approximation technique using radial basis...
Advantage Learning (AL) seeks to increase the action gap between optimal and its competitors, so as improve robustness estimation errors. However, method becomes problematic when induced by approximated value function does not agree with true action. In this paper, we present a novel method, named clipped (clipped AL), address issue. The is inspired our observation that increasing blindly for all given samples while taking their necessities into account could accumulate more errors in...
One of the major challenges current offline reinforcement learning research is to deal with distribution shift problem due change in state-action visitations for new policy. To address this issue, we present a novel reward shifting-based method. Specifically, regularize behavior policy at each state, modify be received by shifting it adaptively according its proximity policy, and apply along opposite directions in-distribution actions ones not. In way are able guide procedure itself...
Advantage learning (AL) aims to improve the robustness of value-based reinforcement against estimation errors with action-gap-based regularization. Unfortunately, method tends be unstable in case function approximation. In this paper, we propose a simple variant AL, named smoothing advantage (SAL), alleviate problem. The key our is replace original Bellman Optimal operator AL smooth one so as obtain more reliable temporal difference target. We give detailed account resulting action gap and...