aircraft steering instability during the taxiing process sometimes occurs resulting from the unstable bifurcation phenomena of the nonlinear steering dynamic system,which may lead to severe *** this study,the control ...
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aircraft steering instability during the taxiing process sometimes occurs resulting from the unstable bifurcation phenomena of the nonlinear steering dynamic system,which may lead to severe *** this study,the control parameter design of an aircraft nose wheel steering control system based on the control continuation method is proposed to reduce the number of unstable bifurcation points and enlarge the system stable region area in a certain parameter ***,the aircraft turning performance can be improved ***,a nonlinear aircraft rollout dynamic model is constructed,and the aircraft ground steering bifurcation characteristics are obtained under the open-loop steering control ***,the bifurcation performances under three closed-loop nose wheel steering controllers based on the feedback control method are compared,and the control parameter of the quadratic nonlinear controller with a better bifurcation control effect is selected as a second bifurcation parameter to analyze the directional system stability via two-parameter bifurcation ***,the influence of a crosswind on the aircraft ground steering bifurcation performance is studied for various control parameter ***,the control effects of a traditional proportional-integral-derivative(PID)nose wheel steering control law and the designed feedback controller are compared and ***,a semi-physical experiment of the aircraft nose wheel steering system is carried out,and different control parameter values are selected for test verification,which can further verify the control effect of the designed nonlinear feedback *** results indicate that the feedback control method is unable to vary the system bifurcation types,but appropriate control parameter design can effectively shrink the system instability region and even eliminate the unstable Hopf bifurcation points under some specific working conditions,improving the aircraft ground turning stability re
Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measur...
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Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measure, a principal method is designed for quantifying the detectabilities of fault detection algorithms over special datasets.
Aiming at the structural asymmetry problem caused by the inconsistency of the two optical fibers connecting the Y waveguide and the resonant cavity in the RFOG optical system driven by a broad-spectrum light source, a...
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Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors due to its strong robustness against measurement and system noise. However, the conventional method su...
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This study focuses on enhancing the evasion capabilities of unmanned ground vehicles(UGVs) using Generative Adversarial Imitation Learning(GAIL). The UGVs are trained to evade unmanned aerial vehicles(UAVs). A decisio...
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This study focuses on enhancing the evasion capabilities of unmanned ground vehicles(UGVs) using Generative Adversarial Imitation Learning(GAIL). The UGVs are trained to evade unmanned aerial vehicles(UAVs). A decision-making neural network has been trained via GAIL to refine evasion strategies with expert demonstrations. The simulation environment was developed with OpenAI Gym and calibrated with real-world data for the improvement of accuracy. The integrated platform including the proposed algorithm was tested in flight experiments. Results showed that the UGVs could effectively evade UAVs in the complex and dynamic environment.
To enable simultaneous transmit and receive(STAR)on the same frequency in a densely deployed space with multi-interference sources,this work proposes a digitally-assisted analog selfinterference cancellation method,wh...
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To enable simultaneous transmit and receive(STAR)on the same frequency in a densely deployed space with multi-interference sources,this work proposes a digitally-assisted analog selfinterference cancellation method,which can acquire reference signals through flexible wired/wireless switching *** on this method,the Minimum Mean Square Error algorithm with known channel state information is derived in detail,determining the upper limit of the cancellation performance,and the Adaptive Dithered Linear Search algorithm for real-time engineering cancellation is *** correctness of theoretical analysis is verified by the practical self-interference channel measured by a vector network ***,we have designed and implemented the corresponding multiinterference cancellation prototype with the digitallyassisted structure,capable of handling multiple interferences(up to three)and supporting a large receive bandwidth of 100 MHz as well as a wide frequency coverage from 30 MHz to 3000 *** test results demonstrate that in the presence of three interferences,when the single interference bandwidth is 0.2/2/20 MHz(corresponding to the receive bandwidth of 2/20/100 MHz),the cancellation performance can reach 46/32/22 dB or more.
This study aimed to investigate the erosion behavior and mechanism of a newly developed 25Cr3Mo2WNiV steel with a chrome coating using promoted ignition combustion *** erosion threshold pressure and temperature of the...
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This study aimed to investigate the erosion behavior and mechanism of a newly developed 25Cr3Mo2WNiV steel with a chrome coating using promoted ignition combustion *** erosion threshold pressure and temperature of the chrome-coated 25Cr3Mo2WNiV steel were determined to be 0.2 MPa and 254.3 K higher than those of traditional chrome-coated 30SiMn2MoV ***,Kirkendall voids and inter-diffusion between the Cr coating and matrix were first observed before *** improved erosion resistance of the chrome-coated 25Cr3Mo2WNiV steel was attributed to the suppression of the Kirkendall effect,which minimized heat generation at the Cr/matrix interface by pre-venting oxygen diffusion and reducing oxygen affinity.
Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy ***,there still exist some limitations in current PE methods,su...
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Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy ***,there still exist some limitations in current PE methods,such as low sample efficiency and local convergence,especially on complex *** this study,a novel PE algorithm called Least-Squares Truncated Temporal-Difference learning(LST2D)is *** LST2D,an adaptive truncation mechanism is designed,which effectively takes advantage of the fast convergence property of Least-Squares Temporal Difference learning and the asymptotic convergence property of Temporal Difference learning(TD).Then,two feature pre-training methods are utilised to improve the approximation ability of ***,an Actor-Critic algorithm based on LST2D and pre-trained feature representations(ACLPF)is proposed,where LST2D is integrated into the critic network to improve learning-prediction *** simulation studies were conducted on four robotic tasks,and the corresponding results illustrate the effectiveness of *** proposed ACLPF algorithm outperformed DQN,ACER and PPO in terms of sample efficiency and stability,which demonstrated that LST2D can be applied to online learning control problems by incorporating it into the actor-critic architecture.
Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian *** MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised m...
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Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian *** MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised method,it is up against parameter problems which makes the parameters intractable to tune and is unfeasible in real-life applications;2)Only considers the clustering information,but ignores the interference of noise within Laplacian.
This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, w...
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This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, which can compute the bounds of the output of a feedforward neural network subject to a bounded input. By applying the proposed interval analysis method to a network trained with fault-free system data, adaptive thresholds for fault detection are computed. Finally, one can acquire fault detection results via a fault detection strategy. The proposed method can achieve tight bounds of the network output and employ simple operations, which leads to accurate fault detection results and a low computational burden.A numerical simulation and an experiment on an AC servo motor are given to illustrate the effectiveness and superiority of the proposed method.
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