Preserving the topology from being inferred by external adversaries has become a paramount security issue for network systems (NSs), and adding random noises to the nodal states provides a promising way. Nevertheless,...
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In order to improve the stability of the robot at work, this paper adds an insertion point between the end of the robot and the next target point, and changes the original linear trajectory to a new trajectory planned...
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The direction of the odor plumes is very helpful for robots to preform odor source localization task. To address issues of that wind measurement equipment is not able or convenient to carry on the robots, this paper p...
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Dear Editor,In this letter,in order to deal with random network delays and packet losses in a class of networked nonlinear systems,three data-driven networked predictive control methods are *** closed-loop systems and...
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Dear Editor,In this letter,in order to deal with random network delays and packet losses in a class of networked nonlinear systems,three data-driven networked predictive control methods are *** closed-loop systems and control increments are derived,respectively.
Sound event localization and detection have been applied in various fields. Due to the polyphony and noise interference, it becomes challenging to accurately predict the sound event and their occurrence locations. Aim...
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The robust stability problem of spatially interconnected systems with signal saturation among the many composed subsystems is considered. The system structure is usually sparse, and each subsystem has different dynami...
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This paper investigates a finite-time tracking problem for the uncertainty nonlinear systems in nonstrict-feedback form,in which the output signal is restricted in a *** on the barrier Lyapunov function and dynamic su...
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This paper investigates a finite-time tracking problem for the uncertainty nonlinear systems in nonstrict-feedback form,in which the output signal is restricted in a *** on the barrier Lyapunov function and dynamic surface control scheme,a novel adaptive neural controller is proposed by using the finite-time Lyapunov *** the aforementioned literature on finite time tracking control,the violation of system output constraint is avoided by combining the barrier Lyapunov function method with finite-time *** structural characteristics of neural network is introduced to expand the adaptive neural finite-time backstepping method to the uncertainty nonlinear systems in the non-strict ***,the dynamic surface control is introduced to cope with the problem of“explosion of complexity”inherent in conventional backstepping *** is shown that the designed controller can achieve finite-time tracking control and all the variables in the closed-loop system are bounded with output constraint guaranteed form stability analysis and simulation results.
Planetary craters are natural navigation landmarks that widely exist and are easily *** navigation based on crater landmarks has become an important autonomous navigation method for planetary *** to the increase in ob...
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Planetary craters are natural navigation landmarks that widely exist and are easily *** navigation based on crater landmarks has become an important autonomous navigation method for planetary *** to the increase in observed crater landmarks and the limitation of onboard computation,the selection of good crater landmarks has gradually become a research hotspot in the field of landmark-based optical *** paper designs a fast crater landmark selection method,which not only considers the configuration observability of crater subsets but also focuses on the influence on navigation performance arising from the measurement uncertainty and the matching confidence of craters,which is different from other landmark selection *** factor of measurement uncertainty,which is anisotropic,correlated and nonidentically distributed,is quantified and integrated into selection based on crater pairing detection and localization error *** addition,the concept of the crater matching confidence factor is introduced,which reflects the possibility of 2D projection measurements corresponding to 3D *** with the configuration observability factor,the crater landmark selection indicator is ***,the effectiveness of the proposed method is verified by Monte Carlo simulations.
CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computationa...
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CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computational model to predict the associations between circRNAs and diseases. And there is existing more and more evidence indicates that the combination of multi-biomolecular information can improve the prediction accuracy. We propose a novel computational model for CDA prediction named MBCDA, we collect the multi-biomolecular information including circRNA, disease, miRNA and lncRNA based on 6 databases, and construct three heterogeneous network among them, then the multi-heads graph attention networks are applied to these three networks to extract the features of circRNAs and diseases from different views, the obtained features are put into variational graph auto-encoder(VGAE) network to learn the latent distributions of the nodes, a fully connected neural network is adopted to further process the output of VGAE and uses sigmoid function to obtain the predicted probabilities of circRNA-disease *** a result, MBCDA achieved the values of AUC and AUPR under 5-fold cross-validation of 0.893 and 0.887. MBCDA was applied to the analysis of the top-25 predicted associations between circRNAs and diseases, these experimental results show that our proposed MBCDA is a powerful computational model for CDA prediction.
This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance ru...
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This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.
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