In recent years deep neural networks have achieved state-of-the-art accuracy at classifying the running state of a *** we propose a composite learning model（CLM） that combines the strength of broad learning and conv...
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In recent years deep neural networks have achieved state-of-the-art accuracy at classifying the running state of a *** we propose a composite learning model（CLM） that combines the strength of broad learning and conventional deep learning techniques to identify the fault types of underactuated surface vessels（USV）.Considering the measurement noises in training and testing data,we develop a deep sparse auto-encoder（DSAE） stacked by denoising auto-encoder（DAE） and contractive auto-encoders（CAEs）.To further reduce the computation time,a modified broad learning system（BLS） based classifier is developed,and the input layer receives the signal from the top layer of *** use the output of the classifier as *** value iterative（VI） based adaptive dynamic programming（adp） is employed to calculate the near-optimal increment of connection ***,we validate the developed approach by experiments using simulation data of USV that compares the proposed CLM with the standard BLS and conventional deep learning methods.
The exact mathematical models of multi-terminal high-voltage direct current（MT-HVDC） systems are hard to be obtained in the practical application of HVDC *** overcome this challenge,a model-free distributed frequenc...
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The exact mathematical models of multi-terminal high-voltage direct current（MT-HVDC） systems are hard to be obtained in the practical application of HVDC *** overcome this challenge,a model-free distributed frequency controller for MT-HVDC systems is proposed based on adaptive dynamic programming（adp） in this ***,for each AC area,only the local and neighboring sampling data of frequency is required without the MT-HVDC system ***,the proposed controller is distributed which effectively balances the communication burden among the AC ***,the proposed controller makes the connected AC areas share their power reserves via HVDC grids to compensate load disturbances so that the necessary power reserves can be *** simulations carried out on a five-terminal HVDC system evaluate the performance of the proposed controller.
Cooperative driving with V2V communication is under extensive investigation,because of its potential to increase the safety,reliability,connectivity,and autonomy of transportation *** paper studies the problem of conn...
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ISBN:
(纸本)9781538629185
Cooperative driving with V2V communication is under extensive investigation,because of its potential to increase the safety,reliability,connectivity,and autonomy of transportation *** paper studies the problem of connected cruise control（CCC） for a platoon of human-driven and autonomous *** data,such as distance and velocity information,are transmitted by vehicle-to-vehicle（V2V） communication between connected *** into account the communication latency and unpredictable behavior in the leading vehicle,we formulate the CCC problem as an adaptive optimal control problem with input delay and disturbance.A novel data-driven control solution is proposed for the vehicle platoon,which guarantees that each vehicle can achieve safe distance and desired common *** adaptivedynamicprogramming technique with sampled-data system theory,a data-driven adaptive optimal controller is learned from sampled data,without the knowledge of the human or vehicle dynamics of the platooning *** and robustness analyses are provided by means of inputto-state stability *** results confirm the efficacy of our method.
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