Due to the nonlinear, strong coupling and uncertain parameters of the new energy four-wheel hub motor, it is more difficult to control the torque of the motor. In order to solve this problem, a torque control method b...
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Due to the nonlinear, strong coupling and uncertain parameters of the new energy four-wheel hub motor, it is more difficult to control the torque of the motor. In order to solve this problem, a torque control method based on the distribution algorithm is proposed for the new energy four-wheel hub motor. The dynamic model of the new energy four-wheel hub motor is suggested, and the unmeasurable flux, electric power and other state variables in the motor model are derived according to the degree of freedom of the body. The paper studies the whole four-wheel hub motor with the purpose to improve the efficiency of the drive system and proposes the distribution algorithm to control the electromagnetic torque of the motor. According to the simulation results, the torque control for the new energy four-wheel hub motor leads to a longer driving range of the vehicle, small change in the amplitude of stator flux and the stator current, better stability of the motor speed, and better torque control effect.
An effective distribution of packets is particularly important for the performance of a network-on-chip system. Ring connected binary tree structures do not have a defined distribution method and this paper elaborates...
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In order to quick response to emergencies such as air crash and natural disaster, satellites on orbit are desirable to fast achieve imaging sequence for real-time tasks. To select targets in hot area for formation fly...
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In order to quick response to emergencies such as air crash and natural disaster, satellites on orbit are desirable to fast achieve imaging sequence for real-time tasks. To select targets in hot area for formation flying satellites, two types of "select-by-grade" algorithms are presented to obtain an appropriate imaging sequence for each satellite. First, ground targets are divided into different groups with different grades in terms of their significances. By making analysis on constraints of target locations and satellite performances, the autonomous task planning is treated as a stepwise optimization problem where the objective function is to maximize the overall imaging gain for all satellites. Second, to solve the optimization problem, the aforementioned different grades ground targets are assigned to different satellites by pre-defined distribution schemes. Finally, a simulation example is provided to illustrate the effectiveness of the proposed algorithms. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.
In order to quick response to emergencies such as air crash and natural disaster, satellites on orbit are desirable to fast achieve imaging sequence for real-time tasks. To select targets in hot area for formation fly...
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In order to quick response to emergencies such as air crash and natural disaster, satellites on orbit are desirable to fast achieve imaging sequence for real-time tasks. To select targets in hot area for formation flying satellites, two types of “select-by-grade” algorithms are presented to obtain an appropriate imaging sequence for each satellite. First, ground targets are divided into different groups with different grades in terms of their significances. By making analysis on constraints of target locations and satellite performances, the autonomous task planning is treated as a stepwise optimization problem where the objective function is to maximize the overall imaging gain for all satellites. Second, to solve the optimization problem, the aforementioned different grades ground targets are assigned to different satellites by pre-defined distribution schemes. Finally, a simulation example is provided to illustrate the effectiveness of the proposed algorithms.
Molecular Dynamics simulations of protein receptors are an emergent tool in rational drug discovery. Nevertheless, employing Molecular Dynamics trajectories in virtual screening of large repositories is a very costly ...
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ISBN:
(纸本)9781479974931
Molecular Dynamics simulations of protein receptors are an emergent tool in rational drug discovery. Nevertheless, employing Molecular Dynamics trajectories in virtual screening of large repositories is a very costly procedure, which ultimately may become unfeasible. Data clustering have been applied in this context with the goal of reducing the overall computational cost in order to make this task feasible. In this paper, we develop a novel estimation of distribution algorithm called Clus-EDA for clustering entire trajectories using structural features from the substrate-binding cavity of the protein receptor. This novel approach is capable of reducing the original trajectory to about 4% of its original size whilst keeping all relevant information for the analysis of receptor-ligand binding. The resulting partition generated by the estimation of distribution algorithm is further validated by analyzing the interactions between 20 ligands and a Fully-Flexible Receptor model containing a 20 ns Molecular Dynamics simulation trajectory. Results show that Clus-EDA is capable of outperforming traditional clustering algorithms such as k-means and hierarchical clustering by providing the smallest variance of the free energy of binding within the conformations in each cluster.
One critical issue for wireless power transfer is to avoid human health impairments caused by electromagnetic radiation (EMR) exposure. The existing studies mainly focus on scheduling wireless chargers so that (expect...
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One critical issue for wireless power transfer is to avoid human health impairments caused by electromagnetic radiation (EMR) exposure. The existing studies mainly focus on scheduling wireless chargers so that (expected) EMR at any point in the area does not exceed a threshold R-t. Nevertheless, they overlook the EMR jitter that leads to exceeding of R-t even if the expected EMR is no more than R-t. This paper studies the fundamental problem of RObustly SafE charging for wireless power transfer (ROSE), that is, scheduling the power of chargers so that the charging utility for all rechargeable devices is maximized while the probability that EMR anywhere does not exceed R, is no less than a given confidence. We first build our empirical probabilistic charging model and EMR model. Then, we present EMR approximation and area discretization techniques to formulate ROSE into a Second-Order Cone Program. After that, we propose the first redundant second-order cone constraints reduction algorithm to reduce the computational cost, and therefore obtain a (1 - epsilon)-approximation centralized algorithm. Further, we propose a (1 - epsilon)-approximation fully distributed algorithm scalable with network size for ROSE. We conduct both simulation and field experiments, and the results show that our algorithms can outperform comparison algorithms by 480.19 percent.
A novel graph-based Estimation of distribution algorithm (EDA) named Probabilistic Model Building Genetic Network Programming (PMBGNP) has been proposed. Inspired by classical EDAs, PMBGNP memorizes the current best i...
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ISBN:
(纸本)9781467315104
A novel graph-based Estimation of distribution algorithm (EDA) named Probabilistic Model Building Genetic Network Programming (PMBGNP) has been proposed. Inspired by classical EDAs, PMBGNP memorizes the current best individuals and uses them to estimate a distribution for the generation of the new population. However, PMBGNP can evolve compact programs by representing its solutions as graph structures. Therefore, it can solve a range of problems different from conventional ones in EDA literature, such as data mining and Reinforcement Learning (RL) problems. This paper extends PMBGNP from discrete to continuous search space, which is named PMBGNP-AC. Besides evolving the node connections to determine the optimal graph structures using conventional PMBGNP, Gaussian distribution is used for the distribution of continuous variables of nodes. The mean value μ and standard deviation σ are constructed like those of classical continuous Population-based incremental learning (PBILc). However, a RL technique, i.e., Actor-Critic (AC), is designed to update the parameters (μ and σ). AC allows us to calculate the Temporal-Difference (TD) error to evaluate whether the selection of the continuous value is better or worse than expected. This scalar reinforcement signal can decide whether the tendency to select this continuous value should be strengthened or weakened, allowing us to determine the shape of the probability density functions of the Gaussian distribution. The proposed algorithm is applied to a RL problem, i.e., autonomous robot control, where the robot's wheel speeds and sensor values are continuous. The experimental results show the superiority of PMBGNP-AC comparing with the conventional algorithms.
The research introduces a comparative review of atmosphere investigation tasks distribution techniques in local network. The article provides information about algorithms, simulation modeling methods and the results o...
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ISBN:
(纸本)9781628419085
The research introduces a comparative review of atmosphere investigation tasks distribution techniques in local network. The article provides information about algorithms, simulation modeling methods and the results of the modeling.
Wireless sensor network is added on traditional GPS to realize double location in this paper. The widely used distributed distance measure algorithm of RSSI based in wireless sensor network is adopted. At the beginnin...
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ISBN:
(纸本)9783037855454
Wireless sensor network is added on traditional GPS to realize double location in this paper. The widely used distributed distance measure algorithm of RSSI based in wireless sensor network is adopted. At the beginning work of this position system, unknown position node A broadcast its localization request, after all the base node received this request, they reply node A with its own location info and the RSSI value from other base node. Node A select the most closest base node as base to determine his own location, moreover, distance between base node and signal strength is take as reference to adjust the weight value of every base node, then the precise position is got after final calculation. In the end, precise of this algorithm is proved by simulation experiment.
In this paper, we proposed a novel task resource distribution algorithm based on Multidimensional Dynamic List Scheduling and Genetic algorithm. The mathematical formulation and implementation of the inner and outer m...
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ISBN:
(纸本)9781424409723
In this paper, we proposed a novel task resource distribution algorithm based on Multidimensional Dynamic List Scheduling and Genetic algorithm. The mathematical formulation and implementation of the inner and outer module of this algorithm are proposed. The numerical example shows the better performance of our designed algorithm.
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