This paper presents a novel approach for stable control of a single-link flexible-joint manipulator(SLFJM).The control objective is to stabilize the SLFJM at the straight-up equilibrium position from the straight-do...
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This paper presents a novel approach for stable control of a single-link flexible-joint manipulator(SLFJM).The control objective is to stabilize the SLFJM at the straight-up equilibrium position from the straight-down equilibrium position and suppress vibration by only using position ***,differential homeomorphic transformation is used to equivalently convert the original system into a new handy ***,the new system is divided into two parts: linear and *** nonlinear part is considered as a virtual disturbance of the linear ***,the Equivalent-input-disturbance-based(EID-based)control system is designed to suppress this virtual nonlinear disturbance at the zero equilibrium *** this way,the control objective of the original system is effectively ***,the numerical results demonstrate its validity.
A position control strategy by employing the model reduction and the cascade transformation is proposed for a planar four-link AAPA(Active-Active-Passive-Active) underactuated manipulator in this ***,a dynamics model ...
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A position control strategy by employing the model reduction and the cascade transformation is proposed for a planar four-link AAPA(Active-Active-Passive-Active) underactuated manipulator in this ***,a dynamics model of the system is ***,three controllers are designed based on the Lyapunov function to control the fourth active link from any initial angle to zero while the angles of the first and second active link remain their initial values,which makes the system is reduced to a planar virtual three-link AAP(Active-Active-Passive) underactuated ***,we obtain the new inputs of the cascade system of the planar virtual three-link AAP underactuated ***,we can get the controllers of the active links to realize the system position control *** results demonstrate the validity of the proposed control strategy.
As slide steering technology has lower maintenance costs, it is widely used in geological drilling industry. In order to adjust the hole trajectory, this technology changes the drilling direction by controlling tool f...
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As slide steering technology has lower maintenance costs, it is widely used in geological drilling industry. In order to adjust the hole trajectory, this technology changes the drilling direction by controlling tool face angle of downhole power drill tool. However, due to the existence of the untwist angle, it is difficult to precisely control the angle, which will directly affect the quality of hole trajectory. So untwist angle prediction is the prerequisite of hole trajectory control. This paper introduces a common method for calculating untwist angle for generating the training set. And then factors that influence untwist angle will be analyzed. Meanwhile, based on the analysis and calculation results, support vector regression is introduced in the prediction algorithm to provide a new way for untwist angle prediction.
A demand analysis method based on TAKAGI-SUGENO(T-S) fuzzy model for drinking service is proposed to provide corresponding services according to users’ emotions and intentions in human-robot interaction,in which T-...
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A demand analysis method based on TAKAGI-SUGENO(T-S) fuzzy model for drinking service is proposed to provide corresponding services according to users’ emotions and intentions in human-robot interaction,in which T-S fuzzy model is used to establish the relationship among human intention and human ***,the transformation of input and output is ***,fuzzy rules are formulated,and then fuzzy inference is applied to get user’s demand corresponding to emotion and *** proposal considers peoples fuzziness in inferring humans intention,which could help the robots to provide satisfied drinking service to *** validate the proposal,drinking service experiments are performed in a laboratory scenario using a humans-robots interaction system,from which the experimental results demonstrate the feasibility of the proposal.
An important feature of the deep learning algorithm is that the hidden layer of the neural network is more dependent on more computing resources and a larger amount of data. In this paper, we use Triplet GAN method to...
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An important feature of the deep learning algorithm is that the hidden layer of the neural network is more dependent on more computing resources and a larger amount of data. In this paper, we use Triplet GAN method to identify human body images with tattoos using fewer data sample labels. The model achieved better results(0.9462) than the only Triplet(0.8352) and only GAN(0.9178) in the MNIST dataset, it also achieved higher recognition accuracy(77-82%) under the premise of saving the amount of data, compared with the traditional machine learning algorithm(54-84%). We provide a new idea for tattoo image recognition applications in embedded computing units.
This paper investigates the problem of the strictly(Q,S,R)-γ-dissipativity analysis for Markovian jump neural networks with a time-varying *** employing an appropriate Lyapunov-Krasovskii functional and using the ext...
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This paper investigates the problem of the strictly(Q,S,R)-γ-dissipativity analysis for Markovian jump neural networks with a time-varying *** employing an appropriate Lyapunov-Krasovskii functional and using the extended relaxed integral inequality to estimate its derivative,a delay-dependent and mode-dependent condition that guarantee the considered Markovian jump neural networks strictly(Q,S,R)-γ-dissipative is ***,a numerical example is provided to illustrate the effectiveness of the proposed method.
Computational methods are often applied to identify essential proteins from protein-protein interaction networks. In this paper, inspected by node and edge clustering coefficient(NEC) and Pe C, we propose an improve...
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Computational methods are often applied to identify essential proteins from protein-protein interaction networks. In this paper, inspected by node and edge clustering coefficient(NEC) and Pe C, we propose an improved version of node and edge clustering coefficient(INEC) which both considers dual topological characteristics of the network and high false positives of the protein-protein interaction data. We apply it for the identification of essential proteins. And we implement three versions of INEC which combine different biological information. In order not to be confused, we call the first one INEC0 which dosen’t integrate biological information, the second one INEC1 which integrates gene expression similarity, and the third one INEC2 which integrates gene expression similarity, functional similarity, and protein-protein sequence similarity. We apply three implemented INEC methods to protein-protein interaction data of Saccharomyces cerevisiae(Yeast) and compare them with some state-of-theart methods(DC, NC, Pe C, and NEC). The experimental results show that our proposed methods achieve better results in terms of prediction accuracy, area under the curve of PR-curve, and Jackknife methodology.
Aiming at the problems of slow recognition,low efficiency and degree of automation in handwritten letter recognition system at present,a handwritten letter recognition system based on extreme learning machine is desig...
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Aiming at the problems of slow recognition,low efficiency and degree of automation in handwritten letter recognition system at present,a handwritten letter recognition system based on extreme learning machine is designed in this *** system is implemented by mixed programming with M ATLAB and visual studio,it can reads,normalize,binarize and extract the handwritten letter *** real-time interactive recognition of handwritten letters can be realized on the basis of training the simple pictures by using the identification model of the extreme learning machine *** experimental results show that the handwriting recognition system based on extreme learning machine designed in this paper can recognize 98.82%of handwritten letters and greatly reduce learning and testing *** with BP neural network and other recognition algorithms,its training times have been reduced by hundreds or even thousands of *** the same time,there is no manual intervention in the entire learning and testing process,which improves the automation of handwriting recognition.
An improved spectral reflectance reconstruction method is developed to transform camera RGB to spectral reflectance by inserting white balance and link function during the training-based method. The novelty in our met...
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An improved spectral reflectance reconstruction method is developed to transform camera RGB to spectral reflectance by inserting white balance and link function during the training-based method. The novelty in our method is the use of whitebalancing to normalize the scene illumination and link function to transform the reflectance, we use a radial basis function network to model the mapping between camera-specific RGB values and specific reflectance spectra. Experimental results indicate that the proposed method significantly outperforms currently existing methods in terms of spectral error and shape especially under the illumination not present in the training process.
With the development of smart home, various appliances are becoming intelligent. In this paper, i Mirror, an intelligent mirror based on facial expression recognition and color emotion adaptation is proposed, which is...
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With the development of smart home, various appliances are becoming intelligent. In this paper, i Mirror, an intelligent mirror based on facial expression recognition and color emotion adaptation is proposed, which is considered as a human-mirror interaction system through real-time facial expression recognition and color lights control based on color emotion *** can not only work as a real mirror for personal grooming, but also record the mood of the user and adapt to it with color presentation. Experiments on facial expression recognition and color emotion adaptation are performed by ten students aged from 18 to 25, from which the experimental results show that i Mirror can effectively identify facial expressions and control light color, in addition, the results of a survey show that 87.7% experimenters agree to use colorful lights to adapt to facial expressions.
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