Linear active disturbance rejection control(LADRC) is used to control the fuel processing system(FPS) of fuel cells. Two LADRC schemes(with and without decoupler) are studied. LADRCs with decouplers are designed at th...
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ISBN:
(纸本)9781467374439
Linear active disturbance rejection control(LADRC) is used to control the fuel processing system(FPS) of fuel cells. Two LADRC schemes(with and without decoupler) are studied. LADRCs with decouplers are designed at three operating points. Step responses and Monte Carlo experiments show that good dynamic performance and strong robustness can be achieved. The result is further verified with bode plots of the closed-loop sys tems. Inspired by this result, LADRCs without decouplers are analyzed. Simulations show that a single decentralized ADRC can be enough to control three different models with satisfactory dynamic performance and good decoupling performance.
With the rapid development of recycling and remanufacturing technologies, disassembly line balancing problems (DLBP) have drawn great attention. Considering the limitation of disassembly by humans or robots alone, thi...
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In this paper, we show that Euler discretization of the sliding mode control system with twisting algorithm can lead to periodic behaviors. Bounds for periodic orbits are derived, which allow one to estimate the maxim...
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In this paper, we show that Euler discretization of the sliding mode control system with twisting algorithm can lead to periodic behaviors. Bounds for periodic orbits are derived, which allow one to estimate the maximum chattering amplitude for a given value of the time step. It is shown that for certain parameter values, there exist arbitrarily long periodic orbits. Theoretical results are illustrated with simulation examples.
Word embedding models have been extensively used in document analysis. Even though many models have been created for embedding documents into vector spaces, their document clustering performance is not noticeably bett...
Word embedding models have been extensively used in document analysis. Even though many models have been created for embedding documents into vector spaces, their document clustering performance is not noticeably better than that of conventional bag-of-words representations. This paper proposes a document clustering called Word Embedding of Dimensionality Reduction (WERD) that can be used in conjunction with any word embedding method and can provide a semantic explanation of the clustering outcomes. Stopwords and a lexical reduction are first used to preprocess the documents. A pre-trained embedding model is used to embed documents. Then a dimension reduction is used to reduce the dimension of the embedded data to remove redundant features and create more compact document vectors used as document features for clustering. After clustering, the Non-Negative Matrix Factorization approach extracts the keywords from each cluster to produce semantic descriptions. Numerous experiments on two datasets show that WERD can produce superior clustering results.
The complex ocean environment leads to low contrast in underwater images and poor target visibility. In addition, the detected objects have multi-scale properties and clustering issues, making marine object detection ...
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Using the Hamiltonian function method, we investigate the excitation control of power systems presented by nonlinear differential algebraic equations. First, a novel Hamiltonian realization structure for nonlinear dif...
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Using the Hamiltonian function method, we investigate the excitation control of power systems presented by nonlinear differential algebraic equations. First, a novel Hamiltonian realization structure for nonlinear differential algebraic systems is applied to the power system. Then we propose a decentralized nonlinear excitation control scheme and analyze the stability of the closed loop system. This strategy takes advantage of the intrinsic properties including especially the internal power balance of the differential algebraic power system model. Simulation illustrates the effectiveness of the control strategy.
Nonlinear Correlation Coefficient (NCC) is proposed to quantitatively measure the nonlinear relation between the variables. Much attention paid on NCC leads to application being far from the basic research. In this pa...
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Nonlinear Correlation Coefficient (NCC) is proposed to quantitatively measure the nonlinear relation between the variables. Much attention paid on NCC leads to application being far from the basic research. In this paper, we propose a mathematical framework to systematically analyze the effects of statistical distribution on NCC. It is found that the arbitrary distortion on distribution leads to the decreasing of NCC and the sharing structure of the concerned distribution minimizes the NCC. Furthermore, considering the situation of a sequence of discrete observations, we provide a collection of rigorous logistic results to justify NCC is an increasing function of sequence length. The numerical examples on Lorenz and linear auto-regression system are used to illustrate proposed results suitably and effectively.
In this paper, we develop a micro-gripper that actuated by piezoelectric cantilever for the need of micro parts assembly. The displacement-voltage relationship model is given. For hysteresis of piezoelectric ceramic, ...
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In this paper, we develop a micro-gripper that actuated by piezoelectric cantilever for the need of micro parts assembly. The displacement-voltage relationship model is given. For hysteresis of piezoelectric ceramic, we present a mix control algorithm, which employs the hysteresis offset control model based on Dahl and PID control model. The results of micro-assembly prove that the model is efficiency.
A new optimal local path planning method for the mobile robot is introduced. It is achieved through the optimal control rules which are formed automatically based on the Q-Learning (QL) method of the Reinforcement Lea...
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ISBN:
(纸本)9781424425020
A new optimal local path planning method for the mobile robot is introduced. It is achieved through the optimal control rules which are formed automatically based on the Q-Learning (QL) method of the Reinforcement Learning (RL). The rules are executed as the reaction behaviors on the mobile robot at last. The state/action space which construct the rules structure are discretized according to the fuzzy logic. A Lookup_Q matrix M circQcirc is built to store Qcirc values of each state-action pair . According to the Boltzman Equation, an action of all available actions is chosen at the same state. The reinforcement signal is studied carefully with a non-uniform manner. All the pairs, which have the maximum circQ value in each column are selected out after QL. Then the optimal control rules are formed based on them after the merger. The algorithm can automatically control the formation of the rules and amends them expediently. At last the method performance is tested in different environments under the control of the rules.
Wireless Capsule Endoscopy (WCE) is an almost new technology to capture images from the whole of Gastrointestinal (GI) tract, noninvasively. WCE is a very useful technology to detect various abnormalities like blood b...
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ISBN:
(纸本)9781467331289
Wireless Capsule Endoscopy (WCE) is an almost new technology to capture images from the whole of Gastrointestinal (GI) tract, noninvasively. WCE is a very useful technology to detect various abnormalities like blood based abnormalities, ulcers and polyps. We note that polyps are growing tissues occur on the surface of tissue instead of inside an organ. Most polyps are not cancerous but if one becomes larger than a centimeter, it can turn into cancer by great chance. So, one of the most important advantages of WCE can be the early detection of polyps and cancers. In this paper we proposed using region-based Active Contour Method (ACM) and geometric feature for automatic detection of polyps. The results on a set of images show that the proposed method can achieve %90.91 accuracy, %100 sensitivity and %-83.33 specificity on our data set.
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