Abstract This paper concerns a set-point control for a folded posture of a 3-link gymnastic planar robot moving in the vertical plane with the first joint being passive and the others being active. To realize the goal...
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Abstract This paper concerns a set-point control for a folded posture of a 3-link gymnastic planar robot moving in the vertical plane with the first joint being passive and the others being active. To realize the goal posture of the kip motion of a gymnast on the high bar, the control objective is to drive the robot from any arbitrary initial state to any arbitrarily small neighborhood of the up-down-down equilibrium point and then balance the robot about that point, where the first link is in the upright position and the second and third links are in the downward position. This paper uses the energy-based control approach and the notion of virtual composite link to design a controller and provides a global motion analysis of the robot. This paper shows that the control toward such a folded posture is different from the swing-up control problem, for which all three links are fully stretched out in the upright position at the goal posture. A new result of this paper is that in addition to some conditions on the control parameters, a constraint on the mechanical parameters of the robot is needed for achieving the set-point control of the folded posture. The simulation results for two 3-link robots are provided to validate the effectiveness of the proposed control law and the necessity of the constraint.
Least association rules are the association rules that consist of the least item. These rules are very important and critical since they can be used to detect the infrequent events and exceptional cases. However, the ...
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Least association rules are the association rules that consist of the least item. These rules are very important and critical since they can be used to detect the infrequent events and exceptional cases. However, the formulation of measurement to efficiently discover least association rules is quite intricate and not really straight forward. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. Therefore, this paper proposes a new measurement called Critical Relative Support (CRS) to mine critical least association rules from educational context. Experiment with students’ examination result dataset shows that this approach can be used to reveal the significant rules and also can reduce up to 98% of uninterested association rules.
Association Rules Mining is one of the popular techniques used in data mining. Positive association rules are very useful in correlation analysis and decision making processes. In educational context, determine a “ri...
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Association Rules Mining is one of the popular techniques used in data mining. Positive association rules are very useful in correlation analysis and decision making processes. In educational context, determine a “right” program to the students is very unclear especially when their chosen programs are not selected. In this case, normally they will be offered to other programs based on the programs availability and not according to their program's field interests. The main concern is, by assigning inappropriate program which is not reflected their overall interest; it may create serious problems such as poorly in academic commitment and academic achievement. Therefore, Therefore in this paper, we proposed a model which consists of pre-processing, mining patterns and assigning weight to discover highly positive association rules. We examined the previous chosen programs by computerscience students in our university for July 2008/2009 intake. The result shows that the proposed model can mine association rules with high correlation. Moreover, for data analysis, there are existed students that have been offered in computerscience program at our university but not within their program's field interests.
This paper describes a path planning algorithm for calculates collision free path of two manipulators in a populated environment for 2 or 3-dimensional workspace. In the algorithm, two manipulators are considered as a...
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This paper describes a path planning algorithm for calculates collision free path of two manipulators in a populated environment for 2 or 3-dimensional workspace. In the algorithm, two manipulators are considered as a single composite one. A newly developed path planning algorithm BFA (Backtrack Free path planning Algorithm) enables the efficient generation of paths of this composite manipulator with many arms. BFA is an exact algorithm, i.e. the algorithm is backtrack free and resolution complete. Its computation time and memory space are proportional to the total number of arms in composite manipulators. Therefore paths can be calculated within practical and predetermined time even for manipulators with many arms, and it becomes possible to plan complicated motions of multi-arm manipulators in fully automated environments. The performance of BFA is evaluated for 2-dimensional environments. An additional advantage of this approach is that paths of individual manipulators can be calculated in parallel processing.
The nonlinear model predictive control (MPC) needs to solve a two-point boundary-value problem (TP-BVP) at every sample time based on the receding horizon control strategy. However, solving a nonlinear algebraic equat...
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The nonlinear model predictive control (MPC) needs to solve a two-point boundary-value problem (TP-BVP) at every sample time based on the receding horizon control strategy. However, solving a nonlinear algebraic equation for the TP-BVP requires high computational load, so developing an efficient computation method of the control law in real-time is a significant issue on the research of the nonlinear model predictive control. This paper proposes an efficient calculation method of the control law for nonlinear MPC. The proposed approach searches an optimal step-type input signal for a given performance index beforehand, then the input signal is successively updated using a continuation method. Hence, it can reduce the computation load because the number of the parameter to be optimized becomes one in the SISO case or the number of the inputs in the MIMO case, and solving TP-BVP can be avoided by a continuation method. In addition, the accuracy of the nonlinear algebraic equation, which gives the optimal condition, keeps well by analytically deriving the updating law of the MPC control law. A numerical example shows that the proposed method can reduce the computation load of the nonlinear MPC, while the accuracy of the optimal conditions given by the nonlinear algebraic equations keeps a tolerance level.
The paper analyzed and model of a fault tolerant electromechanical controlled worm gear driven fuel shut off valve for aerospace application. The analysis is mainly on design a reduced order fractional controller. Thi...
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It is well-known that thresholding algorithm is needed by gray-scale images in segmentation operation. In this paper, real printed circuit boards used are captured using a monochrome charged coupled device camera and ...
It is well-known that thresholding algorithm is needed by gray-scale images in segmentation operation. In this paper, real printed circuit boards used are captured using a monochrome charged coupled device camera and produced images consisting of foreground and background objects in gray-scale format. In order to correctly differentiate these two kinds of attributes, several of thresholding algorithms are applied. Then, misclassification error measure has been employed to evaluate the performances of these thresholding algorithms. This method gives information on how many percentages of background pixels wrongly assigned to foreground, and foreground pixels wrongly assigned to background pixels. As the best thresholding algorithm has been chosen, median filtering and the proposed defect classification algorithm can be applied to remove small noise in resultant images and classify the defects occurred on the printed circuit boards, respectively.
Abstract In this paper, we revisit the energy-based swing-up control problem for a rotational pendulum. Different from the existing energy-based control solution, first, we present a necessary and sufficient condition...
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Abstract In this paper, we revisit the energy-based swing-up control problem for a rotational pendulum. Different from the existing energy-based control solution, first, we present a necessary and sufficient condition for avoiding singular points in the control law and carry out a global motion analysis of the pendulum. Next, we remove the previous required constraint on the initial state of the pendulum and the control parameters for preventing the pendulum getting stuck at the downward equilibrium point by revealing that the point is saddle (hyperbolic and unstable). Specifically, we show that the Jacobian matrix evaluated at the point has two and two eigenvalues in the open left- and right-half planes, respectively. We prove that the pendulum will eventually be swung up into the basin of attraction of any locally stabilizing controller for all initial conditions with the exception of a set of Lebesgue measure zero. Finally, we validate the presented theoretical results via numerical simulation of two rotational pendulums. Our simulation results show that the swing-up control can be achieved quickly under the improved conditions on the control parameters.
This paper treats two-fold symmetrical SIW directional couplers with simple structure and broadband characteristics. The proposed directional coupler consists of a rectangular cavity connected four input/output ports ...
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Data mining techniques are important to sift through the huge amount of gene expression values in microarrays resulting in valuable biological knowledge. An important example is classifying cancer samples, which is cr...
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Data mining techniques are important to sift through the huge amount of gene expression values in microarrays resulting in valuable biological knowledge. An important example is classifying cancer samples, which is crucial to biologists for cancer diagnosis and treatment. In this paper we propose the DMCA technique in which the main objective is reducing the number of genes needed for accurate classification. The proposed technique is a combination of two feature selection techniques, f-score and entropy-based, and a powerful classifier, Support Vector Machines. DMCA achieved promising results and is characterized by being flexible in all of its stages. When applied to two public microarray datasets, DMCA succeeded in reducing the number of gene expression values needed to classify a sample by 71.29% and guaranteed reliable classification accuracy.
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