In this paper, redundancy resolution of a cable-driven parallel manipulator is solved by an iterative-analytic scheme. The method can be applied to all kind of redundant manipulators either parallel or serial with con...
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In this paper, redundancy resolution of a cable-driven parallel manipulator is solved by an iterative-analytic scheme. The method can be applied to all kind of redundant manipulators either parallel or serial with constraint caused through their dynamics. However, for sake of simulation the proposed method is implemented on a cable-driven redundant parallel manipulator (CDRPM). The redundancy resolution problem is formulated as a convex optimization with equality and non-equality constraints caused by manipulator structure and cables dynamics. Karush-Kuhn-Tucker theorem is used to analyze the optimization problem and to find an analytic solution. Subsequently, a tractable and iterative search algorithm is proposed to solve the redundancy resolution of such redundant mechanisms. Furthermore, it is shown through the simulation that, the elapsed time required to implement the analytical redundancy resolution scheme in a closed-loop structure is considerably less than that of other numerical optimization methods.
An important issue in the analysis of two-dimensional electrophoresis images is the detection and quantification of protein spots. The main challenges in the segmentation of 2DGE images are to separate overlapping pro...
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An important issue in the analysis of two-dimensional electrophoresis images is the detection and quantification of protein spots. The main challenges in the segmentation of 2DGE images are to separate overlapping protein spots correctly and to find the abundance of weak protein spots. To enable comparison of protein patterns between different samples, it is necessary to match the patterns so that homologous spots are identified. In this paper we describe a new robust technique to segment and model the different spots present in the gels. The watershed segmentation algorithm is modified to handle the problem of over segmentation by initially partitioning the image to mosaic regions using the composition of fuzzy relations. The experimental results showed the effectiveness of the proposed algorithm to overcome the over segmentation problem associated with the available algorithms.
A multivariable fuzzy controller developed for the simultaneous administration of the anaesthetic drug (propofol) and the analgesic drug (remifentanil), is presented. The controller was designed in order to achieve a ...
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A multivariable fuzzy controller developed for the simultaneous administration of the anaesthetic drug (propofol) and the analgesic drug (remifentanil), is presented. The controller was designed in order to achieve a steady state level of depth of anaesthesia (DOA) and to reduce the amount of drug infused. The multivariable fuzzy controller is based on linguistic rules that interact with three decision tables, one of which represents a fuzzy PI controller. Optimisation using genetic algorithms was used to determine the scaling factors of the fuzzy PI controller. According to the different possibilities for the DOA level and for the surgical stimuli, the multivariable controller defines the required change in the infusion rates of the two drugs. A patient model remifentanil was used to test the multivariable controller. The controller was able to adjust the remifentanil infusion rate according to the stimulus intensity, and takes advantage of the synergistic interaction to the change adequately the propofol infusion rate. The multivariable fuzzy controller was tested under different simulations, and responded efficiently to different induction profiles, set point changes and disturbances.
In this paper, we propose a new model reduction technique for linear stochastic systems that builds upon knowledge filtering and utilizes optimal Kalman filtering techniques. This new technique will reduce the dimensi...
In this paper, we propose a new model reduction technique for linear stochastic systems that builds upon knowledge filtering and utilizes optimal Kalman filtering techniques. This new technique will reduce the dimension of the noise disturbance and will allow any controller designed for the reduced model to be refined into a controller for the original stochastic system, while preserving any specification on the output. Although initially the reduced model will be time-varying, a method will be provided with which the reduced model can become time-invariant if it satisfies some minor technical conditions. We present our theoretical findings with an example that supports the proposed framework and illustrates how model reduction and controller refinement of stochastic systems can be achieved. We finish the paper by considering specific examples to analyze both completeness with respect to controller synthesis and model order reduction with respect to the state.
作者:
宋红石峰Department of Computer Science and Engineering
Beijing Institute of Technology Beijing 100081 China Department of Computer Science and Engineering
Beijing Institute of Technology Beijing 100081 Chinaecurity access control systems and automatic video surveillance systems are becoming increasingly important recently and detecting human faces is one of the indispensable processes. In this paper an approach is presented to detect faces in video surveillance. Firstly both the skin-color and motion components are applied to extract skin-like regions. The skin-color segmentation algorithm is based on the BPNN (back-error-propagation neural network) and the motion component is obtained with frame difference algorithm. Secondly the image is clustered into separated face candidates by using the region growing technique. Finally the face candidates are further verified by the rule-based algorithm. Experiment results demonstrate that both the accuracy and processing speed are very promising and the approach can be applied for the practical use.
Security access controlsystems and automatic video surveillance systems are becoming increasingly important recently,and detecting human faces is one of the indispensable *** this paper,an approach is presented to de...
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Security access controlsystems and automatic video surveillance systems are becoming increasingly important recently,and detecting human faces is one of the indispensable *** this paper,an approach is presented to detect faces in video ***,both the skin-color and motion components are applied to extract skin-like *** skin-color segmentation algorithm is based on the BPNN (back-error-propagation neural network) and the motion component is obtained with frame difference ***,the image is clustered into separated face candidates by using the region growing ***,the face candidates are further verified by the rule-based *** results demonstrate that both the accuracy and processing speed are very promising and the approach can be applied for the practical use.
Many undergraduate engineering students have just a single introductory feedback control course in their study list. Often the curricula found in such courses is totally based on continuous time-domain classic control...
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Many undergraduate engineering students have just a single introductory feedback control course in their study list. Often the curricula found in such courses is totally based on continuous time-domain classic control techniques. However, currently most control design techniques are implemented in digital machines. Thus, digital control concepts should be covered in introductory control courses. In this paper, the issue of how to implement and test digital industrial controllers is addressed. Teaching experiments based on the APMonitor temperature control lab (TCLab) are proposed. It will be shown that TCLab as an Arduino based portable kit, provides an excellent means to test digital controllers, as it is a compact and portable lab to be used by lecturers and students. While there are many low-cost and portable hardware options for teaching dynamics and control, a novel aspect of this paper is the digital control education methods that are validated with classroom experience, particularly with Biomedical and Bioengineering students. Preliminary results are presented.
In this paper, a Linear Matrix Inequality approach is presented for synthesizing controllers that robustly stabilize a plant against Bicoprime Factor uncertainty. Following the development of the general case, non-nor...
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In this paper, a Linear Matrix Inequality approach is presented for synthesizing controllers that robustly stabilize a plant against Bicoprime Factor uncertainty. Following the development of the general case, non-normalized results, the usefulness of normalized Bicoprime Factorizations is studied in this context and shown to be beneficial in deducing the existence of a robustly stabilizing controller for given robust stability margin. Finally, a numerical example is provided to demonstrate the practical applicability of the developed methodology.
The problem of finding a unit in H/sub /spl infin// i.e., an H/sub /spl infin// function the inverse of which is also H/sub /spl infin//, which interpolates to given points in the right-half plane has important applic...
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The problem of finding a unit in H/sub /spl infin// i.e., an H/sub /spl infin// function the inverse of which is also H/sub /spl infin//, which interpolates to given points in the right-half plane has important applications in a number of feedback stabilization problems, i.e., strong stabilization (stabilization by a stable compensator) and simultaneous stabilization (finding a common fixed compensator which stabilizes a finite set of possible plants). The present paper gives an overview of the interpolation theory and some remarks observed with different mappings used in literature to find a unit in H/sub /spl infin//. A new algorithm is also presented to construct a unit in H/sub /spl infin//.
Introducing and using the spider monkey optimization (SMO) as an optimization technique for the electromagnetics and antenna community is the main goal of this paper. The SMO is a new swarm intelligence technique whic...
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Introducing and using the spider monkey optimization (SMO) as an optimization technique for the electromagnetics and antenna community is the main goal of this paper. The SMO is a new swarm intelligence technique which models the foraging behavior of spider monkeys. To show the efficiency of the SMO, different examples are presented in this work. The optimization procedure is used to synthesize the array factor of a linear antenna array and to optimally design a coaxial feeding patch antenna for wireless applications. The obtained results show that SMO is efficient in reaching the optimum solutions with few number of experiments.
The paper studies the problem of leakage localization in water distribution networks. For the case of a single pipe that suffers from a single leak, by taking recourse to pressure and flow measurements, and assuming t...
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ISBN:
(数字)9783907144077
ISBN:
(纸本)9781665497336
The paper studies the problem of leakage localization in water distribution networks. For the case of a single pipe that suffers from a single leak, by taking recourse to pressure and flow measurements, and assuming those are noiseless, we provide a closed-form expression for leak localization, leak exponent and leak constant. For the aforementioned setting, but with noisy pressure and flow measurements, an expression for estimating the location of the leak is provided. Finally, assuming the existence of a single leak, for a network comprising of more than one pipe and assuming that the network has a tree structure, we provide a systematic procedure for determining the leak location, the leak exponent, and the leak constant.
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