A speed sensor fault-tolerant back-stepping controller with a new minimum probability voter based on signal strength (MPVSS) has been introduced in this paper. The major goal of MPVSS is to detect and to reconfigure t...
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ISBN:
(纸本)9781728128740
A speed sensor fault-tolerant back-stepping controller with a new minimum probability voter based on signal strength (MPVSS) has been introduced in this paper. The major goal of MPVSS is to detect and to reconfigure the induction motor control in case of speed sensor failure (intermittent disconnection of an incremental encoder) using sliding mode observer for low speed estimation and extended Kalman filter for medium and high speed estimation. Here, the proposed MPVSS enjoys the feature of insensitivity to rotor resistance variations and easiness to set its threshold. In fact, signal strength plays an essential role in releasing the designer from severe constraints imposed by selecting a correct voter threshold. Simulation results show the efficiency of the suggested method. Besides, the superiority of the presented approach has been confirmed by comparing its performance with a maximum-likelihood voting algorithm.
many areas are currently experiencing rapid growth, requiring reliable and fault-tolerant software in general and, in particular, management systems. The most effective today is multiversion programming, one of the ap...
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ISBN:
(纸本)9781538620854
many areas are currently experiencing rapid growth, requiring reliable and fault-tolerant software in general and, in particular, management systems. The most effective today is multiversion programming, one of the approaches to improve the reliability of software by introducing redundancy. With this approach, there arises the problem of choosing the right variant from the collection by the answer of multiple versions, which is solved by various decision algorithms, most often based on voting. The reliability of this solution greatly affects the reliability of the redundant system as a whole. The article considers existing decision-making algorithms in multiversion execution environments and suggests own modifications of existing voting algorithms and t / (n-1) algorithm. A software implementation of the simulation environment that implements simulations of versions with specified characteristics and proposed modified algorithms is considered. The results of the simulation are considered, the dependence of the reliability indicators of the system on its input parameters is shown, a comparative analysis of various decision algorithms is made on the basis of simulation results. The obtained results show the effectiveness of the proposed modifications of the voting algorithms by an agreed majority and the specificity of the t / (n-1) decision algorithm, which makes sense to apply not in all systems. Most importantly, the simulation results show the possibility of creating a reliable system from not reliable software components, which is very important, especially for areas where there are currently no highly reliable algorithms or software components.
In this paper, we validate and analyze the ability of an agent-based metaheuristic to facilitate the negotiation of consensus among distributed, networked agents. Our metaheuristic is based on the process honeybees us...
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ISBN:
(纸本)9781479925049
In this paper, we validate and analyze the ability of an agent-based metaheuristic to facilitate the negotiation of consensus among distributed, networked agents. Our metaheuristic is based on the process honeybees use to achieve consensus in selecting a new nest site. We show that our metaheuristic successfully guides systems to a consensus in a high percentage of cases and that the quorum size parameter controls the trade-off between optimality of choice versus time to consensus and failure rate. Despite agents having communication with only their local neighbors and the absence of centralized data aggregation, coordination, or mediation, our metaheuristic frequently results in the same consensus as that which would be returned by one or more well-known voting algorithms that require global knowledge and centralized tallying to generate a solution;when it does not, the returned consensus is usually an alternative similar in quality to the globally-informed option.
In this work, a two-stage architecture is used to analyze the information collected from several sensors. The first stage makes classifications from partial information of the entire target (i.e. from different points...
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In this work, a two-stage architecture is used to analyze the information collected from several sensors. The first stage makes classifications from partial information of the entire target (i.e. from different points of view or from different kind of measures) using a simple artificial neural network as a classifier. In addition, the second stage aggregates all the estimations given by the ensemble in order to obtain the final classification. Four different ensembles methods are compared in the second stage: artificial neural network, plurality majority, basic weighted majority, and stochastic weighted majority. However, not only reliability is an important factor but also adaptation is critical when the ensemble is working in changing environments. Therefore, the artificial neural network and the plurality majority algorithm are compared against our two proposed adaptive algorithms. Unlike artificial neural network, majority methods do not require previous training. The effects of improving the first stage and how the system behaves when different perturbations are presented have been measured. Results have been obtained from two applications: a realistic one and another simpler one, with more training examples for a more accurate comparison. These results show that artificial neural network is the most accurate proposal, whereas the most innovative proposed stochastic weighted voting is the most adaptive one.
Context: Nowadays the most effective way to improve the reliability of software is an approach with the introduction of software redundancy - multi-version programming. The reliability of a multi-version system is det...
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Context: Nowadays the most effective way to improve the reliability of software is an approach with the introduction of software redundancy - multi-version programming. The reliability of a multi-version system is determined not only by the reliability of the versions that make it up, but to a greater degree by the decision making algorithm. Objective: Our objective is evaluation and selection of the most reliable voting algorithms in multi-version environments. In order to get this objective there is a need to check all the algorithms in the execution environment, simulating characteristic of the developed system. Thus, we obtain the characteristics of the quality of the algorithm operation in precisely those conditions in which it will work in the system that is developed. Method: The article suggests weighted voting algorithms with a forgetting element, as well as modifications of existing voting algorithms. To be able to check the quality of their work, the simulation environment has been implemented that simulates the operation of the software multi-version execution environment. Results: The article substantiates the use of the most reliable decision making algorithms in the decision block of the real-time operating system. A comparative analysis of decision making algorithms for the operation of the decision making block of the multi-version real-time execution environment has been carried out. Conclusions: The software implementation of the simulation environment that implements the simulations of versions with given characteristics is considered, not only classical decision making algorithms, but also the author's modifications are investigated. The environment allows to obtain the quality characteristics of all implemented decision making algorithms with given system characteristics. The modeling results are considered, the dependence of the system reliability indicators on its input parameters is shown, a comparative analysis of various decision making al
A speed sensor fault-tolerant back-stepping controller with a new minimum probability voter based on signal strength (MPVSS) has been introduced in this paper. The major goal of MPVSS is to detect and to reconfigure t...
详细信息
ISBN:
(纸本)9781728128757
A speed sensor fault-tolerant back-stepping controller with a new minimum probability voter based on signal strength (MPVSS) has been introduced in this paper. The major goal of MPVSS is to detect and to reconfigure the induction motor control in case of speed sensor failure (intermittent disconnection of an incremental encoder) using sliding mode observer for low speed estimation and extended Kalman filter for medium and high speed estimation. Here, the proposed MPVSS enjoys the feature of insensitivity to rotor resistance variations and easiness to set its threshold. In fact, signal strength plays an essential role in releasing the designer from severe constraints imposed by selecting a correct voter threshold. Simulation results show the efficiency of the suggested method. Besides, the superiority of the presented approach has been confirmed by comparing its performance with a maximum-likelihood voting algorithm.
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