Developing a New Weighted Voting Algorithm based on Markov Model

Voting is an important operation in multichannel computation paradigm and realization of ultrareliable and real-time control systems that arbitrates among the results of N redundant variants. These systems include N-modular redundant (NMR) hardware systems and diversely designed software systems based on N-version programming (NVP). Depending on the characteristics of the application and the type of selected voter, the voting algorithms can be implemented for either hardware or software systems. In this paper, a novel voting algorithm is introduced for real-time fault-tolerant control systems, appropriate for applications in which N is large. Then, its behavior has been software implemented in different scenarios of error-injection on the system inputs. The results of analyzed evaluations through plots and statistical computations have demonstrated that this novel algorithm does not have the limitations of some popular voting algorithms such as median and weighted; moreover, it is able to significantly increase the reliability and availability of the system in the best case to 2489.7% and 626.74%, respectively, and in the worst case to 3.84% and 1.55%, respectively.

A TMR Genetic Voting Algorithm for Fault-tolerant Medical Robot

An important problem in fault-tolerant distributed computer systems is maintaining agreement between nonfaulty processes in the presence of undiagnosed faults. Approximate agreement defines a condition in which it is not necessary for the agreed values to be numerically identical. Rather, processes need only agree with each other to within a predefined numerical tolerance. Convergent voting algorithms which achieve approximate agreement have been studied in the context of two classes of systems, synchronous and asynchronous. Studies have also addressed both completely connected and partially connected systems. Together, the two properties of synchrony and connectivity yield 4 different voting domains. In all studies to date, each voting domain has been treated as a separate problem. This paper: shows that for at least one broad family of voting algorithms, the 4 domains are special cases of a more general convergent voting problem; analyzes convergent voting under the 3-mode hybrid fault model of Thambidurai and Park; and presents a set of unifying relations applicable to all 4 voting domains. These relations are used to specify voting algorithms which optimize fault-tolerance, convergence rate, or computational overhead in any given voting domain. The task of designing a voting algorithm for a particular fault-tolerant system is thus greatly simplified.

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N-version programming is one of the most common techniques which is used to improve the reliability of software by building in fault tolerance, redundancy and decreasing common cause failures. N different equivalent software versions are developed by N different and isolated workgroups by considering the same software specifications. The versions solve the same task and return results that have to be compared to determine the correct result. Decisions of N different versions are evaluated by a voting algorithm or the so-called voter. In this paper, two of the most commonly used software voting algorithms such as the majority voting algorithm and the consensus voting algorithm are studied. The distinctive features of Nversion programming with majority voting and N-version programming with consensus voting are described. These two algorithms make a decision about the correct result on the base of the agreement matrix. However, if the equivalence relation on the agreement matrix is not satisfied it is impossible to make a decision. It is shown that the agreement matrix can be transformed into an appropriate form by using the Boolean compositions when the equivalence relation is satisfied.

Estimation of solubility of acid gases in ionic liquids using different machine learning methods

In this work, we study the rank aggregation problem based on election voting model. In addition to classical voting rules: Borda, some elimination voting algorithms, including Kemeny methods, are analyzed in a graph theoretic approach. As the Kemeny ranking problem is NP-hard, a new heuristic elimination voting algorithm is proposed in this work. Some experiments have been carried out on TREC data for evaluating these voting algorithms on rank aggregation. The experiments indicate that these elimination algorithms have comparable performance with Borda algorithms, and sometimes outperform it

Metasearch engines are developed to overcome the shortcoming of single search engine and try to benefit from cooperative decision by combining the results of multiple independent search engines that make use of different models and configurations. In this work, we study the metasearch problem via voting that facilities multiple agents making cooperative decision. We can deem the source search engines as voters and all ranked documents as candidates, then metaseach problem is actually to find a voting algorithm to obtain group’s preferences on these documents(candidates). In addition to two widely discussed classical voting rules: Borda and Condorcet, we study another two voting algorithms, Black and Kemeny. Since Kemeny ranking problem is NP-hard, a new heuristic algorithm has been proposed for metasearch. Some experiments have been carried out on TREC2001 data for evaluating these metasearch algorithms coming from voting.KeywordsSearch EngineCondorcet WinnerStrongly Connect ComponentBorda RuleVote AlgorithmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Fault-tolerant systems are such systems that can continue their operation, even in presence of faults. Redundancy as one of the main techniques in implementation of fault-tolerant control systems uses voting algorithms to choose the most appropriate value among multiple redundant and probably faulty results. Average (mean) voter is one of the commonest voting methods which is suitable for decision making in highly-available and long-missions applications in which the availability and speed of the system is critical. In this paper we introduce a new generation of average voter based on parallel algorithms which is called as parallel average voter. The analysis shows that this algorithm has a better time complexity (log n) in comparison with its sequential algorithm and is especially appropriate for applications where the size of input space is large.

Currently, using commercial off-the-shelf (COTS) components and constructing parallel system becomes the main way to improve satellite system performance remarkably. System reliability relying on its structure rather than devices makes system fault-tolerant architecture and strategy increasingly important. As centralized fault-tolerant solution has the inherent drawback of single point of failure (SPOF), it can not guarantee system reliability well. Distributed fault- tolerant method, due to its complexity and large overhead, has not been maturely used. In this paper, we propose a new distributed fault-tolerant scheme with high reliability and flexibility, in which an equal symmetric distributed fault- tolerant (ESDFt) architecture is constructed. Based on the structure, functional module framework of system nodes and autonomous fault-tolerant strategy are designed. The ESDFt scheme creates favorable conditions for flexible implementation of system fault tolerance. It utilizes the master election mechanism, which eliminates the risks of SPOF and chooses master node intelligently based on user's configuration, making fault-tolerant complexity and processing overhead flexibly adjustable. The verification and evaluation of ESDFt scheme has been performed on a prototype system. The experiment results prove that ESDFt scheme not only ensures system reliability well, but also enhances system flexibility and practicality at the same time.

In this study, long term component reliability analysis of PV system is performed using Markov method. Four major components for evaluation of the system are considered with 16 different states to evaluate a PV system as a package with one reliability index. The probability analysis for each state shows that although at very first years the states of combination of multiple failures are negligible, after several years of operation, all states are effective in the reliability of the system. Based on Markov modeling given in the study and actual failure and repair rates of components, the reliability analysis shows that the reliability of the system decreases from 0.99 to 0.81 in 20 years. The initial condition for each year is gained from the final condition of the previous year. The annual value of the reliability of PV system makes the designers plan major maintenance and switching based on cost and load. 1

Actuation system is a key component of the flight control system. With the rapid development of reliable power-by-wire actuation technology for both aeronautical and space applications, more higher safety, efficiency, reliability, power density and dynamic property are required for actuation system. This paper introduces a kind of high reliable electromechanical actuator controller with dual-redundancy structure to improve the reliability and fault tolerance. By using cross feedback model and an online redundancy management strategy, the system response and fault tolerance are further advanced especially in case of transient faults. The principal for designing the system and the main structure are described, a compound control structure with feed forward control plus feedback control is adopted, the online BIT strategy for coordinating the two channels are explained and the hardware implementation is given. Experimental results show that the reliability of the system is improved with a small and simple structure while still maintaining a quick dynamic response, so that it is suitable for the electric servo control systems demanding high-reliability and high-dynamics in multi-/ all-electric vehicles.

In recent years, control system reliability has received much attention with increase of situations where computer-controlled systems such as robot control systems are used. In order to improve reliability, control systems need to have abilities to detect a fault (fault detection) and to maintain stability and control performance (fault tolerance). In this paper, we address the vibration suppression control of a one-link flexible arm robot. Vibration suppression is realized by an additional feedback of a strain gauge sensor attached to the arm besides motor position. However, a sensor fault (e.g., disconnection) may degrade the control performance and make the control system unstable at its worst. In this paper, we propose a fault tolerant control system for strain gauge sensor fault. The proposed control system has a strain gauge sensor signal observer based on the reaction force observer and detects the fault by monitoring the estimation error. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault mode controller so as to maintain the stability and the control performance. We apply the proposed control system to the vibration suppression control system of a one-link flexible arm robot and confirm the effectiveness of the proposed control system by some experiments.

This paper shows the span of results which can be obtained by modeling a system's behavior by stochastic processes and demonstrates practical rules for employing Markov and semi-Markov models. The introduction summarizes several methods for reliability analysis and gives the advantages and drawbacks of four methods: Markov processes, semi-Markov processes, supplementary variables, the method of stages. The remainder deals with reliability and availability modeling of a 2-unit redundant computer system. There are a) two types of maintenance: corrective (c. m.) and preventive (p. m.), and b) two system parameters: coverage, and an increased failure rate when one unit is under repair or inspection. Approximate expressions for reliability, mean time to failure, and asymptotic availability show the effects of the system parameters as well as of the shapes of the Cdf's of the times related to maintenance actions. For c.m., Markov modeling is a good approximation. For p.m., Markov modeling is a rough approximation; one can go to semi-Markov models or to the method of stages. Lastly, an approximate expression is given for the mean inspection interval which maximizes reliability and availability for p.m.

Using Bayesian networks in reliability evaluation for subsea blowout preventer control system