A fault tolerant control method is proposed in this paper for a turbofan engine gas path degradation through the full flight envelope. A Quantum-behaved Particle Swarm Optimization(QPSO) algorithm is applied to obtain...A fault tolerant control method is proposed in this paper for a turbofan engine gas path degradation through the full flight envelope. A Quantum-behaved Particle Swarm Optimization(QPSO) algorithm is applied to obtain engine inputs adjustments, which contribute to construct off-line performance accommodation interpolation schedules. With a double closed-loop control system structure, command control is corrected based on real-time fault diagnostic results. Simulations indicate that fault tolerant control could reduce thrust and stall margin loss effectively in gas path faults.展开更多
As a newly emerging computing paradigm, edge computing shows great capability in supporting and boosting 5G and Internet-of-Things (IoT) oriented applications, e.g., scientific workflows with low-latency, elastic, and...As a newly emerging computing paradigm, edge computing shows great capability in supporting and boosting 5G and Internet-of-Things (IoT) oriented applications, e.g., scientific workflows with low-latency, elastic, and on-demand provisioning of computational resources. However, the geographically distributed IoT resources are usually interconnected with each other through unreliable communications and ever-changing contexts, which brings in strong heterogeneity, potential vulnerability, and instability of computing infrastructures at different levels. It thus remains a challenge to enforce high fault-tolerance of edge-IoT scientific computing task flows, especially when the supporting computing infrastructures are deployed in a collaborative, distributed, and dynamic environment that is prone to faults and failures. This work proposes a novel fault-tolerant scheduling approach for edge-IoT collaborative workflows. The proposed approach first conducts a dependency-based task allocation analysis, then leverages a Primary-Backup (PB) strategy for tolerating task failures that occur at edge nodes, and finally designs a deep Q-learning algorithm for identifying the near-optimal workflow task scheduling scheme. We conduct extensive simulative case studies on multiple randomly-generated workflow and real-world edge-IoT server position datasets. Results clearly suggest that our proposed method outperforms the state-of-the-art competitors in terms of task completion ratio, server active time, and resource utilization.展开更多
Failure is a systemic error that affects overall system performance and may eventually crash across the entire configuration.In Real-Time Systems(RTS),deadline is the key to successful completion of the program.If tas...Failure is a systemic error that affects overall system performance and may eventually crash across the entire configuration.In Real-Time Systems(RTS),deadline is the key to successful completion of the program.If tasks effectively meet the deadline,it means the system is working in pristine order.However,missing the deadline means a systemic fault due to which the system can crash(hard RTS)or degrade inclusive performance(soft RTS).To fine-tune the RTS,tolerance is the critical issue and must be handled with extreme care.This article explains the context of fault tolerance with improvised Joint EDF-RMS algorithm in RTS.The backup method has been derived to prevent the system from being recursively migrating the same task.If any task migrates three times,this migrated task will get shifted to the backup queue.This backup queue assigns the task to a backup processor and is destined for final execution.For performance evaluation purposes,a relative graph between fault and failure rates,failure and total processor utilization along with other averages have been evaluated.Furthermore,these archived results are compared with fault-tolerant Earliest Deadline First(EDF)and Rate Monotonic Scheduling(RMS)algorithms independently in relatively similar conditions.These comparisons show better performance against overloading conditions.展开更多
A token-bus-based design method of the distributedfault-tolerant industrial network is presented in this pa-per.The dual-link network is of hot-redundancy.The performance of the network is also discussed.
Average （mean） voter is one of the commonest voting methods suitable for decision making in highly-available and long-missions applications where the availability and the speed of the system are critical.In this pap...Average （mean） voter is one of the commonest voting methods suitable for decision making in highly-available and long-missions applications where the availability and the speed of the system are critical.In this paper,a new generation of average voter based on parallel algorithms and parallel random access machine（PRAM） structure are proposed.The analysis shows that this algorithm is optimal due to its improved time complexity,speed-up,and efficiency and is especially appropriate for applications where the size of input space is large.展开更多
This investigation deals with the intelligent system for parallel fault-tolerant diagnostic tests construction. A modified parallel algorithm for fault-tolerant diagnostic tests construction is proposed. The algorithm...This investigation deals with the intelligent system for parallel fault-tolerant diagnostic tests construction. A modified parallel algorithm for fault-tolerant diagnostic tests construction is proposed. The algorithm is allowed to optimize processing time on tests construction. A matrix model of data and knowledge representation, as well as various kinds of regularities in data and knowledge are presented. Applied intelligent system for diagnostic of mental health of population which is developed with the use of intelligent system for parallel fault-tolerant DTs construction is suggested.展开更多
The evolvable multiprocessor (EvoMP), as a novel multiprocessor system-on-chip (MPSoC) machine with evolvable task decomposition and scheduling, claims a major feature of low-cost and efficient fault tolerance. Non-ce...The evolvable multiprocessor (EvoMP), as a novel multiprocessor system-on-chip (MPSoC) machine with evolvable task decomposition and scheduling, claims a major feature of low-cost and efficient fault tolerance. Non-centralized control and adaptive distribution of the program among the available processors are two major capabilities of this platform, which remarkably help to achieve an efficient fault tolerance scheme. This letter presents the operational as well as architectural details of this fault tolerance scheme. In this method, when a processor becomes faulty, it will be eliminated of contribution in program execution in remaining run-time. This method also utilizes dynamic rescheduling capability of the system to achieve the maximum possible efficiency after processor reduction. The results confirm the efficiency and remarkable advantages of the proposed approach over common redundancy based techniques in similar systems.展开更多
Based on the influence of circuit element tolerances to the k-fault diagnosis, a method of fault diagnosis is presented which is called minimum tolerance estimation algorithm and has clear physical meaning. Using this...Based on the influence of circuit element tolerances to the k-fault diagnosis, a method of fault diagnosis is presented which is called minimum tolerance estimation algorithm and has clear physical meaning. Using this’method, an effective estimation of the equivalent fault sources can be obtained with less computing time. It is especially worthwhile to point out that an adaptive sub-optimum algorithm, which comes from the above method, requires even less computing-labor and is particularly suitable to more complicated circuits as well as real-time fault location.展开更多
This paper introduces Twist-routing, a new routing algorithm for faulty on-chip networks, which improves Maze-routing, a face-routing based algorithm which uses deflections in routing, and archives full fault coverage...This paper introduces Twist-routing, a new routing algorithm for faulty on-chip networks, which improves Maze-routing, a face-routing based algorithm which uses deflections in routing, and archives full fault coverage and fast packet delivery. To build Twist-routing algorithm, we use bounding circles, which borrows the idea from GOAFR+ routing algorithm for ad-hoc wireless networks. Unlike Maze-routing, whose path length is unbounded even when the optimal path length is fixed, in Twist-routing, the path length is bounded by the cube of the optimal path length. Our evaluations show that Twist-routing algorithm delivers packets up to 35% faster than Maze-routing with a uniform traffic and Erdos-Rényi failure model, when the failure rate and the injection rate vary.展开更多
Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting ...Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base （BRB）, where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization （EM） algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.展开更多
In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for th...In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for the distribution network only considers the information reported by the Feeder Terminal Unit(FTU)and the fault tolerance rate is low when the information is omitted or misreported.Therefore,this study considers the influence of the distributed generations(DGs)for the distribution network.This takes the CEIAS as a redundant information source and solves the model by applying a binary particle swarm optimization algorithm(BPSO).The improved Dempster/S-hafer evidence theory(D-S evidence theory)is used for evidence fusion to achieve the fault section location for the distribution network.An example is provided to verify that the proposed method can achieve single or multiple fault locations with a higher fault tolerance.展开更多
In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear ea...In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear easily. Circuit faults will inevitably lead to serious losses of availability or impeded mission success without self-repair over the mission duration. Traditional fault-repair methods based on redundant fault-tolerant technique are straightforward to implement, yet their area, power and weight cost can be excessive. Moreover they utilize all plug-in or component level circuits to realize redundant backup, such that their applicability is limited. Hence, a novel selfrepair technology based on evolvable hardware（EHW） and reparation balance technology（RBT） is proposed. Its cost is low, and fault self-repair of various circuits and devices can be realized through dynamic configuration. Making full use of the fault signals, correcting circuit can be found through EHW technique to realize the balance and compensation of the fault output-signals. In this paper, the self-repair model was analyzed which based on EHW and RBT technique, the specific self-repair strategy was studied, the corresponding self-repair circuit fault system was designed, and the typical faults were simulated and analyzed which combined with the actual electronic devices. Simulation results demonstrated that the proposed fault self-repair strategy was feasible. Compared to traditional techniques, fault self-repair based on EHW consumes fewer hardware resources, and the scope of fault self-repair was expanded significantly.展开更多
Purpose-In recent times,fuzzy logic is gaining more and more attention,and this is because of the capability of understanding the functioning of the system as per human knowledge-based system.The main contribution of ...Purpose-In recent times,fuzzy logic is gaining more and more attention,and this is because of the capability of understanding the functioning of the system as per human knowledge-based system.The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm(FPA)using concepts of fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.Design/methodology/approach-The fuzzy logic-based parameter adaptation in the FPA is proposed.In addition,type2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics,which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method,and,in reality,the effectiveness of the interval type2 fuzzy inference system(IT2 FIS)has shown to provide improved results as matched to type-1 fuzzy inference system(T1 FIS)in some latest work.Findings-One case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature.For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statitical analysis which validates the advantages of the interval type2 fuzzy FPA.The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.Originality/value-The main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type2 fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.展开更多
文摘A fault tolerant control method is proposed in this paper for a turbofan engine gas path degradation through the full flight envelope. A Quantum-behaved Particle Swarm Optimization(QPSO) algorithm is applied to obtain engine inputs adjustments, which contribute to construct off-line performance accommodation interpolation schedules. With a double closed-loop control system structure, command control is corrected based on real-time fault diagnostic results. Simulations indicate that fault tolerant control could reduce thrust and stall margin loss effectively in gas path faults.
基金supported National Key R&D Program of China with Grant number 2018YFB1403602Chongqing Technological innovation foundations with Grant numbers cstc2019jscx-msxm0652 and cstc2019jscx-fxyd0385+3 种基金Chongqing Key RD project with Grant number cstc2018jszx-cyzdX0081Jiangxi Key RD project with Grant number 2018ACE50029Sponsored by technological program organized by SGCC(No.52094020000U)Technology Innovation and Application Development Foundation of Chongqing under Grant cstc2020jscx-gksbX0010.
文摘As a newly emerging computing paradigm, edge computing shows great capability in supporting and boosting 5G and Internet-of-Things (IoT) oriented applications, e.g., scientific workflows with low-latency, elastic, and on-demand provisioning of computational resources. However, the geographically distributed IoT resources are usually interconnected with each other through unreliable communications and ever-changing contexts, which brings in strong heterogeneity, potential vulnerability, and instability of computing infrastructures at different levels. It thus remains a challenge to enforce high fault-tolerance of edge-IoT scientific computing task flows, especially when the supporting computing infrastructures are deployed in a collaborative, distributed, and dynamic environment that is prone to faults and failures. This work proposes a novel fault-tolerant scheduling approach for edge-IoT collaborative workflows. The proposed approach first conducts a dependency-based task allocation analysis, then leverages a Primary-Backup (PB) strategy for tolerating task failures that occur at edge nodes, and finally designs a deep Q-learning algorithm for identifying the near-optimal workflow task scheduling scheme. We conduct extensive simulative case studies on multiple randomly-generated workflow and real-world edge-IoT server position datasets. Results clearly suggest that our proposed method outperforms the state-of-the-art competitors in terms of task completion ratio, server active time, and resource utilization.
基金Deepak Dahiya would like to thank Deanship of Scientific Research at Majmaah University for supporting this work under Project No.R-2022-56.
文摘Failure is a systemic error that affects overall system performance and may eventually crash across the entire configuration.In Real-Time Systems(RTS),deadline is the key to successful completion of the program.If tasks effectively meet the deadline,it means the system is working in pristine order.However,missing the deadline means a systemic fault due to which the system can crash(hard RTS)or degrade inclusive performance(soft RTS).To fine-tune the RTS,tolerance is the critical issue and must be handled with extreme care.This article explains the context of fault tolerance with improvised Joint EDF-RMS algorithm in RTS.The backup method has been derived to prevent the system from being recursively migrating the same task.If any task migrates three times,this migrated task will get shifted to the backup queue.This backup queue assigns the task to a backup processor and is destined for final execution.For performance evaluation purposes,a relative graph between fault and failure rates,failure and total processor utilization along with other averages have been evaluated.Furthermore,these archived results are compared with fault-tolerant Earliest Deadline First(EDF)and Rate Monotonic Scheduling(RMS)algorithms independently in relatively similar conditions.These comparisons show better performance against overloading conditions.
文摘A token-bus-based design method of the distributedfault-tolerant industrial network is presented in this pa-per.The dual-link network is of hot-redundancy.The performance of the network is also discussed.
文摘Average （mean） voter is one of the commonest voting methods suitable for decision making in highly-available and long-missions applications where the availability and the speed of the system are critical.In this paper,a new generation of average voter based on parallel algorithms and parallel random access machine（PRAM） structure are proposed.The analysis shows that this algorithm is optimal due to its improved time complexity,speed-up,and efficiency and is especially appropriate for applications where the size of input space is large.
文摘This investigation deals with the intelligent system for parallel fault-tolerant diagnostic tests construction. A modified parallel algorithm for fault-tolerant diagnostic tests construction is proposed. The algorithm is allowed to optimize processing time on tests construction. A matrix model of data and knowledge representation, as well as various kinds of regularities in data and knowledge are presented. Applied intelligent system for diagnostic of mental health of population which is developed with the use of intelligent system for parallel fault-tolerant DTs construction is suggested.
文摘The evolvable multiprocessor (EvoMP), as a novel multiprocessor system-on-chip (MPSoC) machine with evolvable task decomposition and scheduling, claims a major feature of low-cost and efficient fault tolerance. Non-centralized control and adaptive distribution of the program among the available processors are two major capabilities of this platform, which remarkably help to achieve an efficient fault tolerance scheme. This letter presents the operational as well as architectural details of this fault tolerance scheme. In this method, when a processor becomes faulty, it will be eliminated of contribution in program execution in remaining run-time. This method also utilizes dynamic rescheduling capability of the system to achieve the maximum possible efficiency after processor reduction. The results confirm the efficiency and remarkable advantages of the proposed approach over common redundancy based techniques in similar systems.
基金Supported by the National Natural Science Foundation of Chilla
文摘Based on the influence of circuit element tolerances to the k-fault diagnosis, a method of fault diagnosis is presented which is called minimum tolerance estimation algorithm and has clear physical meaning. Using this’method, an effective estimation of the equivalent fault sources can be obtained with less computing time. It is especially worthwhile to point out that an adaptive sub-optimum algorithm, which comes from the above method, requires even less computing-labor and is particularly suitable to more complicated circuits as well as real-time fault location.
文摘This paper introduces Twist-routing, a new routing algorithm for faulty on-chip networks, which improves Maze-routing, a face-routing based algorithm which uses deflections in routing, and archives full fault coverage and fast packet delivery. To build Twist-routing algorithm, we use bounding circles, which borrows the idea from GOAFR+ routing algorithm for ad-hoc wireless networks. Unlike Maze-routing, whose path length is unbounded even when the optimal path length is fixed, in Twist-routing, the path length is bounded by the cube of the optimal path length. Our evaluations show that Twist-routing algorithm delivers packets up to 35% faster than Maze-routing with a uniform traffic and Erdos-Rényi failure model, when the failure rate and the injection rate vary.
基金the National High-tech Research and Development Program of China(No.2011AA7053016)National Natural Science Foundation of China(No.61174030)
文摘Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base （BRB）, where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization （EM） algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.
基金supported by the Science and Technology Project of State Grid Shandong Electric Power Company?“Research on the Data-Driven Method for Energy Internet”?(Project No.2018A-100)。
文摘In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for the distribution network only considers the information reported by the Feeder Terminal Unit(FTU)and the fault tolerance rate is low when the information is omitted or misreported.Therefore,this study considers the influence of the distributed generations(DGs)for the distribution network.This takes the CEIAS as a redundant information source and solves the model by applying a binary particle swarm optimization algorithm(BPSO).The improved Dempster/S-hafer evidence theory(D-S evidence theory)is used for evidence fusion to achieve the fault section location for the distribution network.An example is provided to verify that the proposed method can achieve single or multiple fault locations with a higher fault tolerance.
基金supported by the National Natural Science Foundation of China (Nos. 61271153, 61372039)
文摘In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear easily. Circuit faults will inevitably lead to serious losses of availability or impeded mission success without self-repair over the mission duration. Traditional fault-repair methods based on redundant fault-tolerant technique are straightforward to implement, yet their area, power and weight cost can be excessive. Moreover they utilize all plug-in or component level circuits to realize redundant backup, such that their applicability is limited. Hence, a novel selfrepair technology based on evolvable hardware（EHW） and reparation balance technology（RBT） is proposed. Its cost is low, and fault self-repair of various circuits and devices can be realized through dynamic configuration. Making full use of the fault signals, correcting circuit can be found through EHW technique to realize the balance and compensation of the fault output-signals. In this paper, the self-repair model was analyzed which based on EHW and RBT technique, the specific self-repair strategy was studied, the corresponding self-repair circuit fault system was designed, and the typical faults were simulated and analyzed which combined with the actual electronic devices. Simulation results demonstrated that the proposed fault self-repair strategy was feasible. Compared to traditional techniques, fault self-repair based on EHW consumes fewer hardware resources, and the scope of fault self-repair was expanded significantly.
文摘Purpose-In recent times,fuzzy logic is gaining more and more attention,and this is because of the capability of understanding the functioning of the system as per human knowledge-based system.The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm(FPA)using concepts of fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.Design/methodology/approach-The fuzzy logic-based parameter adaptation in the FPA is proposed.In addition,type2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics,which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method,and,in reality,the effectiveness of the interval type2 fuzzy inference system(IT2 FIS)has shown to provide improved results as matched to type-1 fuzzy inference system(T1 FIS)in some latest work.Findings-One case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature.For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statitical analysis which validates the advantages of the interval type2 fuzzy FPA.The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.Originality/value-The main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type2 fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.
基金This work was supported by the Program of National Nature Science Foundation of China under Grant No. 41301460 and 60934002, the Major Program of National High-Tech Research and Development Project of China under Grant No. G0701070111AA0102017, and the Application Fundamental Research Funds of Department of Science and technology of Sichuai Province under Grant No. 13JC0504.
