A Decentralized Autonomous Control on Highly Redundant Robot Manipulators

The control method of highly redundant robot manipulators is introduced. A decentralized autonomous control scheme is used to guide the movement of robot manipulators so that the work done by manipulators is minimized. The method of computing pseudoinverse which needs too many complicated calculation can be avoided. Then the calculation and control of robots are simplified. At the same time system robustness/fault tolerance is achieved.

APPLICATION OF ASSOCIATIVE MEMORY NEURAL NETWORK IN HIGH VOLTAGE TRANSMISSIONLINE FAULT DIAGNOSIS

Effective methods of enhancing the fault-tolerance property are proposed for two kinds of associative memory (AM) neural network (NN) used in high voltage transmission line fault diagnosis. For feedforward NN (FNN),the conception of 'fake attaction region' is presented to expand the attraction region artificially,and for the feedback Hopfield bidirectional AM NN (BAM-NN),the measure to add redundant neurons is taken to enhance NN's memory capacity and fault-tolerance property. Study results show that the NNs built not only can complete fault diagnosis correctly but also have fairly high fault-tolerance ability for disturbed input information sequence. Moreover FNN is a more convenient and effective method of solving the problem of power system fault diagnosis.

STUDY ON MEASURES OF FAULT TOLERANCE FOR DISTRIBUTED SYSTEM

Fault tolerant ability is an important aspect for overall evaluation of distributed system(DS). This paper discusses three measures for the evaluation: node/edge connectivity, number of spanning trees and synthetic connectivity. A numerical example for illustration and analysis is given, and the synthetic connectivity measure presented by this paper is proved to be rational and satisfactory.

A SOLUTION TO HIGH AVAILABILITY OF OPENSTOCK

High availability is a critical mission for business system. At first, an instance of business system OPENSTOCK for pharmacy is introduced including both client and server sides. Secondly, a solution to the high availability of this system is given in detail, including design and implementation. The essentiality of this solution consists of scope of system information, system parameter tables of service status, schedule strategies of load ba lance and how to acquire system parameters and detect service states. The solution proposed is scalable and application oriented and supporting load balance for high performance and fault tolerate for high reliability. This application system has been applied and verified realistically, and the features of this business system derived in this paper have been achieved.

Evolving Network Model with Local-Area Preference for Mobile Ad Hoc Network

To accurately describe the evolving features of Mobile Ad Hoc Networks (MANETs) and to improve the performance of such networks, an evolving topology model with local-area preference is proposed. The aim of the model, which is analyzed by the mean field theory, is to optimize network structures based on users' behaviors in MANETs. The analysis results indicate that the network generated by this evolving model is a kind of scale-free network. This evolving model can improve the fault-tolerance performance of networks by balancing the connectivity and two factors, i.e., the remaining energy and the distance to nodes. The simulation results show that the evolving topology model has superior performance in reducing the traffic load and the energy consumption, prolonging network lifetime and improving the scalability of networks. It is an available approach for establishing and analyzing actual MANETs.

Active Fault Tolerant Control of a Class of Nonlinear Time-Delay Processes

Based on a nonlinear state predictor (NSP) and a strong tracking filter (STF), a sensor fault tolerant generic model control (FTGMC) approach for a class of nonlinear time-delay processes is proposed. First, the NSP is introduced, and it is used to extend the conventional generic model control (GMC) to nonlinear processes with large input time-delay. Then the STF is adopted to estimate process states and sensor bias, the estimated sensor bias is used to drive a fault detection logic. When a sensor fault is detected, the estimated process states by the STF will be used to construct the process output to form a 'soft sensor', which is then used by the NSP (instead of the real outputs) to provide state predictors. These procedures constitute an active fault tolerant control scheme. Finally, simulation results of a three-tank-system demonstrate the effectiveness of the proposed approach.

Reliability Analysis of Sensor Networks

To Integrate the capacity of sensing, communication, computing, and actuating, one of the compelling technological advances of these years has been the appearance of distributed wireless sensor network (DSN) for information gathering tasks. In order to save the energy, multi-hop routing between the sensor nodes and the sink node is necessary because of limited resource. In addition, the unpredictable conditional factors make the sensor nodes unreliable. In this paper, the reliability of routing designed for sensor network and some dependability issues of DSN, such as MTTF (mean time to failure) and the probability of connectivity between the sensor nodes and the sink node are analyzed. Unfortunately, we could not obtain the accurate result for the arbitrary network topology, which is #P-hard problem. And the reliability analysis of restricted topologies clustering-based is given. The method proposed in this paper will show us a constructive idea about how to place energy-constrained sensor nodes in the network efficiently from the prospective of reliability.

An LMI Method to Robust Iterative Learning Fault-tolerant Guaranteed Cost Control for Batch Processes

Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller (ILRGCC). A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities (LMIs), and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.

Fault-Tolerant Control of Nonlinear Systems Based on Fuzzy Neural Networks

Due to its great potentisl value in theory and application, fault-tolerant control atrategies of nonlinear systems, especially combining with intelligent control methods, have been a focus in the academe. A fault-tolerant control method based on fuzzy neural networks was presented for nonlinear systems in this paper. The fault parameters were designed to detect the fault, adaptive updating method was introduced to estimate and track fault, and fuzzy neural networks were used to adjust the fault parameters and construct automated fault diagnosis. And the fault compeusation control force, which was given by fault estimation, was used to realize adaptive fault-tolerant control. This framework leaded to a simple structure, an accurate detection, and a high robusmess. The simulation results in induction motor show that it is still able to work well with high dynamic performance and control precision under the condition of motor parameters＇ variation fault and load torque disturbance.

An adaptive handoff management for fault tolerant mobile computing

Due to the mobility of mobile hosts,checkpoints and message logs of the computing process may disperseover different mobile support stations in the checkpointing and rollback recovery protocol for mobilecomputing.Three existing checkpoint handoff schemes do not give well consideration to the efficiency offailure-free process execution and the recovery speed of the failure process at the same time.A dynamicadaptive handoff management of the checkpointing and rollback recovery protocol for mobile computing isproposed in this paper.According to the individual feature and current state of each mobile host,differentimplementations are selected dynamically to complete the handoff process upon the handoff event.Performance analyses show that the proposed handoff management incurs a low loss of performance duringfailure-free and achieves a quick recovery upon the process fault.

Early Stage Software Reliability Estimation with Stochastic Reward Nets

This paper presents software reliability modeling issues at the early stage of a software development for fault tolerant software management system. Based on Stochastic Reward Nets, an effective model of hierarchical view for a fault tolerant software management system is put forward, and an approach that consists of system transient performance analysis is adopted. A quantitative approach for software reliability analysis is given. The results show its usefulness for the design and evaluation of the early-stage software reliability modeling when failure data is not available.

Nonlinear parity space applied to an electric autonomous vehicle

The autonomous navigation of an electric vehicle requires the implementation of a number of sensors and actuators intended to inform it about his environment or his position and velocity and deliver necessary inputs. That＇s why it is important to detect and locate sensor and actuator faults as soon as possible to enable the operator to run the vehicle in degraded mode or use the fault tolerant control system if it exists. The main purpose of this paper deals with sensors or actuators faults diagnosis of autonomous vehicle. A diagnosis method using a nonlinear model of the vehicle is developed. Nonlinear state space model of the autonomous electric vehicle is used with the method of nonlinear analytical redundancy to detect and to isolate faults occurred on sensors or actuators. Computer simulations are carried out to verify the effectiveness of the method.

Dependability Analysis for Fault-Tolerant Computer Systems Using Dynamic Fault Graphs

Dependability analysis is an important step in designing and analyzing safety computer systems and protection systems.Introducing multi-processor and virtual machine increases the system faults' complexity,diversity and dynamic,in particular for software-induced failures,with an impact on the overall dependability.Moreover,it is very different for safety system to operate successfully at any active phase,since there is a huge difference in failure rate between hardware-induced and softwareinduced failures.To handle these difficulties and achieve accurate dependability evaluation,consistently reflecting the construct it measures,a new formalism derived from dynamic fault graphs(DFG) is developed in this paper.DFG exploits the concept of system event as fault state sequences to represent dynamic behaviors,which allows us to execute probabilistic measures at each timestamp when change occurs.The approach automatically combines the reliability analysis with the system dynamics.In this paper,we describe how to use the proposed methodology drives to the overall system dependability analysis through the phases of modeling,structural discovery and probability analysis,which is also discussed using an example of a virtual computing system.

Research on the Network Intrusion Detection System based on Modified Particle Swarm Optimization Algorithm

In this paper, we conduct research on the network intrusion detection system based on the modified particle swarm optimization algorithm. Computer interconnection ability put forward the higher requirements for the system reliability design, the need to ensure that the system can support various communication protocols to guarantee the reliability and security of the network. At the same time also require network system, the server or products have strong ability of fault tolerance and redundancy, better meet the needs of users, to ensure the safety of the information data and the good operation of the network system. For this target, we propose the novel paradigm for the enhancement of the modern computer network that is innovative.

Low power and high write speed SEU tolerant SRAM data cell design

As feature size scales down, reliability issues like single event upset(SEU) have become serious for circuit and system designers, especially for those who work on memory and latch designs. In this paper, an improved SEU tolerant data cell design based on the Quatro-10 T cell is proposed. The introduced cell enhances the capability of SEU tolerance by weakening the key transistors in the feedback loop to block the effects of transient fault. Simulation results show that our proposed design achieves obvious higher resilience to SEU and better performance on speed and power dissipation at the expense of an increased area. The proposed cell is a fully SEU immune design with an amount of critical charge at least 7 times more than the Quatro-10 T cell and has the lowest Power Delay Product. It shows that our design is very suitable in high-performance circuit and system design.

Design and reliability,availability,maintainability,and safety analysis of a high availability quadruple vital computer system

With the development of high-speed railways in China,more than 2000 high-speed trains will be put into use.Safety and efficiency of railway transportation is increasingly important.We have designed a high availability quadruple vital computer (HAQVC) system based on the analysis of the architecture of the traditional double 2-out-of-2 system and 2-out-of-3 system.The HAQVC system is a system with high availability and safety,with prominent characteristics such as fire-new internal architecture,high efficiency,reliable data interaction mechanism,and operation state change mechanism.The hardware of the vital CPU is based on ARM7 with the real-time embedded safe operation system (ES-OS).The Markov modeling method is designed to evaluate the reliability,availability,maintainability,and safety (RAMS) of the system.In this paper,we demonstrate that the HAQVC system is more reliable than the all voting triple modular redundancy (AVTMR) system and double 2-out-of-2 system.Thus,the design can be used for a specific application system,such as an airplane or high-speed railway system.

Edge-Fault-Tolerant Properties of Augmented Cubes

As an enhancement on the hypercube Qn, the augmented cube AQn, pro- posed by Choudum and Sunitha [Choudum S.A., Sunitha V., Augmented cubes, Networks, 40（2）（2002）, 71-84], possesses some properties superior to the hypercube Qn. In this paper, assuming that （u, v） is an arbitrary fault-free d-link in an n-dimensional augmented cubes, 1 ≤ d ≤ n - 1, n ≥ 4. We show that there exists a fault-free Hamiltonian cycle in the augmented cube contained （u, v）, even if there are 2n - 3 link faults.