Showing papers on "Control reconfiguration published in 2017"

C2PS: A Digital Twin Architecture Reference Model for the Cloud-Based Cyber-Physical Systems

Abstract: Cyber-physical system (CPS) is a new trend in the Internet-of-Things related research works, where physical systems act as the sensors to collect real-world information and communicate them to the computation modules (i.e. cyber layer), which further analyze and notify the findings to the corresponding physical systems through a feedback loop. Contemporary researchers recommend integrating cloud technologies in the CPS cyber layer to ensure the scalability of storage, computation, and cross domain communication capabilities. Though there exist a few descriptive models of the cloud-based CPS architecture, it is important to analytically describe the key CPS properties: computation, control, and communication. In this paper, we present a digital twin architecture reference model for the cloud-based CPS, C2PS, where we analytically describe the key properties of the C2PS. The model helps in identifying various degrees of basic and hybrid computation-interaction modes in this paradigm. We have designed C2PS smart interaction controller using a Bayesian belief network, so that the system dynamically considers current contexts. The composition of fuzzy rule base with the Bayes network further enables the system with reconfiguration capability. We also describe analytically, how C2PS subsystem communications can generate even more complex system-of-systems. Later, we present a telematics-based prototype driving assistance application for the vehicular domain of C2PS, VCPS, to demonstrate the efficacy of the architecture reference model.

Adaptive Sliding-Mode Control of Markov Jump Nonlinear Systems With Actuator Faults

Abstract: This technical note is concerned with the design problem of adaptive sliding-mode stabilization for Markov jump nonlinear systems with actuator faults. The specific information including bounds of actuator faults, bounds of the nonlinear term and the external disturbance is not available for the controller design. The main attention focuses on designing the adaptive sliding-mode controller to overcome these problems. Firstly, a sliding-mode surface is constructed such that the reduced-order equivalent sliding motion is stochastically stable. Secondly, the adaptive sliding-mode controller can drive the state trajectories of the system onto the sliding-mode surface in finite time, and can estimate the loss of effectiveness of actuator faults and bounds of the nonlinear term and the external disturbance online. Thirdly, the stochastic stability of the closed-loop system can be guaranteed. Finally, a practical example is provided to demonstrate the effectiveness of the presented results.

Prescribed Performance Fault-Tolerant Control of Uncertain Nonlinear Systems With Unknown Control Directions

Abstract: A low-complexity state feedback fault-tolerant control scheme guaranteeing prescribed tracking performance is proposed for a family of uncertain nonlinear systems with unknown control directions. Contrary to the current state-of-the-art, novel error transformation functions and new update laws related to performance functions are introduced to the control design such that no compensators or approximation structures are needed, in spite of actuation faults, component faults, and unknown nonlinearities. The proposed method is verified via a simulation on an inverted pendulum.

Power Quality Concerns in Implementing Smart Distribution-Grid Applications

Abstract: This paper maps the expected and possible adverse consequences for power quality of introducing several smart distribution-grid technologies and applications. The material presented in this paper is the result of discussions in an international CIGRE–CIRED joint working group. The following technologies and applications are discussed: 1) microgrids; 2) advanced voltage control; 3) feeder reconfiguration; and 4) demand-side management. Recommendations are given based on the mapping.

Optimal reconfiguration of distribution system connected with distributed generations: A review of different methodologies

Abstract: The Network Reconfiguration technique is a method which helps mitigate power losses from distribution systems. However, the reconfiguration technique can only do this up to a certain point. Further power loss reduction may be realized via the application of Distributed Generation (DG). However, the integration of DG into the distribution system at a non-optimal location may result in increased power losses and voltage fluctuations. Therefore, a strategy for the selection of optimal placement and sizing of the DG needs to be developed and at the same time ensure optimal configuration. Many heuristic and artificial intelligence methods have been proposed in the literature for optimal distribution network reconfiguration, DGs sizing, and location. This paper reviews some of the more recent methods for distribution network reconfiguration, DG placement, and sizing that are intended to minimize power losses and improve the voltage profile.

Distributed Formation and Reconfiguration Control of VTOL UAVs

Abstract: In this brief, a novel distributed cascade robust feedback control approach is proposed for formation and reconfiguration control of a team of vertical takeoff and landing (VTOL) unmanned air vehicles (UAVs). This approach is based on dynamic communication network. It guarantees intervehicle collision avoidance and considers dynamic constraints of UAVs. In the outer loop of the cascade formation control, a potential field approach is used to generate a desired velocity for each UAV, which ensures that the team of UAVs can perform formation flying, formation rotating and reconfiguration, avoid intervehicle collision, as well as track a specified virtual leader. In the inner loop of the cascade formation control, the velocity of each UAV is designed to track its desired velocity generated by the outer loop, subject to dynamic constraints. The proposed approach is demonstrated via both simulation and flight test.

Adaptive Fuzzy Decentralized Control for a Class of Large-Scale Nonlinear Systems With Actuator Faults and Unknown Dead Zones

Abstract: This paper studies the fault-tolerant control problem for a class of uncertain large-scale nonlinear systems with unknown dead zones and actuator failures, including outage, loss of effectiveness, and stuck. It is assumed that the lower and upper bounds of actuator efficiency factor, the unparametrizable time-varying stuck fault, the system coefficient, and the uncertain functions of our considered systems are unknown. By introducing a smooth function, fuzzy logic systems and a bound estimation approach, a decentralized backstepping design method of fault-tolerant tracking controller is developed for the systems under consideration. The proposed controller can compensate the effects of actuator faults and dead zones completely. It is proved that all the signals in the closed-loop systems are ultimately bounded, and the tracking control performance can be achieved by the proposed controller. In comparing with the existing results, the restrictions on the number of failures are removed and the stuck fault is allowed to be time-varying. Finally, simulation results show the efficiency of the proposed control scheme.

A comprehensive review on power distribution network reconfiguration

Abstract: Reconfiguration of radial distribution networks is becoming a viable solution for improving the performance of distribution networks. Configurations may be varied with manual or automatic switching operations so that all of the loads are supplied and reduce power loss, increase system security, and enhance power quality. Reconfiguration also relieves the overloading of the network components. The change in the network configuration is performed by opening sectionalizing (normally closed) and closing tie (normally open) switches of the network. These switchings are performed in such a way that the radiality of the network is maintained and all of the loads are energized. Several researchers have attempted to solve the power distribution network reconfiguration problem using various techniques. This paper presents a comprehensive survey on network reconfiguration to bring out a clear idea for future research.

Virtual Network Topology Adaptability Based on Data Analytics for Traffic Prediction

Abstract: The introduction of new services requiring large and dynamic bitrate connectivity can cause changes in the direction of the traffic in metro and even core network segments throughout the day. This leads to large overprovisioning in statically managed virtual network topologies (VNTs), which are designed to cope with the traffic forecast. To reduce expenses while ensuring the required grade of service, in this paper we propose a VNT reconfiguration approach based on data analytics for traffic prediction (VENTURE). It regularly reconfigures the VNT based on the predicted traffic, thus adapting the topology to both the current and the predicted traffic volume and direction. A machine learning algorithm based on an artificial neural network is used to provide robust and adaptive traffic models. The reconfiguration problem that takes as its input the traffic prediction is modeled mathematically, and a heuristic is proposed to solve it in practical times. To support VENTURE, we propose an architecture that allows collecting and storing data from monitoring at the routers and that is used to train predictive models for every origin-destination pair. Exhaustive simulation results of the algorithm, together with the experimental assessment of the proposed architecture, are finally presented.

Current Sensor Fault-Tolerant Control for Direct Torque Control of Induction Motor Drive Using Flux-Linkage Observer

Abstract: This paper proposes a novel fault-tolerant control (FTC) scheme for direct torque control of induction motor (IM) drives against the line current sensor failures. Three major steps involved in the proposed FTC scheme are the detection of sensor fault, isolation of the same, and finally, the reconfiguration by proper estimation. Third-difference operator employed in the motor line current is found suitable for the detection of the sensor fault, while flux-linkage observer-based current estimation scheme performs the task of estimation of line current post the occurrence of the fault. Furthermore, a decision-making logic circuitry isolates the faulty signal and simultaneously selects the appropriate estimated current signal to make the drive fault-tolerant. The proposed current sensor FTC scheme is simple and unique in nature. Moreover, it can be universally applied with any speed control schemes involving IM drive. The proposed scheme is simulated and extensively tested in MATLAB/Simulink. The obtained simulation results are also verified using a dSPACE-1104-based IM drive laboratory prototype to show the effectiveness of the scheme.

The RFET—a reconfigurable nanowire transistor and its application to novel electronic circuits and systems

Abstract: With CMOS scaling reaching the limits in the next decade, new approaches are required to enhance the functionality of electronic systems. Reconfigurability on the device level promises to realize more complex systems with a lower device count. In the last 5 years a number of interesting concepts have been proposed to realize such a device level reconfiguration. Among these the reconfigurable field effect transistor (RFET), a device that can be configured between an n-channel and p-channel behavior by applying an electrical signal, can be considered as an end of roadmap extension of current technology with only small modifications to the process flow [1]. This paper gives a review on the RFET basics and current status. In the first sections the state of the art of reconfigurable devices will be summarized [2] and the RFET will be introduced together with related devices based on silicon nanowire technology [3]. The device optimization with respect to device symmetry and performance will be discussed next [4,5]. The potential of the RFET device technology will then be shown by discussiing circuit implementations making use of the unique advantages of this device concept [6,7,8]. The basic device concept was also extended towards applications in flexible devices and sensors [9,10] extending the capabilities also towards so called More than Moore applications were new functionalities are implemented in CMOS base processes. Finally the prospects of the RFET device technology will be discussed.

Multi-objective electric distribution network reconfiguration solution using runner-root algorithm

Abstract: Display Omitted The runner-root algorithm (RRA) is adapted to solve the network reconfiguration problem.Five objectives namely power loss, load balancing among the branches, load balancing among the feeders, number of switching operations and node voltage deviation are considered.The proposed RRA method is applied to the 33-bus and 70-bus test networks for evaluation.The proposed RRA method has better performance in comparison to other methods. This paper presents a runner-root algorithm (RRA) for electric distribution network reconfiguration (NR) problem. The considered NR problem in this paper is to minimize real power loss, load balancing among the branches, load balancing among the feeders as well as number of switching operations and node voltage deviation using max-min method for selection of the final compromised solution. RRA is equipped with two explorative tools, which are random jumps with large steps and re-initialization strategy to escape from local optimal. Moreover, RRA is also equipped with an exploitative tool to search around the current best solution with large and small steps to ensure the obtained result of global optimization. The effectiveness of the applied RRA in both single- and multi-objective has been tested on 33-node and 70-node distribution network systems and the obtained test results have been compared to those from other methods in the literature. The simulation results show that the applied RRA can be an efficient method for network reconfiguration problems with single- and multi-objective.

Industrial Big Data Analysis in Smart Factory: Current Status and Research Strategies

Abstract: Under the background of cyber-physical systems and Industry 4.0, intelligent manufacturing has become an orientation and produced a revolutionary change. Compared with the traditional manufacturing environments, the intelligent manufacturing has the characteristics as highly correlated, deep integration, dynamic integration, and huge volume of data. Accordingly, it still faces various challenges. In this paper, we summarize and analyze the current research status in both domestic and aboard, including industrial big data collection, modeling of the intelligent product lines based on ontology, the predictive diagnosis based on industrial big data, group learning of product line equipment and the product line reconfiguration of intelligent manufacturing. Based on the research status and the problems, we propose the research strategies, including acquisition schemes of industrial big data under the environment of intelligent, ontology modeling and deduction method based intelligent product lines, predictive diagnostic methods on production lines based on deep neural network, deep learning among devices based on cloud supplements and 3-D self-organized reconfiguration mechanism based on the supplements of cloud. In our view, this paper will accelerate the implementation of smart factory.

Robust Adaptive Fault-Tolerant Control for a Class of Unknown Nonlinear Systems

Abstract: This paper studies the fault-tolerant tracking control problem for a class of strict-feedback nonlinear systems subjected to actuator faults and external disturbances. The prior knowledge for actuator fault, nonlinearity, and external disturbance is totally unknown, besides the control directions. Based on a backstepping approach, an adaptive fault-tolerant control scheme is developed, without utilizing neural networks. In the control design, a group of new feedback mechanisms are proposed to compensate for the unknown system dynamics and actuator faults. Furthermore, to relax a requirement of the initial system states, a modification technique is designed to adjust the reference signal and virtual control laws for a short time. It is shown that the global closed-loop stability is guaranteed and the tracking performance is achieved. The above result is illustrated via simulations on a one-link manipulator and a ship autopilot.

Fuzzy Adaptive Fault-Tolerant Output Feedback Attitude-Tracking Control of Rigid Spacecraft

Abstract: This paper proposes a stable adaptive fuzzy fault-tolerant attitude-tracking controller for a rigid spacecraft in the presence of unavailable velocities, external disturbance, actuator faults, and actuator saturation. Fuzzy logic systems are applied to approximate the unknown nonlinear function vector, and a fuzzy adaptive observer is designed to estimate the unmeasured velocity of the rigid body. By using the backstepping technique, a novel adaptive fuzzy attitude-tracking fault-tolerant control scheme is developed. It has been testified that this control approach guarantees that all signals of the rigid spacecraft are bounded and the tracking error between the system output and the reference signal converges to a small neighborhood of zero. Simulation examples with constant faults and time-variant faults are provided to show the fault-tolerant effectiveness of the control method.

Online Reconfiguration of Active Distribution Networks for Maximum Integration of Distributed Generation

Abstract: This paper proposes the online reconfiguration of active distribution networks. The control of the active/reactive output power of distributed generation (DG) units combined with the control of remote controlled switches are employed in order to minimize DG curtailment, alleviate lines congestion, and mitigate voltage rise issues due to DG integration. Convex relaxations of the ac power flow equations and mixed integer linear disjunctive formulations are adopted to the optimization model in order to obtain fast and optimal solutions using standard branch and bound solvers. The computation burden of the optimization procedure is drastically reduced by exploiting the assessment of switching actions, which is performed using multiple load/generation scenarios. The effectiveness of the proposed optimization model is verified using different distribution test systems.

Robust Control Allocation for Spacecraft Attitude Tracking Under Actuator Faults

Abstract: This brief addresses attitude tracking problems for an over-actuated spacecraft in the presence of actuator faults, imprecise fault estimation, and external disturbances. First, a model reference adaptive control technique is used to design a high-level controller to produce the three-axis virtual control torque. Then, taking fault estimation uncertainties into account, a robust control allocation (RobCA) strategy is proposed to redistribute virtual control signals to the remaining actuators when an actuator fault occurs. The RobCA is formulated as a min–max optimization problem, which deals with actuator faults directly without reconfiguring the controller and ensures some robustness of system performances. Finally, simulation results are provided to show the effectiveness of the overall control strategy.

A Fault-Tolerant Series-Resonant DC–DC Converter

Abstract: The series-resonant dc–dc converter (SRC) is widely used as power supply for telecommunications, wireless power transfer for electrical vehicle, and high-voltage power supplies. Recently, it became very popular in solid-state transformer application, where fault tolerance is a highly desired feature and it is obtained through redundancy. This letter proposes a reconfiguration scheme for the SRC for the case of failure in one semiconductor, which could drastically reduce the need of redundancy. Using the proposed scheme, the full-bridge based SRC can be reconfigured in a half-bridge topology, in order to keep the converter operational even with the failure [open circuit (OC) or short circuit (SC)] of one switch. As a drawback of this technique, the output voltage drops to half of its original value. Therefore, a novel reconfigurable rectifier based on the voltage-doubler topology is proposed as a solution to keep the output voltage constant after the fault. To verify the feasibility of the proposed scheme, the converter is tested experimentally in a 700–600 V prototype with 10 kW of output power. An insulated gate bipolar transistor (IGBT) SC fault is tested and the results confirm the effectiveness of the proposed approach.

On the Parameterized Complexity of Reconfiguration Problems

Abstract: We present the first results on the parameterized complexity of reconfiguration problems, where a reconfiguration variant of an optimization problem $$\mathcal {Q}$$Q takes as input two feasible solutions S and T and determines if there is a sequence of reconfiguration steps, ie a reconfiguration sequence, that can be applied to transform S into T such that each step results in a feasible solution to $$\mathcal {Q}$$Q For most of the results in this paper, S and T are sets of vertices of a given graph and a reconfiguration step adds or removes a vertex Our study is motivated by results establishing that for many NP-hard problems, the classical complexity of reconfiguration is PSPACE-complete We address the question for several important graph properties under two natural parameterizations: k, a bound on the size of solutions, and $$\ell $$l, a bound on the length of reconfiguration sequences Our first general result is an algorithmic paradigm, the reconfiguration kernel, used to obtain fixed-parameter tractable algorithms for reconfiguration variants of Vertex Cover and, more generally, Bounded Hitting Set and Feedback Vertex Set, all parameterized by k In contrast, we show that reconfiguring Unbounded Hitting Set is W[2]-hard when parameterized by $$k+\ell $$k+l We also demonstrate the W[1]-hardness of reconfiguration variants of a large class of maximization problems parameterized by $$k+\ell $$k+l, and of their corresponding deletion problems parameterized by $$\ell $$l; in doing so, we show that there exist problems in FPT when parameterized by k, but whose reconfiguration variants are W[1]-hard when parameterized by $$k+\ell $$k+l

Distributed Fault-Tolerant Control of Networked Uncertain Euler–Lagrange Systems Under Actuator Faults

Abstract: This paper investigates the distributed fault-tolerant control problem of networked Euler-Lagrange systems with actuator and communication link faults. An adaptive fault-tolerant cooperative control scheme is proposed to achieve the coordinated tracking control of networked uncertain Lagrange systems on a general directed communication topology, which contains a spanning tree with the root node being the active target system. The proposed algorithm is capable of compensating for the actuator bias fault, the partial loss of effectiveness actuation fault, the communication link fault, the model uncertainty, and the external disturbance simultaneously. The control scheme does not use any fault detection and isolation mechanism to detect, separate, and identify the actuator faults online, which largely reduces the online computation and expedites the responsiveness of the controller. To validate the effectiveness of the proposed method, a test-bed of multiple robot-arm cooperative control system is developed for real-time verification. Experiments on the networked robot-arms are conduced and the results confirm the benefits and the effectiveness of the proposed distributed fault-tolerant control algorithms.

Measures of reconfigurability and its key characteristics in intelligent manufacturing systems

Abstract: In recent years, the fields of reconfigurable manufacturing systems, holonic manufacturing systems, and multi-agent systems have made technological advances to support the ready reconfiguration of automated manufacturing systems. While these technological advances have demonstrated robust operation and been qualitatively successful in achieving reconfigurability, limited effort has been devoted to the measurement of reconfigurability in the resultant systems. Hence, it is not clear (1) to which degree these designs have achieved their intended level of reconfigurability, (2) which systems are indeed quantitatively more reconfigurable and (3) how these designs may overcome their design limitations to achieve greater reconfigurability in subsequent design iterations. Recently, a reconfigurability measurement process based upon axiomatic design knowledge base and the design structure matrix has been developed. Together, they provide quantitative measures of reconfiguration potential and ease. This paper now builds upon these works to provide a set of composite reconfigurability measures. Among these are measures for the key characteristics of reconfigurability: integrability, convertibility, and customization, which have driven the qualitative and intuitive design of these technological advances. These measures are then demonstrated on an illustrative example followed by a discussion of how they adhere to requirements for reconfigurability measurement in automated and intelligent manufacturing systems.

Adaptive Neural-Fuzzy Sliding-Mode Fault-Tolerant Control for Uncertain Nonlinear Systems

Abstract: This paper proposes an adaptive neural-fuzzy sliding-mode control method for uncertain nonlinear systems with actuator effectiveness faults and input saturation. The parameter dependence of the control scheme is removed from the bound of actuator faults by updating online. A neural-fuzzy model is developed to approximate the uncertain nonlinear terms and a sliding-mode online-updating controller is developed to estimate the bound of the actuator with no prior knowledge of the fault. The asymptotic stability is verified via the Lyapunov method in the presence of actuator faults and saturation. Furthermore, the adaptive neural-fuzzy control method is extended to the uncertain faulty nonlinear systems with integral sliding-mode manifold as well as other popular sliding-mode surfaces. A numerical example is presented to demonstrate the effectiveness of the derived results.

Current trends in reconfigurable modular robots design

Abstract: This article presents a review on trends in modular reconfigurable robots, comparing the evolution of the features of the most significant robots over the years and focusing on the latest designs. These features are reconfiguration, docking, degrees of freedom, locomotion, control, communications, size, and powering. For each feature, some of the most relevant designs are presented and the current trends in the design are discussed.

Fault-Tolerant Control for an Internet-Based Three-Tank System: Accommodation to Sensor Bias Faults

Abstract: This paper focuses on the fault-tolerant control problem for an Internet-based three-tank system in the presence of possible sensor bias faults. The Internet-based three-tank system is an experimental setup that can be regarded as a typical networked system for evaluating networked fault-diagnosis and fault-tolerant control methods. Packet dropout phenomenon in the sensor-to-controller link is considered in this paper, and the fault type we deal with is chosen as the sensor bias fault. Fault-diagnosis unit is designed toward an auxiliary system. Sensor bias faults can be detected by comparing the residual signal generated by the fault detection filter and a prescribed threshold. After that, the fault can be isolated by using the residual analysis approach. Once the fault is isolated, it can be estimated iteratively in the least-squares sense. A fault accommodation method is proposed, and a fault-tolerant control strategy is achieved based on the fault information provided by the fault-diagnosis unit. The approach brought forward in this paper is demonstrated via an experimental study on the practical Internet-based three-tank system. Results show the effectiveness and the applicability of the proposed techniques.

Optimal Control Algorithms for Reconfiguration of Shipboard Microgrid Distribution System Using Intelligent Techniques

Abstract: The distribution power system in ship is almost similar to an islanded microgrid and supplies energy to navigation, service, and operation system, as well as sophisticated systems of weapons and communications in future ships. After a fault occurs, reconfiguration refers to changing the topology of the shipboard microgrid power system (SMPS) in order to isolate system damage and restore lost loads/or optimize certain characteristics of the system in real time. Reconfiguration problem in shipboard microgrid is nonlinear with numerous discrete variables and additional constraints. Traditional optimization methods are not the best solution due to tendency of getting stuck to a suboptimal solution and/or not providing solution in real time. In this study, intelligent techniques, such as genetic algorithm and particle swarm optimization, have been applied for reconfiguration of SMPS. Proposed methods consider all the operational constraints and load priorities. Graph theory is utilized to model the SMPS and mathematically represent the shipboard system. Proposed intelligent reconfiguration algorithms were implemented using MATLAB and tested on 8-BUS and 13-BUS SMPS models including distributed generations and islanding. Test systems were reconfigured in three different possible scenarios by considering load priority, load magnitude, and by combining these two simultaneously. Developed reconfiguration algorithm was also implemented in real time using controller-in-the-loop with real-time digital simulator. Simulation results show satisfactory performance for several test operating scenarios.

A 1.06-to-5.09 TOPS/W reconfigurable hybrid-neural-network processor for deep learning applications

Abstract: An energy-efficient hybrid neural network (NN) processor is implemented in a 65nm technology. It has two 16×16 reconfigurable heterogeneous processing elements (PEs)arrays. To accelerate a hybrid-NN, the PE array is designed to support on demand partitioning and reconfiguration for parallel processing different NNs. To improve energy efficiency, each PE supports bit-width adaptive computing to meet variant bit-width of different neural layers. Measurement results show that this processor achieves a peak 409.6GOPS running at 200MHz and at most 5.09TOPS/W energy efficiency. This processor outperforms the state-of-the-art up to 5.2X in energy efficiency.