Showing papers on "Control reconfiguration published in 2014"

Event-triggered dynamic output feedback control for networked control systems

Abstract: This study is concerned with the event-triggered control for networked control systems via dynamic output feedback controllers (DOFCs). The output measurement signals of the physical plant are sampled periodically. An output-based discrete event-triggering mechanism is introduced to choose those only necessary sampled-data packets to be transmitted through a communication network for controller design. Under this event-triggering mechanism, the resultant closed-loop system is first modelled as a linear system with an interval time-varying delay. Then a novel stability criterion is established by employing the Lyapunov-Krasovskii functional approach. Based on this stability criterion, a new sufficient condition is derived to co-design both the desired DOFCs and the event-triggering parameters. Finally, a satellite control system is taken to show the effectiveness of the proposed method.

Fuzzy Adaptive Actuator Failure Compensation Control of Uncertain Stochastic Nonlinear Systems With Unmodeled Dynamics

Abstract: This paper investigates fuzzy adaptive actuator failure compensation control for a class of uncertain stochastic nonlinear systems in strict-feedback form. These stochastic nonlinear systems contain the actuator faults of both loss of effectiveness and lock-in-place, unmodeled dynamics, and without direct measurements of state variables. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is established to estimate the unmeasured states. By introducing the dynamical signal and the changing supply function technique design into the backstepping control design, a robust adaptive fuzzy fault-tolerant control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are bounded in probability in the presence of the actuator failures and the unmodeled dynamics. Simulation results are provided to show the effectiveness of the control approach.

Model Predictive Control of Swarms of Spacecraft Using Sequential Convex Programming

Abstract: DOI: 10.2514/1.G000218 This paper presents a decentralized, model predictive control algorithm for the optimal guidance and reconfiguration of swarms of spacecraft composed of hundreds to thousands of agents with limited capabilities. In previous work, J2-invariantorbitshavebeenfoundtoprovidecollision-freemotionforhundredsoforbitsinalowEarthorbit. This paper develops real-time optimal control algorithms for the swarm reconfiguration that involve transferring from one J2-invariant orbit to another while avoidingcollisions and minimizing fuel. The proposedmodel predictive control-sequential convex programming algorithm uses sequential convex programming to solve a series of approximate path planning problems until the solution converges. By updating the optimal trajectories during the reconfiguration, the model predictive control algorithm results in decentralized computations and communication between neighboring spacecraft only. Additionally, model predictive control reduces the horizon of the convex optimizations, which reduces the run time of the algorithm. Multiple time steps, time-varying collision constraints, and communication requirements are developed to guarantee stability, feasibility, and robustness of the model predictive control-sequential convex programming algorithm.

Optimal Distribution Feeder Reconfiguration for Reliability Improvement Considering Uncertainty

Abstract: This paper proposes a new method to improve the reliability of the distribution system using the reconfiguration strategy. In this regard, a new cost function is defined to include the cost of active power losses of the network and the customer interruption costs simultaneously. Also, in order to calculate the reliability indices of the load points, the reconfiguration technique is considered as a failure-rate reduction strategy. Regarding the reliability cost, the composite customer damage function is employed to find the customer interruption cost data. Meanwhile, a powerful stochastic framework based on a two- point estimate method is proposed to capture the uncertainty of random parameters. Also, a novel self-adaptive modification method based on the clonal selection algorithm is proposed as the optimization tool. The feasibility and satisfying performance of the proposed method are examined on the 69-bus IEEE test system.

Monolithic Silicon Integration of Scaled Photonic Switch Fabrics, CMOS Logic, and Device Driver Circuits

Abstract: We demonstrate 4 × 4 and 8 × 8 switch fabrics in multistage topologies based on 2 × 2 Mach-Zehnder interferometer switching elements. These fabrics are integrated onto a single chip with digital CMOS logic, device drivers, thermo-optic phase tuners, and electro-optic phase modulators using IBM's 90 nm silicon integrated nanophotonics technology. We show that the various switch-and-driver systems are capable of delivering nanosecond-scale reconfiguration times, low crosstalk, compact footprints, low power dissipations, and broad spectral bandwidths. Moreover, we validate the dynamic reconfigurability of the switch fabric changing the state of the fabric using time slots with sub-100-ns durations. We further verify the integrity of high-speed data transfers under such dynamic operation. This chip-scale switching system technology may provide a compelling solution to replace some routing functionality currently implemented as bandwidth- and power-limited electronic switch chips in high-performance computing systems.

Reconfigurable electrical interconnection strategies for photovoltaic arrays: A review

Abstract: Non-uniform irradiance significantly decreases the power delivered by solar photovoltaic arrays. A promising technique for compensating these power losses relies on dynamically reconfiguring the electrical connections between photovoltaic modules. This paper presents the current state-of-the-art strategies for photovoltaic array reconfiguration in order to increase the power output under partial shading and mismatch conditions. The different approaches have been compared in terms of effectiveness of the control algorithms, monitored electrical and environmental variables, overall hardware complexity and specific features of each solution. Finally, the most challenging aspects of the reconfiguration strategy are identified and further discussed.

4-D Arrays as Enabling Technology for Cognitive Radio Systems

Abstract: Time-modulation (TM) in four-dimensional (4-D) arrays is implemented by using a set of radio-frequency switches in the beam forming network to modulate, by means of periodic pulse sequences, the static excitations and thus control the antenna radiation features. The on-off reconfiguration of the switches, that can be easily implemented via software, unavoidably generates harmonic radiations that can be suitably exploited for multiple channel communication purposes. As a matter of fact, harmonic beams can be synthesized having different spatial distribution and shapes in order to receive signals arriving on the antenna from different directions. Similarly, the capability to generate a field having different frequency and spatial distribution implies that the signal transmitted by time-modulated 4-D arrays is direction-dependent. Accordingly, such a feature is also exploited to implement a secure communication scheme directly at the physical layer. Thanks to the easy software-based reconfigurability, the multiple harmonic beamforming, and the security capability, 4-D arrays can be considered as an enabling technology for future cognitive radio systems. In this paper, these potentialities of time-modulated 4-D arrays are presented and their effectiveness is supported by a set of representative numerical simulation results.

Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost

Abstract: Power loss reduction can be considered as one of the main purposes for distribution system operators. Reconfiguration is an operation process used for this optimisation by means of changing the status of switches in a distribution network. Recently, all system operators tried their best in order to obtain well-balanced distribution systems to decrease the operation cost, improve reliability and reduce power loss. This study presents an efficient method for solving the multi-objective reconfiguration of radial distribution systems with regard to distributed generators. The conventional distribution feeder reconfiguration (DFR) problem cannot meet the reliability requirements, because it only considers loss and voltage deviation as objective functions. The proposed approach considers reliability, operation cost and loss simultaneously. By adding the reliability objective to the DFR problem, this problem becomes more complicated than before and it needs to be solved with an accurate algorithm. Therefore this study utilises an Enhanced Gravitational Search Algorithm called EGSA which profits from a special mutation strategy in order to reduce the processing time and improve the quality of solutions, particularly to avoid being trapped in local optima. The proposed approach has been applied to two distribution test systems including IEEE 33 and 70-node test systems.

Novel neural networks-based fault tolerant control scheme with fault alarm.

Abstract: In this paper, the problem of adaptive active fault-tolerant control for a class of nonlinear systems with unknown actuator fault is investigated. The actuator fault is assumed to have no traditional affine appearance of the system state variables and control input. The useful property of the basis function of the radial basis function neural network (NN), which will be used in the design of the fault tolerant controller, is explored. Based on the analysis of the design of normal and passive fault tolerant controllers, by using the implicit function theorem, a novel NN-based active fault-tolerant control scheme with fault alarm is proposed. Comparing with results in the literature, the fault-tolerant control scheme can minimize the time delay between fault occurrence and accommodation that is called the time delay due to fault diagnosis, and reduce the adverse effect on system performance. In addition, the FTC scheme has the advantages of a passive fault-tolerant control scheme as well as the traditional active fault-tolerant control scheme's properties. Furthermore, the fault-tolerant control scheme requires no additional fault detection and isolation model which is necessary in the traditional active fault-tolerant control scheme. Finally, simulation results are presented to demonstrate the efficiency of the developed techniques.

Smart Distribution Grid: Optimal Day-Ahead Scheduling With Reconfigurable Topology

Abstract: This paper proposes an optimal operational scheduling framework to be taken in use in the distribution management system (DMS) as the heart of smart active distribution networks (ADNs). The proposed algorithm targets to optimally control active elements of the network, distributed generations (DGs) and responsive loads (RLs), seeking to minimize the day-ahead total operation costs. The technical constraints of the components and the whole system are accommodated in the ac power flow fashion. As an innovative point, the DMS effectively utilizes the hourly network reconfiguration capabilities being realized by the deployment of remotely controlled switches (RCSs). Accordingly, besides the optimal schedule of active elements, the optimal topology of the network associated with each hour of the scheduling time horizon is determined as well. The effect of hourly reconfiguration on the capacity release of DGs and RLs is highlighted, which could be envisaged as a new trend in the reserve scheduling problem. Considering practical issues, the maximum daily switching actions of RCSs as well as switching costs are judicially included. The optimization procedure is formulated as a mixed-integer nonlinear problem and tackled with the genetic algorithm. To validate the satisfactory performance of the proposed framework, a 33-bus ADN is thoroughly interrogated.

Robust static output-feedback controller design against sensor failure for vehicle dynamics

Abstract: This study deals with the design of a robust fault estimation and fault-tolerant control for vehicle lateral dynamics subject to external disturbance and unknown sensor faults. Firstly, a descriptor state and fault observer is designed to achieve the system state and sensor fault estimates simultaneously. Secondly, based on the information of on-line fault estimates, a robust fault-tolerant controller based on static output-feedback controller (SOFC) design approach is developed. To provide linear matrix inequalities of less conservatism, the results are conducted in the non-quadratic framework dealing with unmeasurable premise variables case. Simulation results show the effectiveness of the proposed control approach when the vehicle road adhesion conditions change and the sideslip angle is unavailable for measurement.

ZyCAP : efficient partial reconfiguration management on the Xilinx Zynq

Abstract: New hybrid FPGA platforms that couple processors with a reconfigurable fabric, such as the Xilinx Zynq, offer an alternative view of reconfigurable computing where software applications leverage hardware resources through the use of often reconfigured accelerators. For this to be feasible, reconfiguration overheads must be reduced so that the processor is not burdened with managing the process. We discuss partial reconfiguration (PR) on these architectures, and present an open source controller, ZyCAP, that overcomes the limitations of existing methods, offering more effective use of hardware resources in such architectures. ZyCAP combines high-throughput configuration with a high-level software interface that frees the processor from detailed PR management, making PR on the Zynq easy and efficient.

Distributed PI-control with applications to power systems frequency control

Abstract: This paper considers a distributed PI-controller for networked dynamical systems. Sufficient conditions for when the controller is able to stabilize a general linear system and eliminate static control errors are presented. The proposed controller is applied to frequency control of power transmission systems. Sufficient stability criteria are derived, and it is shown that the controller parameters can always be chosen so that the frequencies in the closed loop converge to nominal operational frequency. We show that the load sharing property of the generators is maintained, i.e., the input power of the generators is proportional to a controller parameter. The controller is evaluated by simulation on the IEEE 30 bus test network, where its effectiveness is demonstrated.

Adaptive PID-Sliding-Mode Fault-Tolerant Control Approach for Vehicle Suspension Systems Subject to Actuator Faults

Abstract: Advanced fault-tolerant control schemes are required for ensuring efficient and reliable operation of complex technological systems such as ground vehicles. A novel approach to fault-tolerant control design is proposed for a full-scale vehicle dynamic model with an active suspension system in the presence of uncertainties and actuator faults. The proposed control scheme uses a sliding-mode controller to generate the tracking signal to the valve for each of the four wheel subsystems for mitigating three degrees of freedom (3-DOF) heave-roll-pitch motion arising from road undulations. For each of the electrohydraulic valve-cylinder pair in each subsystem, an adaptive proportional-integralderivative (PID) controller is proposed. Designing an adaptation scheme for the PID gains to accommodate actuator faults is among the main contributions of this work. The focus on actuator faults is motivated by the fact that loss of actuator effectiveness is a critical fault scenario in vehicle suspension systems and that the probability of occurrence of faults in actuators is higher and more severe when compared with other components. To analyze the performance of the proposed approach, computer simulations are carried out to illustrate control performance, robustness, and fault tolerance. The performance of our approach is then compared with that of the sliding-mode control (SMC) approach presented by Chamseddine and Noura. Results clearly indicate the strength of the adaptation scheme and its ability to mitigate fault effects in a short time. Simplicity of the overall scheme and the stabilization of the system under both faulty and fault-free conditions are the main positive features of the proposed approach.

Two Active Fault-Tolerant Control Schemes of Induction-Motor Drive in EV or HEV

Abstract: In this paper, two active fault-tolerant control (AFTC) schemes dedicated to induction-motor drives in electric or hybrid vehicle powertrains are presented and compared. Fault detection and mitigation are merged to propose a robust algorithm against speed-sensor faults (fault is modeled as significant additional noise or an exponential type emulating a bias) leading to uncertainties in the measurement. The first architecture is a hybrid fault tolerant-control (FTC) with proportional-integral and H∞ controllers; the second architecture is the generalized internal model control (GIMC) with a natural reconfiguration. Both are built to ensure resilience while keeping good dynamic performances. For each architecture, the speed-sensor fault detection is based on an extended Kalman filter (EKF) that generates a residual vector. The correction method is calculated differently for the two schemes specifically in the switching transition phase between the nominal and robust controllers. A comparative study is carried out between the two FTC schemes.

Adaptive Fault-Tolerant Spacecraft Attitude Control Design With Transient Response Control

Abstract: This paper proposes an adaptive fault tolerant attitude controller, based on variable structure control, to address tracking control problem of spacecraft in the presence of unknown actuator failure, control input saturation and external disturbances In contrast to traditional robust fault tolerant attitude controllers, the proposed controller is capable of controlling the transient response of the closed loop system by means of a dedicated parameter Also this method does not require exact knowledge of the actuator faults and is implemented with uncertain value of fault information By adjusting a simple parameter dynamically and using Lyapunov direct method and the properties of quaternion representation, the ultimate boundedness of attitude and angular velocity errors in presence of external disturbances is proven Numerical simulations used to prove the success of proposed controller in achieving high attitude performance in the presence of external disturbances, inexact knowledge of fault information, actuator failures and control input saturation

Temporal-Logic Based Runtime Observer Pairs for System Health Management of Real-Time Systems

Abstract: We propose a real-time, Realizable, Responsive, Unobtrusive Unit (rt-R2U2) to meet the emerging needs for System Health Management (SHM) of new safety-critical embedded systems like automated vehicles, Unmanned Aerial Systems (UAS), or small satellites. SHM for these systems must be able to handle unexpected situations and adapt specifications quickly during flight testing between closely-timed consecutive missions, not mid-mission, necessitating fast reconfiguration. They must enable more advanced probabilistic reasoning for diagnostics and prognostics while running aboard limited hardware without affecting the certified on-board software. We define and prove correct translations of two real-time projections of Linear Temporal Logic to two types of efficient observer algorithms to continuously assess the status of the system. A synchronous observer yields an instant abstraction of the satisfaction check, whereas an asynchronous observer concretizes this abstraction at a later, a priori known, time. By feeding the system’s real-time status into a statistical reasoning unit, e.g., based on Bayesian networks, we enable advanced health estimation and diagnosis. We experimentally demonstrate our novel framework on real flight data from NASA’s Swift UAS. By on-boarding rt-R2U2 aboard an existing FPGA already built into the standard UAS design and seamlessly intercepting sensor values through read-only observations of the system bus, we avoid system integration problems of software instrumentation or added hardware. The flexibility of our approach with regard to changes in the monitored specification is not due to the reconfigurability offered by FPGAs; it is a benefit of the modularity of our observers and would also be available on non-reconfigurable hardware platforms such as ASICs.

Method and apparatus for creating a dynamically reconfigurable energy storage device

Abstract: A method and apparatus of creating a dynamically reconfigurable energy source comprised of individual, isolated, controllable energy modules, supported by software to measure and manage the energy modules and facilitate the reconfiguration, where the platform consisting of hardware, based upon an inverted H-Bridge circuitry, in combination with software which allows for real-time management, control, and configuration of the modules and uses a combination of software algorithms and localized electronic switches, to achieve a performance and functionality of the invention matching, or exceeding, traditional large, heavy, and expensive power electronics-based products used for charging, energy storage management, power inverting, and motor or load control

Dynamic Consideration of DC Microgrids With Constant Power Loads and Active Damping System—A Design Method for Fault-Tolerant Stabilizing System

Abstract: It is known that constant power loads (CPLs) can yield instability in dc-power systems under certain operating conditions. This instability phenomenon is due to the interaction between the dc-grid and the negative input impedance characteristic of the CPLs. Dynamic behavior and stability analysis of a dc-microgrid with CPLs is presented in this paper. Then, a method to design a fault-tolerant stabilizing system for a dc-microgrid with CPLs is presented. It consists in implementing a local stabilizing agent on each CPL. Then, a method to design the stabilizing system is proposed. The method is based on the definition and resolution of a constrained optimization problem. It permits to consider several fault scenarios, such as the electrical reconfiguration of the dc-microgrid, or the failure of an agent. To illustrate the method's effectiveness, it has been implemented and experimentally tested on a test bed.

Fault Detection and Fault Tolerant Operation of a Five Phase PM Motor Drive Using Adaptive Model Identification Approach

Abstract: Nowadays, the use of multiphase fault tolerant permanent magnet (PM) machines is a suitable solution for increasing the reliability of high-performance motion control applications. This solution requires fault detection, isolation, and control adaptation. For this reason, a new open switch fault detection scheme in voltage-source inverter supplying a PM motor is presented in this paper. The detection method is based on model identification of the motor phase currents. The detection scheme is fast, robust, general, and capable of detecting multiple faults. The control algorithm, detection method, isolation, and reconfiguration strategies are discussed. After that, the proposed method is implemented in the fault tolerant control of a five-phase brushless direct current (BLDC) motor drive. Simulation results in MATLAB/Simulink are shown to demonstrate the effectiveness of the proposed detection technique. Experimental results on a five-phase fault tolerant BLDC motor validate the theoretical developments.