Asynchronous Operation Research Articles

Inverter‐side robust damping controller design of hybrid HVDC with cascaded multi‐infeed MMC converters in asynchronous situation

Objective it is known that the rectifier side control usually suffers from the time delay and long distance communication problems, which could make the damping controller to be invalid and decrease the system stability. Specifically, when the system is in asynchronous operation, the rectifier controllers cannot damp the oscillations in inverter side AC system. Thus, to design the HVDC damping controller at inverter side becomes a feasible solution to avoid these problems. Methods Based on the MMC control strategy, to design the damping controllers at inverter side, the mixed H2/H∞ robust method with regional pole placement is investigated for the two MMC inverters in constant active power control based on the master-slave control mode, where the robustness, control effort and the damping ratios can all be guaranteed simultaneously. During the design process, the simplified system models, namely the TLS-ESPRIT identification algorithm, is also used for controller study. Finally, two robust controllers are obtained based on the proposed method and the inverter side damping controllers are added at the MMCs of hybrid HVDC. Results The damping controllers for hybrid HVDC with cascaded multi-infeed MMCs can be designed at inverter side, which endows the hybrid HVDC with more control functions compared with the classical HVDC systems. The damping controllers can be added at the cascaded multi-infeed MMC inverters in constant active power control, which can enhance the connected AC systems' small stabilities. Conclusions Based on the multi-objective robust theory, the control effectiveness and robustness of the designed controllers can be guaranteed simultaneously, which can damp the low frequency oscillations significantly in different operating situations.

Mathematical modeling start-up and steady state modes of asynchronous motors operation with capacitive compensation of reactive power

Mathematical modeling start-up and steady state modes of asynchronous motors operation with capacitive compensation of reactive power

Analysis of Asynchronous Operating Conditions of Synchronous Machines Using Classical and Electromagnetic Models

Analysis of asynchronous conditions in a synchronous machine was initially made by classical method following the generalized machine theory. Later on, it took a turn after the advent of solid iron rotor/solid iron pole-shoe. It was noted that there is a discrepancy between computed and actual quantities between results obtained by the classical and the non-classical model. It was gradually understood that the reason behind this discrepancy was the effect of distributed eddy currents in the solid metallic parts. Authors like B.J. Chalmer, B. Adkins, A. Canay, and others, contributed much to the analysis of asynchronous conditions by adopting new techniques. The paper presents the methodology for using these techniques to estimate the asynchronous variables under loss of excitation (LOE), also to find the same by classical method based on generalized machine theory.

О двух методах вычисления трапециевидной характеристики устройства АЛАР на основе равномерных данных

The paper presents two methods to compute the trapezoidal characteristic of automatics for elimination of asynchronous operation (AEAO). The source data are hodographs of asynchronous operations (AO hodographs). Every AO hodograph is an array of active and reactive resistances values, which have been received or calculated with equal time step. The first method is based on the phase increase of characteristic size without proportions sacrificing of sensitive and coarse elements of the characteristic (trapeze). Trapeze bases are stretched as long as we have unfixed AO hodographs for AEAO. The second method is based on narrowing the coarse characteristic element without sacrificing the initial size of the sensitive element. Both methods are iterative homogenous operations algorithms. These homogenous operations are necessary to compute the cha­racteristic with minimal size and keep constraints for AEAO. The main emphasis of the characteristic computation is on keeping the sensitivity constraints and fixing the AO hodographs. These methods are used to build up a software. The paper also describes a computational experiment based on actual data. The experiment showed these methods are effective when calculating the AEAO sets. Experts on electrical modes can use these methods to adjust the AEAO with trapezoidal characteristic.

Temporal Memory With Magnetic Racetracks

Race logic is a relative timing code that represents information in a wavefront of digital edges on a set of wires in order to accelerate dynamic programming and machine learning algorithms. Skyrmions, bubbles, and domain walls are mobile magnetic configurations (solitons) with applications for Boolean data storage. We propose to use current-induced displacement of these solitons on magnetic racetracks as a native temporal memory for race logic computing. Locally synchronized racetracks can spatially store relative timings of digital edges and provide non-destructive read-out. The linear kinematics of skyrmion motion, the tunability and low-voltage asynchronous operation of the proposed device, and the elimination of any need for constant skyrmion nucleation make these magnetic racetracks a natural memory for low-power, high-throughput race logic applications.

Bi-adjusting duty cycle for green communications in wireless sensor networks

Green communications is a challenging issue for communications and networking. In order to save energy, nodes of the wireless sensor networks (WSNs) usually adopt the low duty cycle mode which brings a large delay to the event detection and data transmission to the sink and deteriorates the network’s timely processing of the event. In this paper, bi-adjusting duty cycle schedule (BADCS) scheme is proposed to reduce event detection latency as well as data routing delay for low duty cycle wireless sensor networks. BADCS scheme consists mainly of two duty cycle adjustment algorithms: (a) active slot asynchronous adjustment algorithm for nodes in the same sensing area; (b) the continuous adjustment algorithm for two adjacent nodes on the routing path with one active slot interval. Specifically, the operations are 2-fold. First, perform asynchronous operations on the active slots of the nodes in the same sensing area, so that the active slots of the nodes in the same sensing area are distributed as evenly as possible without overlapping. In this way, it is possible to reduce the latency by the time the event is perceived after its occurrence. Secondly, active slots of the nodes on the routing path are adjusted to be with pipeline style, so that when the nodes receive the data packet, they can route through the continuous active slots, thus greatly reducing the delay of data routing. Two adjustment algorithms of active slot are given in detail in this paper. The performance of BADCS mode is discussed in detail, and its performance is better than the previous strategy. Comprehensive experiments are conducted, and the results demonstrate that the proposed BADCS scheme significantly improves event detection performance in terms of detection latency, detection probability, and routing delay. Detection delay and routing delay are reduced as high as 3.91% and 56.22% respectively.

An asynchronous distributed gradient algorithm for economic dispatch over stochastic networks

The economic dispatch problem (EDP) in power systems is usually formulated as a category of convex optimization problems in which the collective cost function is expressed as the sum of all individual objectives of generators. It is inclined to be solved through a distributed way, which is to minimize the total generation cost while meet the demands under generator capability restrictions. In this paper, we consider this class of convex optimization problems that involve coupling linear constraint and individual box constraints. In order to make information communication of network decentralized, reliable and computationally inexpensive, an asynchronous distributed primal–dual optimization algorithm is proposed over stochastic networks. This algorithm allows nodes to use asynchronous communication strategy to update their state, and the step-sizes for seeking the optimum solution are uncoordinated constants. The asynchronous operation for generators takes link failures of networks into account. Under strongly convex assumption on objective functions, it is proved that the proposed algorithm can seek the exact optimal solution with probability one if the expectation of communication network is undirected connected. The effectiveness of the proposed optimization algorithm over stochastic networks is illustrated by provided simulation results.

Improving the performance of processing special computing tasks using an asynchronous actor model

The use of third-party ready-made solutions to perform special computing tasks (SCT): processing text arrays in a natural language, the use of cryptography methods in data transmission networks, machine learning in solving applied problems, scientific computations and many other ones is a common practice in modern development of software systems. However, the use of third-party ready-made software solutions often leads to their poor optimization for parallel and distributed operation and to the difficulty in vertical and horizontal scaling, impossibility of modifying a solution, e.g., due to its legal protection, etc. In order to solve these problems, an asynchronous actor model can be used that facilitates developing software for processing special computing tasks. In addition, an asynchronous actor model allows parallel processing of input tasks, provides asynchronous operation, and extends its functionality to third-party ready-made solutions, that it is impossible or forbidden to modify to meet user’s or optimization requirements. Methods, algorithms, and the entire logic of asynchronous actor operation involve transitions of actors from one state to another under the effect of input messages and returning the results of processed tasks to the frame system. This allows setting an automatic grammar and for using methods and approaches for developing software systems based on finite-state automata. The asynchronous actor operation scheme is represented by a directional state graph, which allows using the mathematical apparatus of the finite-state automaton theory (the Mealy model) to describe the same. The developed model is convenient for designing and organizing the SCT processing using computer systems. The use of the asynchronous actor model makes it possible, in special operation modes, to increase the performance of poorly optimized SCT without modifying the same, as compared to task processing without using the asynchronous actor model.

A fully integrated 10-bit 100 MS/s SAR ADC with metastability elimination for the high energy physics experiments

This paper presents a fully integrated 10-bit 100 MS/s successive approximation register (SAR) ADC for the high energy physics experiments. The ADC uses a non-binary weighted capacitor digital-to-analog converter (C-DAC) network and a hybrid capacitor switching procedure to increase conversion accuracy and speed. A metastability elimination technique is employed to avoid comparator metastability, and then reduce the conversion error rate (CER) at high-speed asynchronous operations. The full custom static logic is used to improve the radiation hardness. The ADC was designed and fabricated in a 40 nm CMOS process. It occupies 0.078 mm2 active area, including a reference generator, with a core area of 0.037 mm2. The measured ADC core power consumption and the total power consumption are 1.32 mW and 8.5 mW respectively, including the reference generator at a 1.1 V supply. The resulting figure-of-merit (FOM), for sampling rate 100 MS/s, is 130 fJ/conversion-step. It achieves a good dynamic performance with ∼9.3-bit effective number of bits (ENOB) at 100 MS/s with 14.97 MHz input signal. The measured spurious free dynamic range (SFDR), total harmonic distortion (THD) and signal-to-noise ratio (SNR) are 72.6 dB, −69.2 dB, 58.3 dB, respectively. The measured differential nonlinearity (DNL) and integral nonlinearity (INL) are +0.62/−0.4 LSB and +0.67/−0.54 LSB respectively.

Dynamic Event-Triggered Asynchronous Control for Nonlinear Multiagent Systems Based on T–S Fuzzy Models

In this article, the event-triggered asynchronous control problem of nonlinear multiagent systems is investigated based on Takagi-Sugeno fuzzy models. In order to rationally utilize network resources and elaborately avoid unnecessary continuous monitoring, an event-triggered mechanism with a new dynamic threshold parameter and a sampler are considered, respectively. Besides, an asynchronous operation method is adopted to deal with the mismatched premise variables between the fuzzy system and fuzzy controller. Based on the Lyapunov stability theory and appropriate inequality, some sufficient criteria in the form of linear matrix inequalities are obtained to ensure the stability of the closed-loop system. Finally, an illustrative example is provided to demonstrate the effectiveness and superiority of the proposed method.

Hybrid CPU/GPU tasks optimized for concurrency in OpenMP

Sierra and Summit supercomputers exhibit a significant amount of intranode parallelism between the host POWER9 CPUs and their attached GPU devices. In this article, we show that exploiting device-level parallelism is key to achieving high performance by reducing overheads typically associated with CPU and GPU task execution. Moreover, manually exploiting this type of parallelism in large-scale applications is nontrivial and error-prone. We hide the complexity of exploiting this hybrid intranode parallelism using the OpenMP programming model abstraction. The implementation leverages the semantics of OpenMP tasks to express asynchronous task computations and their associated dependences. Launching tasks on the CPU threads requires a careful design of work-stealing algorithms to provide efficient load balancing among CPU threads. We propose a novel algorithm that removes locks from all task queueing operations that are on the critical path. Tasks assigned to GPU devices require additional steps such as copying input data to GPU devices, launching the computation kernels, and copying data back to the host CPU memory. We perform key optimizations to reduce the cost of these additional steps by tightly integrating data transfers and GPU computations into streams of asynchronous GPU operations. We further map high-level dependences between GPU tasks to the same asynchronous GPU streams to further avoid unnecessary synchronization. Results validate our approach.

Design and Application of a Distribution Network Phasor Data Concentrator

The wide area measurement system (WAMS) based on synchronous phasor measurement technology has been widely used in power transmission grids to achieve dynamic monitoring and control of the power grid. At present, to better realize real-time situational awareness and control of the distribution network, synchronous phasor measurement technology has been gradually applied to the distribution network, such as the application of micro multifunctional phasor measurement units (μMPMUs). The distribution network phasor data concentrator (DPDC), as a connection node between the μMPMUs and the main station, is also gaining more attraction. This paper first analyzes the communication network structure of DPDCs and μMPMUs and compares and analyzes the differences in the installation locations, functions, communication access methods and communication protocols of the phasor technology devices of the distribution network and the transmission network. It is pointed out that DPDCs not only need the functions of data collection, storage, and forwarding like transmission network PDCs, but also should be able to access more μMPMUs, and can aggregate the phasor data of the same time scale from μMPMUs by different communication methods. The communication protocol selected by DPDC should be expanded to support remote control, telemetry, fault diagnosis and other functions of distribution automation. The application requirements of DPDCs are clarified, and the key indicators of DPDCs are given as a method to evaluate the basic performance of DPDCs. Then, to address the problems of more μMPMU access, abnormal communication, and data collection with different delays that DPDC encountered, a DPDC that considers multiple communication methods is designed. Based on the Linux system and the libuv library, the DPDC is designed with event-driven mechanism and structured programming, runs multiple threads to implement multitasking, and invokes callbacks to perform asynchronous non-blocking operations. The DPDC test system and test methods are designed. The performance of the designed DPDC is evaluated through the test and the test results are analyzed. Lastly, its real-world application is disclosed, which further confirmed the value of our DPDC.

Structural coloration using face turning and variable tool vibration frequency

Abstract The technique of manufacturing surface micro-/nano- structures to colorize metal surfaces by using elliptical vibrating cutting has been continuously developed and has good industrial potential. However, the image rendering is based on a raster scan path and constant variation of cutting velocity. The process efficiency and stability are significantly restricted. In this study, a new approach is proposed to implement the elliptical vibration texturing in a face turning setup, where the image rendering is achieved by an equidistant spiral tool path and modulation of the tool vibration frequency. The basic principle is that, while moving at a constant surface velocity, the tool follows a variable frequency elliptical vibration to machine gratings with different spacings on the workpiece surface. In order to ensure the uniformity in the radial direction and the consistency of the color under the same frequency excitation, a smoothly accelerated equidistant spiral tool path is designed. In addition, since the running speed of the machine tool is not completely synchronized with the signal of the tool vibration, a compensation method through the pre-experimental calibration test is proposed. The machining test on the ultra-precision lathe is performed. It is found that on the compensated machined image, cumulative errors caused by the asynchronous operation of the lathe and vibration tool are eliminated, which validates the feasibility and effectiveness of the method.

Thermodynamics-based Cognitive Demodulation for 'THz Torch' Wireless Communications Links

The low-cost ‘THz Torch’ technology, which exploits the thermal infrared spectrum (ca. 10 to 100 THz), was recently introduced to provide secure low data rate communications links across short distances. In this paper, a thermodynamics-based approach is proposed for greatly enhancing the sensitivity of detection with non-stationary thermal radiation, generated by thermal emitters that have been modulated well beyond their thermal time constants. Here, cognitive demodulation is employed and, unlike all previous demonstrators, allows truly asynchronous operation by dynamically predicting the thermal transients for the next bit to be received. The result is a five-fold increase in the reported operational figure of merit (Range × Bit Rate) for ‘THz Torch’ wireless communications links. A single-channel (2 m × 125 bps) prototype and an 8-channel frequency-division multiplexed (0.5 m × 1,000 bps) prototype are demonstrated as proof-of-principle exemplars for the enhanced method of demodulation. Measurements show superior bit error rate performance with an increase in range and bit rate, when compared with conventional threshold detection. This work represents a paradigm shift in thermal-based modulation-demodulation of digital data, and offers a practical solution for the implementation of future ubiquitous secure ‘THz Torch’ wireless communications links; as well as other applications.

Protection against the Effects of the Asynchronous Operation of Synchronous Motors Based on the Principle of Comparison of the Machine Power Factor

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">This paper deals with the possibility of using the principle of comparison of the operational power factor for evaluation of the asynchronous operation of synchronous motors. This way of definition of the asynchronous operation is possible to use for motors protection and other protective systems of drives with synchronous motors.</span>

C++20 Coroutines on Microcontrollers—What We Learned

Coroutines will be added to C++ as part of the C++20 standard. Coroutines provide native language support for asynchronous operations. This letter evaluates the C++ coroutine specification from the perspective of embedded systems developers. We find that the proposed language features are generally beneficial, but that memory management of the coroutine state needs to be improved. Our experiments on an ARM Cortex-M4 microcontroller evaluate the time and memory costs of coroutines in comparison with alternatives, and we show that context switching with coroutines is significantly faster than with thread-based real-time operating systems. Furthermore, we analyzed the impact of these language features on prototypical Internet of Things sensor software. We find that the proposed language enhancements potentially bring significant benefits to programming in C++ for embedded computers, but that the implementation imposes constraints that may prevent its widespread acceptance among the embedded development community.

Hybrid method based on particle filter and NARX for real-time flow rate estimation in multi-product pipelines

Real-time flow estimation plays a vital role in multi-product pipeline operations, and the accuracy of real-time flow estimation is affected by noise interference and instrument accuracy and cannot be performed by direct observation of flow meter. Pipeline flow models based on the first principle method are established and employed as soft sensors of pipeline real-time flow rate. However, these models are validated by the controlled experimental pipeline, which may be ineffective regarding actual pipelines with uncertain physical parameters. In this paper, a novel approach integrating data-driven and model-driven method is proposed to estimate the flow rate of petroleum products on-line. The difference between the theoretical model and actual state of a pipeline is accounted for by the friction coefficient, and on-line calibration is achieved by solving multi-objective optimisation problems with asynchronous operation data. The flow state of the pipeline is obtained in real time by the particle filter when new pressure observations with noise become available. The estimation performance of local pressure mutation points is improved by adopting the recurrent nonlinear autoregressive neural network modelling blue of the data-driven method. The effectiveness of the proposed method is evaluated blue by examining actual data of the pipeline over a period of time. The prediction results of some other model-driven and data-driven methods are also compared to blue that of the proposed method. The results blue indicate that the proposed method improves the accuracy and reliability of the product flow rate estimations even under unforeseen operation conditions.

Sun tracker sensor for attitude control of space navigation systems

We report a sun tracker sensor for attitude control of space navigation systems. The sensor exploits the concept of asynchronous operation previously devised by the authors for those devices. Asynchronous luminance sensors optimize sun trackers operation because only illuminated pixels are readout and can transmit data. This approach outperforms classic frame-based sun trackers in terms of bandwidth consumption, latency, and power consumption. The new sensor under study has been optimized for operation and interaction with other attitude control systems when it is embarked. The sensor power consumption is quite reduced. To save power, its pixels enter automatically in standby mode after gauging illumination levels. The device operates with only 0.45V. The pixel matrix has been devised to optionally be directly powered by energy harvesting systems based on photovoltaic diodes connected to a storage capacitor without a DC-DC converter.

Predictive Hybrid Powertrain Energy Management with Asynchronous Cloud Update

The optimal energy management of a hybrid powertrain has the task to provide the required traction power combining both power sources in the best way. This can be achieved well if the future drive cycle is known/precomputed. However, both speed and traction power requirement may deviate from the expected ones due to many factors, like traffic, weather etc. Against this background, it might be sensible to recompute them whenever needed to keep using the latest future information. Unfortunately, this computation is typically too slow for real time use. In this paper we propose a control structure in which the real time task is solved by a predictive controller which tracks the optimal reference from the cloud, and requests an update of the reference regularly. The update can integrate new information from V2X. This asynchronous operation allows recovering most of the performance of the perfect prediction, while removing tight constraints on the offline computation and copes better with interruptions in communications to the cloud.

Multi-Area Automatic Generation Control Scheme Considering Frequency Quality in Southwest China Grid: Challenges and Solutions

Southwest China Grid (SCG) is one of the hydropower-rich power grids around the world. SCG has recently been into asynchronous operation mode, it is expected to face challenges in low inertia and frequency stability issues caused by the hydraulic turbine governing system (HTGS), which brings profound changes to the validity and stability for the multi-area automatic generation control (AGC) power systems. This article analyzes the frequency control problems of SCG according to the operation data from asynchronous operation tests. To overcome the large overshoot and reverse regulation for external disturbances, frequency-based segment values of frequency bias for areas under TBC mode are developed considering multi-deadband effects, and a switching method of control modes for supporting large-disturbance recovery is proposed. Based on the complex and nonlinear of AGC systems, a fuzzy PD+I controller is proposed to reduce the excessively large overshoot. Furthermore, the rule for tuning D gain is established by the sign of change of area control error (ACE), and flexible I-part is applied to the control process based on the relationship between ACE and frequency. Then, we also provide filter-based control strategies with adaptive parameters to effectively coordinate hydropower and thermal power generators. The filter coefficients are computed considering various delays within AGC systems. Some case studies and actual operating conditions demonstrate the efficiency and accuracy of the proposed ideas compared with current control strategies.