Control Channel Research Articles

3D graphene-based active electrodes with large areal capacitance by modified direct ink writing method

The application of 3D printing technology in the field of energy storage is of great practical significance but still remains challenging. Recently, 3D-printed graphene-based architecture has been found to be a promising material for electrochemical energy storage devices. In this study, graphene-based conductive filaments were printed through direct ink writing method (DIW), and then dense poly-pyrrole film (PPy) was formed on the surface of the 3D frame by simple electrodeposition. And followed by post treatment three-dimensional heterogeneous graphene-based electrodes wrapped by nanocarbon cloth (3DCGs) were readily prepared. 3D-printed open porous structure provides effective aligned channels for ion transport as well as large ion accessible area for electrochemical reaction. PPy layer helps to maintain the structural integrity and obtain high capacitance retention rate. A series of 3DCGs with controllable channels were prepared by adjusting the number printing layers, infilled spacing and nozzle size. Thus, we gained an insight into the influence of structural engineering of electrode materials on electrochemical performance. The 5-layer 3DCG with filament spacing of 300 µm and filament diameter of 400 µm achieved an areal capacitance of 2265.19 mF/cm2 at a scan rate of 5 mV/s, which was significantly higher than that of non-3DCG (400.15 mF/cm2). Briefly, this study reports the integration of DIW 3D-printing and electrodeposition techniques allowing a facile way of fabricating customized 3D-electrodes with large areal capacitance.

PHONEMES, MORPHEMES, MORPHS AND ALLOMORPHS IN THE MARKOV ALPHABET OF A SET OF DATA SOURCES

For artificial languages formed by many sources of big data, in the Markov alphabet, a prescription is investigated that provides linkage between the word and the source, through the consideration of phonemes, morphemes, morphs and allomorphs in this language. The artificial language is studied in the context of solving the problem of synthesizing a methodology for classifying the risks of laundering proceeds from crime and financing terrorism in big data of organizational systems. New provisions of the theory of Markov algorithms are being developed. Methods of data decomposition using the N-scheme of the Markov algorithm, developed to replace his well-known g-scheme, are studied. A method for decomposing words into phonemes in the Markov alphabet is considered. It has been established that Markov phonemes are formed on the basis of terminal symbols of the alphabet M = litjпо1…оx /abdgckm for big data input samples and the alphabet MK = litj/abdgckm for the control channel. The method of synthesizing morphemes from Markov phonemes is studied from the positions of both the theory of algorithms and linguistics. The properties of roots and affixes of morphemes are considered from the standpoint of the theory of algorithms, in particular, in the N-scheme of the Markov algorithm. A scientific contradiction in the linguistic approach to the formation of morphemes is revealed, a way to overcome it is proposed. The results of the theoretical substantiation of the method of determining (assigning) for morphemes morphs and allomorphs within the framework of the theory of algorithms are given. New properties of Markov phonemes in the Markov alphabets AM±2 and KMK±2 not previously seen in linguistics are established. Some scientific conclusions previously obtained in linguistics are confirmed from the position of the theory of algorithms. A generalized, reference model of a morpheme has been developed, its abstract nature has been confirmed, methods for synthesizing morphs and allomorphs in a categorical representation format have been given. The statement is synthesized in the form of a Markov diagram of occurrences, its comprehensive analysis is carried out. It is concluded from the above research results that the decomposition of big data into phonemes and morphs provides the representation of statements in the form of chains of occurrences that can be recoded into a categorical presentation format, and by analyzing numbers-types and numbers of morphisms, it is possible to extract their signatures from morphs, which are allomorphs.

Leveraging Load-Aware Dynamic Pricing for Cell-Level Demand-Supply Equilibrium

Demand-supply equilibrium is a preferable state for a cell, since resources are fully utilized and users' quality-of-experience is guaranteed. In principle, a price will be determined for utilizing a base station (BS) based on its load, and users will react to the prices of available BSs. In this paper, a deep reinforcement learning (DRL) based dynamic pricing method is proposed for the fully-decoupled RAN (FD-RAN). The proposed method exploits the separate control channel provided by the control BS, and can reach overall equilibrium for data BSs, with multi-link cooperative transmission inherently supported. We elaborately design the state, action and reward of DRL, and utilize several techniques. Simulations are conducted to demonstrate the stability, performance, and generalization of our proposed method.

Flow resistance of flexible vegetation in real‐scale drainage channels

AbstractThe definition of simple and accurate methods to estimate flow resistance in vegetated channels is still a challenging issue in soil bioengineering practices and programming riparian vegetation management to control channel conveyance capacity, sediment deposition, and flooding propensity. In this paper, measurements collected by Errico et al. (2018, 2019) in drainage channels colonized by common reed (Phragmites australis) were used to study the effect of flexible vegetation and its management in flow resistance estimate. At first, a theoretical flow resistance equation, obtained applying dimensional analysis and incomplete self‐similarity condition for the velocity distribution of an open channel flow, was briefly summarized. Then, this flow resistance equation was calibrated and tested by open‐field hydraulic experiments carried out by Errico et al. (2018, 2019) at the real scale of existing vegetated drainage channels. In particular, the Γ function of the power velocity profile was empirically related to the slope energy and the flow Froude number by using the available measurements. Taking into account the hydrological regime of the flow in the investigated channels, the original data set was divided into two sub‐data sets (calibrating and testing data set) exploring the same range of measured discharges. The calibration and testing of the flow resistance equation were carried out without distinguishing measurements corresponding to different vegetation conditions (full‐vegetated, half‐vegetated, non‐vegetated, central vegetation cut, extensive vegetation cut). The analysis demonstrated that the theoretical flow resistance equation allows an accurate estimate of the Darcy‐Weisbach friction factor which is characterized by errors that are always less than 10% and less than or equal to 5% for 90.9% of the investigated cases. The finding of this study also allowed to evaluate the effects of different vegetation management scenarios on flow resistance.

A Space-ground Joint Target Detection System Based on Artificial Intelligence

Due to the low efficiency and poor adaptability of template matching in target detection, this paper represents a space-ground joint detection system based on artificial intelligence, which takes advantage of the high computation power of the ground system to train neural networks and utilize the measurement and control channel to update and synchronize the on-orbit system. Based on YOLOv5, an oriented bounding box is used for labeling and training, the angle is considered as a class and the loss for the angle is added to the code. After training the network with the ground system, the weight will be sent to the satellite. This process would repeat once there are new training data that worse the update. Based on the new routine for target detection, the accuracy and robustness are significantly higher than before.

Distributed finite-time adaptive fault-tolerant formation–containment control for USVs with dynamic event-triggered mechanism

This paper presents a distributed finite-time adaptive fault-tolerant formation–containment control strategy for unmanned surface vessels (USVs) with dynamic event-triggered mechanism in the presence of total disturbances and actuator failures. A two-layer framework consisting of reference trajectory estimators and trajectory tracking controllers is proposed. In the first layer, two sets of distributed finite-time reference trajectory estimators (DFRTE) are developed using graph theory to estimate trajectory information (position and velocity) for leaders and followers. In the second layer, the fast integral terminal sliding mode control (FITSMC) is introduced to ensure that the leaders form the desired formation, and the followers converge to the convex hull formed by the leader, the robust exact differentiators (RED)-based disturbance observers are constructed to estimate the total disturbances composed of model uncertainties and external disturbances, and adaptive laws are designed to compensate actuator failures. To reduce communication resource consumption between the actuator and the controller channels, dynamic event-triggered mechanisms (DETMs) are designed to update the actuators only when the triggering conditions are satisfied. The Lyapunov analysis method is employed to prove the finite-time stability of the closed-loop system. Simulation results demonstrate the effectiveness of the proposed control scheme.

Integrated vehicle control using adaptive control allocation

SummaryThe focus of this paper is an integrated, fault‐tolerant vehicle control algorithm for the overall stability of ground vehicles. The proposed scheme comprises a high‐level controller that creates a virtual control input and a low‐level adaptive control allocator that distributes the virtual control effort among redundant actuators. The proposed control framework distinguishes itself from earlier results in the literature by its ability to blend active suspension, steering and traction control channels, in the presence of uncertainties and time‐varying dynamics, without the need for fault identification. The control structure is validated in the simulation environment using a fourteen‐degree‐of‐freedom non‐linear vehicle model. The integrated controller is compared to the case of a conventional control approach where each control problem is solved separately. Our results show that, compared to the conventional approach, the proposed method ensures that the vehicle follows driver inputs with up to % higher longitudinal maneuver velocity, despite the presence of actuator failures and slippery road conditions. Furthermore, to demonstrate the benefit of integrating active suspension control to the overall control scheme, we replaced the suspension control of the proposed approach with an independent suspension control system for comparison purposes. We then showed that the integrated case provided % lower roll angle deviation, and % lower pitch angle deviation, in the presence of actuator effectiveness loss and adverse road conditions.

Time-optimal maneuvers of a spacecraft between two arbitrary states in proximity of a circular reference orbit

The problem is considered to find the time-optimal control that transfers a fourth-order system that consists of a double integrator and a harmonic oscillator, coupled by one control channel, between two arbitrary states. That fourth-order system is equivalent to the Hill-Clohessy-Wiltshire model of the relative dynamics of an orbiting spacecraft in proximity of a second spacecraft on a circular reference orbit, subjected to a thrust parallel to the orbital velocity vector and having time-continuous amplitude. A new method is here introduced to determine the time-optimal control problem stated above. This method combines two previously discovered optimal control synthesis methods: the method by Romano and Curti (2020), that enables to find (analytically, in some case) the optimal control transferring a general Linear Time Invariant Normal system between two arbitrary states; and, the method by Belousova and Zarkh (1996), that enables to find the optimal control transferring a fourth-order system consisting of a double integrator and a harmonic oscillator, coupled by one control channel, from an arbitrary initial state to the origin of the state space, if the optimal control is a priori known, that transfers the same system from a reference state to the origin. The here proposed combined method utilizes two phases. During the first phase, a number of reference minimum-time controls are obtained that transfer the system from specific reference states to the state space origin; this is achieved by exploiting Pontryagin’s principle together with back-propagation from the origin of the state space. During the second phase, a search is run along a particular curve in the state space (named extremal search path) that depends on the boundary states of the problem at hand. In particular, a minimum-time control problem is iteratively solved to find the optimal control history that steers the system from a state on that curve to the origin, by exploiting Belousova and Zarkh method, until a particular state is found which satisfies an equivalency condition that, as demonstrated by Romano and Curti, guarantees that the optimal control history pertaining to the problem of transferring the system from that state to the origin is the same optimal control history that transfers the system between the arbitrarily set initial and final states. The new results, substantiated by numerical experiments, have both a theoretical and a practical value, as they could be applied for the optimal guidance of spacecraft performing autonomous proximity maneuvers.

PARAMETERS OF FLOWS OF GRAIN MATERIALS

Solving the issue related to the study of flows of loose materials is due to the development of modern sensors of flow parameters of loose materials. In particular, it can be about flow sensors. This type of sensors is one of the most attractive for use in the control and regulation channels of modern automated production control systems in the agricultural and food industry. The issues considered in this article relate to the mechanics of flows of loose materials. The field of mechanics, which studies the static and dynamic aspects of loose materials, is one of the basic branches of mechanics in general. The main focus is on free gravity flow. Grain material is considered as loose material. Taking into account the peculiarities of loose material and the specifics of various industries, the problem of creating flow parameter sensors was and will be relevant. The definition of the object and process for which the sensor is being developed, namely the study of flows of loose materials, is also relevant. The article considered how loose material behaves during free fall from silos in an airless space and also in an airy one. The consumption of bulk materials from the bottom opening of the silo, in most cases, is not stable and leads to the formation of a variable flow of bulk material. After the grain leaves the silos opening, a gravitational flow is formed, consisting of dispersed grains and an air flow. The formed flow of bulk material can be considered as an information factor for determining the consumption of bulk material and a factor in creating effective sensors for automated control systems of technological processes. Formulas for calculating the flow rate of loose material in a gravity flow and the flow volumes at different states were also given in the article.

ELECTRODYNAMICS OF HIGH-PRECISION ITERATIVE FEED ELECTRIC DRIVE OF MACHINING CENTER WITH INERTIAL LOAD

The kinematical diagram and refined mathematical model of steady motion in machining mode of high-precision itera-tive multichannel differential-geared electric feed drive of machining center with substantially inertial working tool are presented. The structural-algorithmic diagram of a three-channel control system of an electric drive, represented by various options for implementing an iterative algorithm for the interaction of control channels is given. Concretization of computer model is completed to simulation of movements of iterative two- and three-channel electric drive with sub-ordinated adjustment of control channels, destined for displacement of working tool feed mechanism in face milling mode. Comparative assessment in time and frequency areas of quality indicators to improve the feed accuracy using the proposed multichannel electromechanical system is completed. Comparison is made with similar on purpose, but dif-ferent on speed of operation, modern single-channel gearless feed electric drives, which traditionally used on heavy metal cutting machines and machining centers. It is shown that in compensated two- and three-channel electric drive compared to even broadband single-channel asynchronous feed electric drive with frequency-current vector control a significant increase not only in speed of operation, but also in the dynamic accuracy of feed control practically in the entire range of working tool movements can be achieved. It is determined that iterative three-channel electric drive potentially provides a level of quality control of the working tool, unattainable not only in the corresponding traditional single-channel electric feed drives of various types, but in a similar construction two-channel differential-reducer feed electric drive. References 10, figures 5, table 1.

Environment assisted cyclic fatigue crack growth testing of polymer/inorganic laminates under strain energy release rate control

We focus on the development and implementation of an environmental (hot-dry or hot-humid air) testing methodology for adhesively bonded laminates under maximum strain energy release rate (SERR) control. The technique overcomes disadvantages of displacement- and force-controlled fatigue crack growth testing. Fracture mechanics based double cantilever beam (DCB) specimens comprising steel/epoxy- and glass/polyolefin-laminates were investigated using an electrodynamic test system with automated software control. Crack length was evaluated in-situ with a compliance calibration approach. User-defined SERR values were set with a control channel. The SERR was changed every 200,000 cycles or after exceeding crack length milestones. For steel/epoxy-laminates with an adhesive thickness of approximately 5 µm a good agreement of crack growth rates was obtained by displacement and SERR control. Moreover, the negative effect of humidity (50% vs. 10% rh) on the fatigue delamination resistance was confirmed at 60 °C. In contrast, significant deviations of crack growth rates under displacement and SERR control were deduced for glass/polyolefin-laminates with an adhesive thickness of 250 µm under hot-dry (60 °C, 1%rh) conditions. The deviations were attributed to differences in the damage zone size for the soft polymeric adhesive. Under hot-humid (60 °C, 80%rh) conditions a reasonable agreement of displacement and SERR controlled test data was observed and attributed to a less pronounced damage zone and a failure of the glass/polyolefin-laminates in an interfacial manner.

Modeling and State Estimation for Supervisory Control of Networked Timed Discrete-Event Systems and Their Application in Supervisor Synthesis

This paper considers modeling and state estimation of timed discrete-event systems (TDESs) with communication delays and losses. In the previous framework, the specified closed-loop system language may contain physically impossible strings, i.e., strings never occur in practice. To exclude these physically impossible strings, this paper presents a new modeling framework for supervisory control of networked TDESs. Specifically, we first analyze how to model and update the observation channel and the control channel under communication delays and losses. We then construct an automaton that explicitly describes the interaction process between the plant and the supervisor over the observation channel and the control channel so that the language of the closed-loop system can be specified. Compared with the existing work, the proposed framework can model the “dynamics” of the closed-loop system more accurately. Under the proposed framework, we further estimate states of the closed-loop system under communication delays and losses. The state estimation is implemented on-the-fly and bases on only the information of observations and controls in history. As an application of the proposed modeling and state estimation approaches, we finally extend the existing approaches to find all the admissible and safe supervisors of networked TDESs.

FPGA based hardware platform for trapped-ion-based multi-level quantum systems

We report a design and implementation of a field-programmable-gate-arrays (FPGA) based hardware platform, which is used to realize control and signal readout of trapped-ion-based multi-level quantum systems. This platform integrates a four-channel 2.8 Gsps@14 bits arbitrary waveform generator, a 16-channel 1 Gsps@14 bits direct-digital-synthesis-based radio-frequency generator, a 16-channel 8 ns resolution pulse generator, a 10-channel 16 bits digital-to-analog-converter module, and a 2-channel proportion integration differentiation controller. The hardware platform can be applied in the trapped-ion-based multi-level quantum systems, enabling quantum control of multi-level quantum system and high-dimensional quantum simulation. The platform is scalable and more channels for control and signal readout can be implemented by utilizing more parallel duplications of the hardware. The hardware platform also has a bright future to be applied in scaled trapped-ion-based quantum systems.

Blockchain Enhanced Stock Trading Application

Stock exchange works and functions in a very inconvenient and hectic way because of post-trade processes which are cost-inefficient, time-consuming and can be prone to numerous risks. This motivates us to experiment with new technologies like blockchain which has immense potential to change the process of post-trading. In this paper, we propose an implementation of a stock trading application built on Hyperledger Fabric, a hybrid blockchain architecture. The network for our application is built using Hyperledger Composer framework. All the transactions done on the client app are recorded and appended to the Fabric with the help of a REST server. Fabric contains various security measures such as Access Control Lists and channels to ensure only authorized users to have access to those transactions. Before the users can perform any transactions, they will be given an identity card containing the certificates and credentials required to access the blockchain network. With our approach, we aim to significantly cut the transaction costs of exchanging shares and bring about a seamlessly efficient platform where participants would confirm trades via a distributed ledger

Multi-Agent System for Rogue Drone Interception

A multitude of applications based on unmanned aircraft vehicles (UAVs), in conjunction with the UAVs' diminishing costs and increasing capabilities, present a major threat to public safety as well as critical infrastructure security, leading to the need for versatile and robust counter-drone solutions. This work presents a novel multi-agent jamming system (MUAV-JS), where a group of cooperative autonomous agents employ various algorithms (detection, tracking, jamming, and self-localization) to counter unauthorized drone operations. The proposed system employs a joint wireless jamming and cooperative positioning framework to best track and intercept the moving rogue drone, utilizing a relative positioning system based on signals of opportunity in conjunction with inertial and vision measurements. Software-defined radio technology is incorporated on the pursuer agent to achieve rogue drone GPS disruption, while at the same time the autonomous agents cooperate to compute the location estimate of the pursuer agent. In the presence of jamming, to improve the wireless communication performance of the autonomous agents, a cellular communication architecture is also used as an additional channel for control and information exchange. For evaluation purposes, a prototype multi-agent system is designed, implemented, and tested in a real-world environment to demonstrate its enhanced localization and jamming performance, when compared to single-agent approaches.

METHODOLOGY FOR CLASSIFYING MONEY LAUNDERING RISKS TYPOLOGIES

The method of classifying the typologies of money laundering and terrorist financing risks in big data from a variety of data sources of organizational systems is investigated. The main provisions of this technique are theoretically substantiated, reference models and calculation formulas are given. An algebraic approach for the synthesis of the method is proposed, a theoretical justification of the feasibility of its use is given. The algebraic approach to the synthesis of the methodology is implemented on the basis of category theory and the theory of algorithms, in particular the theory of Markov algorithms, which is considered outside of normal algorithms. The N-scheme of the Markov algorithm is considered, which was developed to replace its well-known g-scheme and provides processing of words in natural, artificial and combined languages, which can be represented in an ordered and extended Markov alphabet A±2, which takes into account many sources of big data. Methods for inputting incomplete, heterogeneous (heterogeneous) and non-representative input data samples are given. A method is proposed for converting input data samples into cycles of the Big Data Transfer Protocol. A reference model of the legal economic activity of the organizational system has been synthesized. This reference model is subjected to analysis and signs of illegal economic activity of mutually interacting organizational systems are highlighted. A reference model of the system for classifying the risks of laundering proceeds from crime and financing of terrorism has been developed. To combat money laundering, the N-scheme of the Markov algorithm for one data source and the Markov system, consisting of such schemes, for a variety of big data sources are theoretically substantiated. It is concluded that the synthesized Markov system provides a decomposition of words and their morphisms, contains a common data input control channel, and provides a classification of money laundering risks.

Application of Microcontroller-Based Multipath Servos in Industrial Robot Control Systems

In recent years, nanotechnology has continued to develop, especially the use of nanomaterials in various fields. Microcontroller is the most typical embedded system at this stage. With the development of science and technology, microcontroller has been widely used in people’s production life. A simple and practical multiservo controller can be built by using microcontroller and LED control chip PCA9685, which can realize at least 16 channels of servo control. In this paper, the control program of multichannel actuator is designed in detail, and the speed regulation of multichannel actuator is studied, which is applied to the industrial robot system driven by actuator. Nanomaterials, as new materials with various unique properties, have great application prospects, and this paper investigates the extension of nanomaterials in the field of robotic systems.

On-Chip Liquid Manipulation via a Flexible Dual-Layered Channel Possessing Hydrophilic/Hydrophobic Dichotomy

The hydrophilic/hydrophobic cooperative interface provides a smart platform to control liquid distribution and delivery. Through the fusion of flexibility and complex structure, we present a manipulable, open, and dual-layered liquid channel (MODLC) for on-demand mechanical control of fluid delivery. Driven by anisotropic Laplace pressure, the mechano-controllable asymmetric channel of MODLC can propel the directional slipping of liquid located between the paired tracks. Upon a single press, the longest transport distance can reach 10 cm with an average speed of ∼3 cm/s. The liquid on the MODLC can be immediately manipulated by pressing or dragging processes, and versatile liquid-manipulating processes on hierarchical MODLC chips have been achieved, including remote droplet magneto-control, continuous liquid distributor, and gas-producing chip. The flexible hydrophilic/hydrophobic interface and its assembly can extend the function and applications of the wettability-patterned interface, which should update our understanding of complex systems for sophisticated liquid transport.

Research of an Adjustable DC Electric Drive in the Generator Braking Mode

The article is devoted to the study of an adjustable DC electric drive with a compensated electric motor of independent excitation of the 4PF series in the mode of controlled generator braking. The linearization of the model is performed, a linear transfer function is obtained via the control channel. The dependences of the oscillation index and the time constant in the duty cycle function of the pulse converter in the braking mode are determined, the operating range of the braking mode is determined. As a result of theoretical studies, the operating range of the change in the duty cycle of the pulse converter in the armature circuit of the electric motor has been determined. The dependences of the correction coefficients for the transfer function of the linear part of the electric drive replacement circuit in the controlled dynamic braking mode are obtained, which allow taking into account the nonlinearity of the pulse converter

Nanobridge SQUIDs as Multilevel Memory Elements

With the development of alternative computing schemes working at cryogenic temperatures, superconducting memory elements have gained interest. In this context, superconducting quantum interference devices (SQUIDs) are promising candidates, as they may trap different discrete amounts of magnetic flux. We demonstrate that a field-assisted writing scheme allows such a device to operate as a multilevel memory by the readout of eight distinct vorticity states at zero magnetic field. We present an alternative mechanism based on single phase slips, which allows the vorticity state to be switched while preserving superconductivity. This mechanism provides a possibly deterministic channel for flux control in SQUID-based memories, under the condition that the field-dependent energy of different vorticity states are nearby.