Robust Control Mechanism Research Articles

CREATE SOLUTIONS FOR VERSIONING AND MANAGING DATASETS USED IN AI AND ML.

It is also essential to correctly version and manage datasets to make them easily recognizable, traceable, and sharable throughout the various stages of AI & ML model development. Notably, there are many solutions to dataset versioning and management, with the best one touching on existing machine learning pipelines, highlighted by tools like DVC and MLflow, in this paper. To achieve this, the study provides simulation reports on using these tools in the current dynamic data environments, including healthcare, finance, and e-commerce, requiring robust version control mechanisms to counter quickly evolving data. Potential issues such as scale, data accuracy, and compatibility with present system adoptions are discerned with suggested solutions such as cloud-based management, checks and balances on data integrity, and ease of integration. The use of visuals shows how data lineage visualization helps in understanding the data flow for better implementation of measures and how different versioning tools compare in performance. The conclusions drawn from the study pertain to the fact that the implementation of structured data versioning strategies contributes to the enhancement of model quality and efficiency in addition to enhancing interaction between data scientists and engineers. This research finds that proper methods of developing and applying data versioning and data management practices are critical for effectively implementing AI and ML models in complex ecosystems that make decisions based on the most contemporary data. Future work will investigate the applicability of these tools as the number of data points to process increases, as well as the variability of those data points.

A concise funnel robust model-free control mechanism for hypersonic space vehicles based on error driving

Based on non-affine models of hypersonic space vehicles, the tracking control problem of hypersonic vehicles is studied and analyzed in this article using funnel robust model-free control mechanism considering parametric uncertainty and external disturbances. First, the control system is decomposed into altitude subsystem and velocity subsystem. For altitude subsystem, we propose a concise funnel robust model-free control mechanism based on error driving, and a novel model transformation approach is applied to the controller design. The new model-free controller only contains a Hurwitz stable term and a filtering term, and does not need precise motion model and too much calculation, so it can improve the calculation speed of the system. For velocity subsystem, only a concise proportional-integral controller is needed to meet the tracking requirements. Moreover, the devised controller is capable of guaranteeing funnel performance on the altitude and velocity tracking errors. Finally, numerical simulation results are presented to verify the efficiency of the design.

A secure blockchain-oriented data delivery and collection scheme for 5G-enabled IoD environment

−There are innumerable ways the Internet of Drones (IoD) technology can impact our society. With the deployment of an airborne network, the IoD can support real-time low-cost delivery of services ranging from military surveillance to a myriad of civilian applications. Nevertheless, the drones employ insecure wireless communication channels to communicate with other entities in the system, inhibiting its induction in sensitive installations if insecure or inefficient Authenticated Key Agreement (AKA) schemes are employed. The blockchain, an open distributed ledger-based technology, is increasingly being adopted to address the security concern as discussed. Recently, Bera et al. presented an efficient blockchain-enabled AKA scheme for data management among various entities in IoD network. However, their scheme does not support anonymity and untraceability for the drones; also, it does not provide resistance to Ground station server impersonation attack, while the protocol has a few redundancies. Later, we proposed an enhanced blockchain-enabled AKA scheme BOD5-IOD to authenticate drones in the system. The BOD5-IOD, other than supporting a robust access control mechanism between drones and GSS, also ensures safe transactions among all entities in the IoD environment. The formal analysis and performance evaluation endorse that our scheme supports security requirements with computational and communication efficiency of 34.4% and 23.3%, respectively.

An appraisal of local content requirements in the Iranian oil and gas industry

Leading countries in the petroleum industry strive to maximize their benefits from exploring, developing, and producing oil and gas by setting out various policies and requirements such as local content. Iran, like many other oil and gas-producing countries, has legal and contractual local content requirements. However, the lack of transparent and integrated regulatory and contractual frameworks and fixed threshold applied for all types and life cycle of fields and operations are considered as concerns and challenges of local content policies in Iran. Determining metrics to measure local content is another issue that is not clarified as required in legal and contractual requirements. Establishing a constructive local content policy in Iran requires the active integration of factors such as actual improvements in local service or product and labor productivity. Transparent legislative and regulatory frameworks, robust performance planning, monitoring, and control mechanisms, along with precise metrics for measurement of local content, are indispensable prerequisites for realizing local content policies. The characteristics of operations and the need to implement new technologies must also be considered to design an appropriate policy. Moreover, the development of integrated approaches and congruent laws and regulations could facilitate and accelerate the achievement of development goals.

Organization Features and Profitability: Implications for a Sample of Emerging Countries

A huge number of prior works has tested the link between control mechanisms and organization profitability. Several methods are used by such works to enhance the notion that there is an inconsistent result in the link between the board feature and organization profitability. However, there is unpredictability of this link shown by the prior works. Thus, the current work aims at testing the board features as internal control mechanisms represented by the size of both organization and the board of directors in their impact on organization profitability in the non-financial companies in Jordan, which was selected from a sample of Emerging Countries. Data were collected from the annual reports for 65 organizations for the year 2019 from the website of ASE via utilizing a cross-sectional analysis study. After testing the hypothesis of the current work, the findings revealed that the size of the board of director has a significant impact on the organization profitability of nonfinancial companies in Jordan. However, this work showed that organization size has an insignificant impact on organization profitability. The current work might help policymakers in Emerging Countries in general, and Jordanian non-financial sector in particular, deliberate policies related to using robust control mechanisms to enhance directors' commitment toward utilizing internal control mechanisms for the ultimate aim in promoting organization profitability

Comprehensive Modelling of Renewable Energy Based Microgrid for System Level Control Studies

Renewable energy will constitute the backbone of the future sustainable energy systems by forming onsite microgrids. This reduces the utility grid burden and outages. Besides, microgrids can address the issues of greenhouse gasses, global warming, fossil fuel evaporations, slow start-up/shutdown times, etc. However, their dependency on geography/climatic conditions lead to the exhibition of intermittent output characteristics. Moreover, a majority of microgrids must be interfaced with the utility grid through power electronic converters, which are static and do not possess any kinetic energy. Due to this nature, these systems are highly sensitive to events, and thereby, creating issues with fast detection of islanding during abnormalities. Furthermore, for superior power quality, stability, energy yield, reliability, and protection, they must be properly coordinated with the utility grid or neighbour microgrids via robust control mechanisms. To study all these factors, lead to a better system, it is desired to have a perfect model of the system. Many literary works have developed microgrid models by focusing on a very particular aspect or component of it with respect to their area of research. But, comprehensive models are much required for many different studies as mentioned above. Further, the comprehensive model helps in detailed system-level studies. So, with this intension, this paper proposes the development of comprehensive model of the microgrid which involves all its key characteristics/elements. Further, system-level control study is presented to persuade the importance of this proposed model. From results, the WJC method is recommended as the best method to design microgrid’s controller.

Maneuvering Control of Hexrotor UAV Equipped With a Cable-Driven Gripper

This study proposes a control method for the maneuvering control of an aircraft system equipped with a cable-driven gripper. The UAV chosen for the study is a hex-rotor due to its durability and redundancy. The reason for opting for the cable-driven robotic arm is because of its extended range as compared to a fixed robotic arm. The aircraft system also contains an Ultra HD camera which helps to locate and identify the target object. Since the UAV grabs the object, the extra weight introduces some instability in the system. To help stabilize the dynamic behavior of the gripper and reduce external wind disturbance, we need an effective and robust control mechanism. To tackle these issues, this paper designs a control method based on the Model Reference Adaptive Control with an integrator (MRACI) with reference dynamics like an observer. On one hand, first, verify the performance of the proposed controller using computer-based simulations. On the other hand, it also applies the designed method to hardware-based results. The simulations and experimental results show that the designed controller works as intended and the errors are within an acceptable range.

Voltage stability augmentation of hybrid power system using robust reactive power control strategy of PV plant

The involvement of large-scale grid-tied photovoltaic (PV) systems is growing speedily, and enormous effort is given to design the robust control mechanism of PV systems to augment the performance of the PV system in both transient and steady-state states. The terminal voltage may fluctuate at steady-state conditions due to the alternating nature of solar irradiance and affect the LVRT aptitude at the transient period. Therefore, in this paper, a cascaded grid-side AC-DC inverter control strategy is developed by modifying the inverter input signal to control the terminal voltage. The proposed dead-band-based inverter controller maintains the terminal voltage at rated value during steady-state and augments LVRT aptitude at transient conditions by injecting an efficient quantity of reactive power. The overall scenario, including PV system, conventional power plant, and load, has been designed and examined using the “PSCAD/EMTDC” platform. The traditional control system is taken into comparison with the proposed control system to verify the effectiveness of this innovative control technique.

State defense during the first wave of the COVID-19 pandemic: the cases of the Russian Federation and Hungary

The first cases of the COVID-19 epidemic, registered in January 2020, and the first wave that followed, hit the world unprepared. The only means available to the various states were the various restrictive measures expected to alleviate the epidemic. In this article, the restrictive legal measures of two European countries, the EU member state Hungary and non-the EU member state Russia, are compared from the rule of law and law enforcement. The special legal order introduced in both countries and the measures taken within its framework have resulted in a significant restriction of fundamental rights. The epidemiological data of the two countries differed significantly, yet they tried very hard to defend themselves with similar means. There are two primary differences. Russia has used more robust control mechanisms to enforce similar measures, presumably due to the more difficult epidemic situation. The other difference is that Russia’s restrictions against Hungary did not cover freedom of expression and freedom of expression. As both the state of emergency and, with it, the more severe restrictions were lifted during the period under review. Following the reduction of the epidemic situation, both states remained within the legal framework.

Exorcising the “Ghosts” from the Government Payroll in Developing Countries in the Wake of the Covid-19 Pandemic: Ghana’s Empirical Example

The salary payment of government workers constitute a significant percentage of total government expenditure in developing economies, simply because the government remains the largest or biggest employer. The Government Payroll system, therefore, requires a robust control mechanism to detect and prevent the occurrence of “payroll fraud”, as the irregularity denies the state of huge sums of monies going down the drain and into private pockets, and which could have otherwise been channelled into some critical sectors of the economy; and to minimise the excessive borrowing by government to fill the gap. The several efforts and reforms by the Controller and Accountant-General’s Department (CAGD) and the Ghana Audit Service (GAS) in particular; and the Ministry of Finance (MoF) in general, to clean the Government Payroll of these “payroll frauds” consistently over the years have not yielded the desired results. The various studies conducted on “payroll fraud” in Ghana did not address themselves to the introduction of the “Electronic-Salary Payment Voucher (E-SPV) system since 2014, which was hailed by many as the final panacea to the “annual ritual of ghost workers on the government payroll”. To fill the gap, we conducted this empirical cross-sectional research on “payroll fraud” based on the “fraud triangle theory” and the “graft estimation model”. We employed non probability purposive, but convenient, sampling methodology by means of structured questionnaires and face-to-face interviews to arrive at our conclusion. Our major finding was that “payroll fraud” can never be eliminated (but only minimised), and must therefore be treated and necessarily managed to the barest minimum (between 1% and 5%), just as normal “bad debts” in Financial Statements. Policy makers will have to revisit the issues about “Ghost Workers”, in the midst of the novel and dreaded, and disastrous Convid-19 pandemic.

Robust Adaptive Synchronization of a Class of Uncertain Chaotic Systems with Unknown Time-Delay

In this paper, a robust adaptive control strategy is proposed to synchronize a class of uncertain chaotic systems with unknown time delays. Using Lyapunov theory and Lipschitz conditions in chaotic systems, the necessary adaptation rules for estimating uncertain parameters and unknown time delays are determined. Based on the proposed adaptation rules, an adaptive controller is recommended for the robust synchronization of the aforementioned uncertain systems that prove the robust stability of the proposed control mechanism utilizing the Lyapunov theorem. Finally, to evaluate the proposed robust and adaptive control mechanism, the synchronization of two Jerk chaotic systems with finite non-linear uncertainty and external disturbances as well as unknown fixed and variable time delays are simulated. The simulation results confirm the ability of the proposed control mechanism in robust synchronization of the uncertain chaotic systems as well as to estimate uncertain and unknown parameters.

MagNI: A Magnetoelectrically Powered and Controlled Wireless Neurostimulating Implant.

This paper presents the first wireless and programmable neural stimulator leveraging magnetoelectric (ME) effects for power and data transfer. Thanks to low tissue absorption, low misalignment sensitivity and high power transfer efficiency, the ME effect enables safe delivery of high power levels (a few milliwatts) at low resonant frequencies ( ∼250kHz) to mm-sized implants deep inside the body (30-mm depth). The presented MagNI (Magnetoelectric Neural Implant) consists of a 1.5-mm 2 180-nm CMOS chip, an in-house built 4×2mm ME film, an energy storage capacitor, and on-board electrodes on a flexible polyimide substrate with a total volume of 8.2mm 3. The chip with a power consumption of 23.7 μW includes robust system control and data recovery mechanisms under source amplitude variations (1-V variation tolerance). The system delivers fully-programmable bi-phasic current-controlled stimulation with patterns covering 0.05-to-1.5-mA amplitude, 64-to-512- μs pulse width, and 0-to-200-Hz repetition frequency for neurostimulation.

Feedback Linearization Based Robust Control for Linear Permanent Magnet Synchronous Motors

In this study, we designed a feedback linearization control strategy for linear permanent magnet synchronous motors (LPMSMs) as well as a robust control mechanism. First, the highly nonlinear system was transformed into an exact linear system by the feedback linearization technique. Then, we designed a robust controller to mitigate the impact of system parameter disturbances on system performance. This novel robust feedback controller can be applied to electromagnetic force, speed and position control loops in linear motors, correct the errors created by uncertainty factors in the entire system in real time, and set the system’s settling time based on the application environment of the plant. Finally, we performed simulations and experiments using a PC-based motor control system, which demonstrated that the proposed robust feedback controller can achieve good performance in the controlled system with robust anti-disturbance control.

On Designing a Lesser Obtrusive Authentication Protocol to Prevent Machine-Learning-Based Threats in Internet of Things

In the era of the Internet of Things (IoT), people access many applications through smartphones for controlling smart devices. Therefore, such a centralized node must follow a robust access control mechanism so that an intruder cannot control the connected devices. Recent reports suggest that password can be used as an authentication factor for accessing the smart setups. However, this static information can be compromised under the light of different machine learning (ML)-empowered attack mechanisms. Alarmingly, different sensors used in the IoT setup can also expose this static information to the adversaries. Password-based authentication that uses a challenge–response strategy is an effective solution for handling such threat scenarios. In this article, at first, we show that no existing usable challenge–response protocol is safe to be used in the public area network. Following this, we propose a challenge–response protocol that is more secure to use in the public domain. By using eight classifiers, we show that a learning-based threat specific to our protocol has a marginal impact on the method’s security standard. The discussion in this article also suggests that the proposed protocol has usability and security advantages compared to the existing state of the art (e.g., reduces the number of interactions between the user and verifier by a factor of 0.5).

3D On-Demand Flying Mobile Communication for Millimeter-Wave Heterogeneous Networks

Millimeter wave (mmWave) technology achieving multi-gigabits speed plays a significant role in beyond 5G and the next 6G wireless communication networks thanks to its huge spectrum utilization and beam-based directional transmissions. To tackle temporary ultra-high data demands of hotspot areas, three-dimensional (3D) heterogeneous network (HetNet) is designed with the integration of mmWave unmanned aerial vehicles (UAV) to provide resilient instantaneous control and data transmissions. However, some critical beam-related issues for mmWave implementation of UAVs/drones are addressed including robust initial beam alignment, mobility-aware beam tracking and beam refinement. In this research, we aim at developing robust and efficient beam control mechanisms by implementing a prototype of 3D flying heterogeneous communications. The backhaul connections operate at mmWave frequency between airship and UAV/drone, while fronthaul links adopt lower frequency bands such as Wi-Fi for multiuser data transmissions. We evaluate system performances for our proposed beam control schemes and provide a real-time prototype of 3D on-demand flying mobile communication for mmWave HetNets.

Robust Hierarchical Control Mechanism for Aggregated Thermostatically Controlled Loads

Thermostatically controlled loads (TCLs) are good candidates for direct load control (DLC). They can be aggregated to join the electricity market through a centralized management performed by virtual power plant (VPP). However, there are two main concerns that arise when TCLs participate in DLC. The first is related to the dispatchability of VPP against normal energy demand of individual TCLs in uncertain time-variant environments. The second refers to the tremendous increase of communication and computational requirements needed to perform DLC on a large population of TCLs. This paper introduces aggregators between the DLC controller and TCLs with a novel robust control mechanism to reconcile these concerns. The control mechanism is implemented with two layers: the upper layer suppresses the control payback effect with a quadratic optimization model, and the lower layer addresses the power trajectory tracking with a novel payback tracking error model (PTEM). The control method needs minimum sensing infrastructure since it requires power data only at the aggregation level. Our simulations resulted in a robust reference power tracking by the aggregator with a percentage root mean squared error between 3.33% – 5.69% under uncertain time-variant environments. The continuous responsiveness indicates that the aggregators manage to convert the aggregated TCLs into “manageable resources” that ensure the dispatchability of VPP.

Six weeks into the 2019 coronavirus disease outbreak: it is time to consider strategies to impede the emergence of new zoonotic infections.

Six weeks into the 2019 coronavirus disease outbreak: it is time to consider strategies to impede the emergence of new zoonotic infections.

Observer based adaptive robust Feedback-linearization control for VVER-1000 nuclear reactors with bounded axial power distribution based on the validated multipoint kinetics reactor model

In nuclear reactor, spatial oscillations in neutron flux distribution resulting from xenon reactivity feedback are a matter of concern. If the oscillations in power distribution are not controlled, power density and rate of change of power at some locations in the reactor core may exceed their respective limits causing the nuclear power plant instability. Therefore, during the design stages of any Pressurized Water Nuclear Reactor (P.W.R), it is necessary to identify the existence of xenon oscillation and to design suitable control strategy for regulating the spatial power distribution. In each nuclear power plant, Load-following control is one of the most important techniques for nuclear reactor regulation. A novel nonlinear controller called observer-based adaptive robust feedback-linearization controller for VVER-1000 nuclear reactors is presented in this paper. This novel control strategy is then applied to the Axial power distribution control during load following operation in the VVER-1000 nuclear reactors.The reactor core is simulated based on the validated four nodes kinetics reactor model and three groups of delayed neutron precursor’s concentration based on the Skinner-Cohen model. Considering the limitations of the xenon concentrations and delayed neutrons precursor’s densities physical measurement, an adaptive sliding mode observer is designed to estimate their values and finally adaptive robust feedback-linearization based on the adaptive sliding mode observer and nodal kinetics reactor model is presented to AO control during load following operation for nuclear reactors. The stability analysis is given by means Lyapunov approach, thus the designed control system is guaranteed to be stable within a large range.Simulation results show that robust control and state estimation with adaptive robust feedback-linearization and adaptive Sliding mode methodologies can be achieved in nuclear plant systems with diverse applications including control and estimation in the presence of model uncertainties and external disturbances. One significant finding to emerge from this paper is that the Observer based Adaptive robust feedback-linearization control method provides a robust, high-performance and automatic control mechanism at all the power ranges of operation for P.W.R control system.

Neural Network Integrated Adaptive Backstepping Control of DC-DC Boost Converter

This paper deals with the output voltage regulation problem of dc-dc boost converter feeding a resistive load. A new control mechanism based on Chebyshev neural network embedded in an adaptive backstepping framework is proposed for the boost converter control. Since the converter is complex, time varying and non-linear in nature, it exhibits high sensitivity to unanticipated disturbances in the load current. Hence, designing a robust control mechanism to attain a satisfactory transient and steady state performance over a wide range of operating points is a challenging task. In this work, a control law is derived based on the systematic and recursive design strategy of adaptive backstepping method. A single layer functional link Chebyshev neural network is employed for a fast estimation of uncertain and time varying load profile of the boost converter. The stability of overall converter equipped with the proposed controller is proved using Lyapunov stability criterion. Further, in order to validate the proposed methodology, the boost converter is simulated in MATLAB/Simulink software and is subjected to different load perturbations. The efficacy of the proposed control is highlighted by evaluating it against the conventional adaptive backstepping control under identical conditions. The results obtained reveals that the proposed control is much faster in estimating the unknown load parameter and offers satisfactory output voltage tracking, yielding fast response and low peak overshoot/undershoot in the event of unknown load perturbations. Experimental investigation using dspace DS1103 controller is further carried out to validate the efficacy of proposed control scheme.

Robust Frequency Control of an Islanded AC Micro Grid using BDA Optimized 3DOF Controller under Plug in Electric Vehicle

The article presents the effectiveness of a Binary Dragonfly Algorithm (BDA) based 3-DOF controller for robust frequency control in an islanded AC micro-grid system under different uncertainties. A micro-grid is incorporated with the integration of various renewable energy based distributed generations (DG). The proposed micro-grid system is structured with wind turbine generator (WTG), Photo voltaic (PV) system, Diesel engine generator (DEG), Micro-turbines (MT), Aqua electrolyzer based Fuel Cells(FC) and with few energy storage devices i.e Battery energy storage (BES) and Flywheel energy storage (FES). Moreover a chargeable plug in electric vehicle is effected as load side demand while obtaining frequency control mechanism in micro-grid system. However large dynamics, low inertia and incurred uncertainties of most DG system affects system performance especially on system frequency seriously. In view of this to obtain robust control mechanism in islanded micro-grid system the article proposes a novel Binary Dragonfly Algorithm based 3-DOF controller to ensure servicing of good quality power to remote consumers. The performances of proposed BDA optimized 3-DOF controller is compared with conventional PSO, GA technique based PID and PI controller in order to justify supremacy of proposed approaches. Finally it has been suggested that the proposed BDA optimized 3-DOF controller is more effectiveness over other optimized controllers.