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Pesticides are essential for removing plant pests and sustaining good yields on agricultural land. Excessive use has detrimental repercussions, such as the depletion of soil fertility and the proliferation of immune insect species, such as Nilaparvata lunges and Nezara viridula. Unmanned aerial vehicle (UAV) variable-rate spraying offers a precise and adaptable alternative strategy for overcoming these challenges. This study explores research trends in the application of semi-automatic approaches and land-specific platforms for precision spraying. The employment of an autonomous control system, together with a selection of hardware such as microcontrollers, sensors, pumps, and nozzles, yields the performance necessary to accomplish spraying precision, UAV performance efficacy, and flexibility in meeting plant pesticide requirements. This paper discusses the implications of ongoing and developing research. The comparison of hardware, control system approaches, and data acquisition from the parameters of each study is presented to facilitate future research. Future research is incentivized to continue the precision performance of the variable rate development by combining it with cropland mapping to determine the need for pesticides, although strict limits on the amount of spraying make it difficult to achieve the same, even though the quality is very beneficial.

The purpose of the paper is to propose a new implementation of the PID (proportional–integral–derivative) algorithm in digital hardware. The proposed structure is optimized for cost. It follows a serialized, rather than parallel, scheme. It uses only one arithmetic block, performing the multiply-and-add operation. The calculations are carried out in a sequentially cyclic manner. The proposed circuit operates on standard single-precision (32-bit) floating-point numbers. It implements an extended PID formula, containing a non-ideal derivative component, and weighting coefficients, which enable reducing the influence of setpoint changes in the proportional and derivative components. The circuit was implemented in a Cyclone V FPGA (Field-Programmable Gate Array) device from Intel, Santa Clara, CA, USA. The proper operation of the circuit was verified in a simulation. For the specific implementation, which is reported in the paper, the sampling period of 516 ns was obtained, which means that the proposed solution is comparable in terms of speed with other hardware implementations of the PID algorithm operating on single-precision floating-point numbers. However, the presented solution is much more efficient in terms of cost. It uses 1173 LUT (Look-up Table) blocks, 1026 registers, and 1 DSP (Digital Signal Processing) block, i.e., about 30% of logic resources required by comparable solutions. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Robotics is currently the most cutting-edge international science and technology, as well as a highvalue-added core technology. Robots are widely used in a variety of industrial fields, as a new direction in the development of robotics, and play an important role in solving the current employment problems in China. OBJECTIVES: This paper combines its research results, introduces the machine learning method in the robot control system, and establishes the employment index system in the robot working environment by combining the employment factors with the environmental relationship analysis. METHODS: This paper combines its research results, introduces the machine learning method in the robot control system, and establishes the employment index system in the robot working environment by combining the employment factors with the environmental relationship analysis. RESULTS: The study found that the willingness of university students to choose a job gradually increases as their education level rises; the lower the level of education, the weaker their willingness to look for a job; the higher the level of education the more sensitive they are to the quality of education and educational specialities, the higher their willingness to work. CONCLUSION: Based on the robot control system design the factors that have an impact on the environment in real economic activities (e.g., age, gender, occupation, education level, etc.) play a role in promoting the future application and development of robotics in China. [ABSTRACT FROM AUTHOR]

While using multirotor UAVs for transport of suspended payloads, there is a need for stability along the desired path, in addition to avoidance of any excessive payload oscillations, and a good level of precision in maintaining the desired path of the vehicle. However, due to the nonlinear and underactuated nature of the system, in addition to the presence of mismatched uncertainties, the development of a control system for this application poses an interesting research problem. This paper proposes a control architecture for a multirotor slung load system by integrating a Multi-Surface Sliding Mode Control, aided by a Radial Basis Function Neural Network, with a Deep Q-Network Reinforcement Learning agent. The former will be used to ensure asymptotic tracking stability, while the latter will be used to suppress payload oscillations. First, we will present the dynamics of a multirotor slung load system, represented here as a quadrotor with a single pendulum load suspended from it. We will then propose a control method in which a multi-surface sliding mode controller, based on an adaptive RBF Neural Network for trajectory tracking of the quadrotor, works in tandem with a Deep Q-Network Reinforcement Learning agent whose reward function aims to suppress the oscillations of the single pendulum slung load. Simulation results demonstrate the effectiveness and potential of the proposed approach in achieving precise and reliable control of multirotor slung load systems. [ABSTRACT FROM AUTHOR]

In this paper, a new modulation strategy based on the carrier-based switching strategy for the non-square direct matrix converters (MC) is proposed to control the active power of distributed generation (DG) units. In this strategy, the active power of DGs is controlled by the central input current control of the non-square direct MC independent from the voltage and frequency. Conventionally, each DG has a converter, and for supplying a load with N number of DGs, N number of converters are needed and each converter has its own modulation switching and control strategy to control the power output of each DG. Needless to say, in a microgrid with N number of DGs, the control strategy of each converter has more complex structure than that of a microgrid with one converter, and surely the former strategy entails more volume and price. Using the proposed converter in this paper, it is possible to supply a load with N number of DGs through one converter. Also, the power outputs of all DGs are controlled by a central control strategy. The proposed central control strategy is described and simulated for a typical microgrid. Experimental and simulation results validate the effectiveness of the proposed converter and the proposed strategy. The results demonstrate the applicability and efficiency of the system and verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

Semiconductor vertical furnaces must achieve even faster and more precise temperature control due to the demand for ever-reducing the minimum feature size or critical dimension in semiconductor chips. Also, the insulation performance of vertical furnaces has improved to reduce power consumption; as a side effect, temperature reduction operation takes longer without active cooling. Therefore, in addition to heaters, vertical furnaces equipped with coolers have emerged to achieve higher productivity, more precise temperature control, and lower power consumption. However, the inability to generate positive and negative control inputs for one of the heaters or coolers poses a challenge for an intuitive controller parameter design. The aim of this paper is to address these issues by proposing an intuitive method for designing a controller in the frequency domain which virtually integrates heaters and coolers. We implemented the controller in a full-scale actual semiconductor vertical furnace and first confirmed that the linearity is high. Furthermore, we experimentally verified that the controller achieves both high-speed, high-precision temperature control and low power consumption. [ABSTRACT FROM AUTHOR]

Automated Guided Vehicles (AGVs) are essential elements of manufacturing intralogistics and material handling. Improving the position accuracy along the AGV trajectory allows the vehicle to work on narrower aisles with lower error tolerance. Despite the increasing number of papers in AGVs and mobile robots' position control research area, there is a lack of curatorial work presenting and analyzing the control strategies applied in the problem domain. Therefore, the main objective is to analyze the published researches of the past seven years on the position control of AGVs to recognize research patterns, gaps, and tendencies, outlining the research field. The paper proposes a systematic literature review to investigate the research field from the controller design perspective. Its protocol and procedures are presented in detail. Four main research topics were addressed: the control strategies used in the AGV position control problem, how the literature presents the AGV operating requirement of position accuracy, how the literature validate the proposed controller and present their results regarding the system's position accuracy, and the technological tendencies the proposed solutions reveals. Besides, within the main topics, other points were investigated, such as the AGV application area, the considered mathematical model, the sensors and guidance system used, and the maximum payload of the vehicle and operation under different load conditions. The data synthesis shows the predominant control strategies applied to the problem and the interaction among distinct control theory areas, indicating a notable interaction of Intelligent Control techniques to the other strategies. The paper's contributions are using a systematic literature review method over the AGV position control publications, presenting an overview of the research area, analyzing the research question topics from selected articles, and proposing a research agenda. [ABSTRACT FROM AUTHOR]

This paper proposes a two-level control strategy based on a super-twisting sliding-mode algorithm (STA) to optimally allocate power imbalances in shipboard microgrids (SMGs) while achieving frequency regulation. The strategy employs an STA observer to estimate the unknown power load demand imbalances in finite time. This estimate is then passed to an online high-level optimal control framework to periodically determine the optimal sequence of power reference values for each energy storage device (ESS), minimising the operational cost of the SMG. The online optimised power reference values are interpolated and passed to the low-level STA control strategy to control the output power of each ESS. The efficacy of the proposed methods is demonstrated through numerical simulations conducted on a prototypical model of an SMG equipped with two ESSs, namely batteries and fuel cells with associated hydrogen storage. [ABSTRACT FROM AUTHOR]

Although smart home has received wide attention in recent years, numerous scholars focus more on energy optimization strategy than energy dispatch hardware device (named energy router). Meanwhile, this energy router should have several features, i.e., high renewable energy utilization, energy multi-port and low volume. Thus, this paper designs a nine-port energy router regarding smart home and proposes a multimode hierarchical management strategy for this energy router. First, for the multi-port demand of wind, solar, storage and utilization, this paper presents a nine-port energy router to improve the renewable energy consumption and power supply flexibility. In addition, to reduce the volume of the energy router, a non-isolated AC/DC hybrid topology is constructed through embedding the integrated power electronic converters, which achieves the miniaturization of the energy router. In order to improve the renewable energy utilization rate, the decentralized module control is proposed for the components of energy router to provide the voltage and frequency support for system, and realizes the power sharing of distributed generations (DGs). Furthermore, the power exchange control with three-mode switching is proposed to guarantee the global energy flow balance under complex conditions. Eventually, the feasibility of the energy router is verified by the simulation and experiments. [ABSTRACT FROM AUTHOR]

Microgrid's voltage regulation is of particular importance during both grid-connected and islanded modes of operation. Especially, during the islanded mode, when the support from the upstream grid is lost, stable voltage regulation is vital for the reliable operation of critical loads. This paper proposes a robust and data-driven control approach for secondary voltage control of AC microgrids in the presence of uncertainties. To this end, unfalsified adaptive control (UAC) is utilized to select the best stabilizing controller from a set of pre-designed controllers with the minimum knowledge required from the microgrid. Two microgrid test systems are simulated in MATLAB to verify the effectiveness of the proposed method under different scenarios like load change and communication link failure. [ABSTRACT FROM AUTHOR]

Background: Petri nets are a formal specification technique for modelling of control processes and modern flexible manufacturing systems. Interpreted Petri nets take into account input and output signals, allowing to apply them in any control system or even in control part of a cyber-physical system. Due to the fact that Petri nets are not used in the industrial practice, the students sometimes lack motivation to learn them. Contributions: In the paper we propose how to help students learn interpreted Petri nets with Minecraft (as a game-based learning). We show how interpreted Petri nets can be modelled in Minecraft and how they communicate with the surrounding environment via input and output signals to visualize control processes. The proposed approach has been validated experimentally among university students. Hypotheses: (1) Creating interpreted Petri net models with Minecraft helps to understand the basic principles; (2) Minecraft makes the course more attractive. Methodology: Students were divided into an experimental group (with game-based learning) and a control group (with traditional learning). The experimental group filled in a knowledge test twice (on the entry and on the exit) and a questionnaire. The control group filled in the same knowledge test at the end of the course. Findings: The observations confirm that the Minecraft-based teaching of interpreted Petri nets allows to gain better results in final tests, making at the same time the course more attractive and enjoyable. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive self-tuned current controller design for an LCL-filtered LC-tuned single-phase shunt hybrid active power filter (HAPF), which offers adaptability and flexibility of the control system to filter parameters changes. System modelling and online identification of parameters are presented. Then, a systematic self-tuned controller (STC) design is proposed to calculate the controller parameters and obtain the final control law adaptively. The exact HAPF parameters design is described and the overall closed-loop stability evaluation with considering digital control delay is discussed in this paper. To confirm the theoretical achievements, simulations and experimental tests on a real prototype system are performed. The results are in good accordance and demonstrate the effectiveness and superior performance of the suggested control technique. Furthermore, a comprehensive comparison between the proposed control technique and other controllers is provided to show the superiority of the proposed system from different aspects. [ABSTRACT FROM AUTHOR]

The field of human-computer interaction has progressed very rapidly over the last few decades, creating another area of research - human-robot interaction (HRI). This paper describes the implementation of HRI using developed Lithuanian language synthesis and recognition tools. Lithuanian language has a very small population of native speakers, which makes training the synthesizers and automated speech recognition tools very complex. Different Lithuanian language dialects and non-native speakers also experience severely deteriorated language recognition performance. There are still many issues concerning the lower level of the HRI field. The current automated Lithuanian speech recognition does not take into account the speaker's emotions. The issues of HRI are being considered. The task of developing HRI control system is discussed. HRI with the NAO V6 robot, a control system for verbal interaction, is discussed. The contribution of our research is related to the application of HRI to the pedagogical problem of teaching and motivating school children in the classroom. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the controllability conditions of linear control systems involving distinct local fractional derivatives. Sufficient conditions for controllability using Kalman rank conditions and the Gramian matrix are presented. We show that the controllability of the local fractional system can be determined by the invertibility of the Gramian matrix and the full rank of the Kalman matrix. We also show that the local fractional system involving distinct orders is controllable if and only if the Gramian matrix is invertible. Illustrative examples and an application are provided to demonstrate the validity of the theoretical findings. [ABSTRACT FROM AUTHOR]

The on-ground validation of control systems designed for manipulators working in orbit is very difficult due to the necessity of simulating the microgravity environment on Earth. In this paper, we present the possibilities of utilising the KUKA KUBE test-bed with industrial robots to experimentally verify space systems using hardware-in-the-loop tests. The fixed-base KUKA industrial robot is operated in gravitational environment, while the space system model plant is solved in real time parallel to on-ground experiment. The test-bed measurements are the input of the model plant, and the output of the model is treated as an input for the industrial robot actuation. In the performed experiment, the control system based on the Dynamic Jacobian is validated. The desired point that is reached by the manipulator's end-effector is constant in the simulated environment and moving with respect to the test-bed frame. The position of the space manipulator's end-effector is calculated by evaluating dynamics of the satellite in real-time model. The results show that the control system applied to the KUKA robot works correctly. The measurements from the torque sensors mounted in KUKA robot's joints are in accordance with the simulation results. This fact enhances the possibilities of gravity compensation, thus simulating microgravity environment on the test-bed. [ABSTRACT FROM AUTHOR]

This paper presents a method for controlling the voltage of inverter-based Microgrids by proposing a new scale-free distributed cooperative controller. The main contribution of this paper is that the proposed distributed cooperative controller is scale-free where is independent of any information about the communication system and the number of distributed generators, as such it works for any Microgrids with any size. Moreover, the communication network is modeled by a general time-varying graph which enhances the resilience of the proposed protocol against communication link failure, data packet loss, and arbitrarily fast plug and play operation in the presence of arbitrarily finite communication delays as the protocol does not require the knowledge of the upper bound on the delay. The stability analysis of the proposed protocol is provided. The proposed method is simulated on the CIGRE medium voltage Microgrid test system. The simulation results demonstrate the feasibility of the proposed scale-free distributed nonlinear protocol for regulating voltage of Microgrids in the presence of communication failures, data packet loss, noise, and degradation. [ABSTRACT FROM AUTHOR]

This paper proposes a direct damping feedback control method against power system oscillations under small or large disturbances. For a targeted oscillation mode, this control method continuously minimizes the difference between the real-time estimated damping ratio and a desired value by changing power outputs of selected inverter-based resources. The method adopts a proportional-integral controller whose parameters are tuned using a nonlinear single-input-single-output model on damping estimation and control with a single-oscillator equivalent regarding the targeted power system mode. Also, optimization of these controller parameters considers both robustness and time performance in damping control. The paper also proposes utilizing a “zero-th order” parametric resonance phenomenon to simplify the controller design. Tests on a small power system and a 140-bus 48-machine Northeast Power Coordinating Council system validate the effectiveness of the proposed damping controller utilizing battery-based energy storage systems. [ABSTRACT FROM AUTHOR]

Uncertain cut-in maneuver of vehicles from adjacent lanes makes it difficult for vehicle's automatic speed control strategy to make judgments and effective control decisions. In this paper, an intelligent speed control strategy for uncertain cut-in scenarios is established based on a basic autonomous driving system. This strategy judges cut-in maneuver from surrounding vehicles and outputs adaptive control action under current environment according to Q value of state-action pair based on a Q network. In addition, according to the analysis of cut-in scenarios, the Q network is trained based on a novel reinforcement learning method named as experience screening deep Q-learning network (ES-DQN). The proposed ES-DQN is an extension of double deep Q-learning network (DDQN) algorithm, and includes two parts: experience screening and policy learning. Based on the experience screened from the experience screening part, the proposed learning method can train an intelligent speed control strategy which has stronger adaptability and control effect in uncertain cut-in scenarios. According to simulation results, the proposed intelligent speed control strategy trained by ES-DQN has better performance under uncertain cut-in scenarios than DDQN method and traditional ACC strategy. Meanwhile, by adjusting weight value in reward function, the system can realize different control target. [ABSTRACT FROM AUTHOR]

Nowadays, energy generation systems that include renewable energies, substations, distribution, transmission, control, measurement, and storage applications, among others, and are interrelated are known as Smart Grids. All these techniques and technologies involve extensive research and development, which allows for the solving of key aspects, such as control, diagnosis, and fault recovery, as well as communication systems focused directly on the operation of the electrical networks. Due to the relevance of knowledge concerning developments in these areas of Smart Grids, this paper presents a review of the research related to the control systems applied to Smart Grids and Micro Grids, both in supply and demand. Likewise, some control models relate to different processes, with a special focus on techniques related to Petri nets. The paper shows, among other outcomes, the advances in the control of smart grids, the types of generation and their influence on the design of transmission lines, integrated circuits applied based on sensors, communication technologies, and automation schemes in all levels of the electrical network. Finally, patents from 1950 to 2019 related to Smart Grid in energy systems are traced and presented. [ABSTRACT FROM AUTHOR]

Material flow analysis (MFA) is the main methodology to assess material flow circularity. It is essentially a data-analysis-based approach whose physical foundations consist of conservation of mass. To improve both the accuracy and the repeatability of MFA models, in this paper we leverage compartmental dynamical thermodynamics merged with graph theory and control theory. The key idea is that the thermodynamic compartments and their connections can be added, removed or modified as needed to achieve a circular material flow. Thus, our methodology consists of designing thermodynamical material networks (TMNs). We also provide a physics-based definition of circularity and implement a nonlinear compartmental control, which has been possible since TMNs are highly dynamic models based on differential calculus (i.e. ordinary differential equations) rather than on arithmetic as is typical for MFA models. As we envision scalable and repeatable designs of TMNs, we made publicly available the paper source code.1 [ABSTRACT FROM AUTHOR]

This paper presents a controller design technique for cascade control systems based on the grey wolf optimization (GWO) algorithm. In the proposed control scheme, the proportional-integral-proportional-derivative (PI-PD) controller structure is used to control both the open-loop unstable process in the primary loop and the stable process in the secondary loop. To determine the optimal controller parameters, a new optimization algorithm is used in which the Euclidean distance function is used as a multi-objective function. A symmetry property of the Euclidean distance function is that its distance does not depend on the starting point and destination. The multi-objective function is designed according to system time response specifications such as settling time, overshoot, and steady-state error. Thus, the optimization algorithm allows the simultaneous determination of all controller parameters according to the desired output response. Three simulation studies are presented in the paper and the results are compared with studies using various methods based on internal model control, a modified Smith predictor, and a genetic algorithm. The simulation results reveal that the proposed method improves the performances of the systems in the control of cascade processes. [ABSTRACT FROM AUTHOR]

An increasing number of new buildings equipped with modern and energyefficient thermo-technical systems contribute to society’s efforts to make urban environments more sustainable shortly than they were before. Despite this, the applied methods have negative consequences that slow down this process. On the (concrete) example of the sports hall, by analyzing the consumption of final (electrical) energy for artificial lightning, this paper pointed out the negative effects of shading in buildings – phenomena that arise as a consequence of accelerated urbanization, without more detailed planning prediction bases. To create this numerical study, the software packages EnergyPlus and Google SketchUp were used, which communicate via the Legacy OpenStudio platform. Based on the conducted simulations, it was concluded that the consumption of final (electrical) energy for artificial lighting can be increased over 2.59 times, depending on the next parameters: the shape factor and orientation of the building, technical characteristics of lighting, and windows, spatial planning and urbanization, etc. For the sake of creating sustainable cities, energy-eco projects should not focus only on individual buildings in the future, i.e. isolated cases. The problem should be looked at more broadly, taking into account at least the immediate environment, i.e. “communication” of the analyzed building with its surroundings. [ABSTRACT FROM AUTHOR]

Multi-surface sliding mode control addresses the limitations of traditional sliding mode control by employing multiple sliding surfaces to handle uncertainties, disturbances, and nonlinearities. The design process involves developing sliding surfaces, designing switching logic, and deriving control laws for each surface. In this paper, first, a robust finite-time multi-surface sliding mode controller will be presented and its performance analyzed by applying it to a multirotor subjected to a suspended payload, modeled in the form of a single pendulum, itself defined as a spatial (3D) dynamic model. Next, an adaptive finite-time multi-surface sliding mode controller will be derived—adding a variable adaptive parameter to the existing sliding surfaces of the robust finite-time control—and applied to the same system. It will be shown that the adaptive controller, with an adaptive parameter that adjusts itself based on the present value of the multi-surface sliding mode parameter, creates an improved fast finite-time convergence by obtaining an optimal settling time and minimizing undershoot of the multirotor state vector. Empirical verification of the effectiveness of the adaptive control will be carried out by presenting the control performances against a step response. It is also shown that the control may be utilized to approximate external disturbances—represented by the pendulum—and that with the application of control, the vehicle's motion may be stabilized and the payload swing suppressed. Lyapunov stability theory-based stability proofs for the controllers' designs are developed, showing the asymptotic stability of the output and uniform boundedness of the errors in the system dynamics. It is verified that the multi-surface sliding mode control can account for system uncertainties—both matched and mismatched—in addition to changes in internal dynamics and disturbances to the system, where the single pendulum payload is representative of the changes in dynamics that may occur to the system. Numerical simulations and characteristics are presented to validate the performance of the controllers. [ABSTRACT FROM AUTHOR]

The penetration of inverter-based resources is growing rapidly around the globe. During a fault, the behavior of inverter-based resource is very different from a traditional synchronous machine based generation. As the penetration of inverter-based resources increases, there is an urgency for the industry to understand their behavior so that these resources can be accurately modeled and their impact on various protection schemes can be studied in detail. This path begins with standardizing the response of inverter-based resources to a fault. Additionally, this paper discusses issues with modeling inverter-based resources in a short circuit model which is developed for systems dominated by synchronous machines and finally a need for further research to understand impacts on traditional protection schemes as inverter-based resources continue to displace traditional generation. This paper does not offer solutions however, it is intended to encourage further study by industry professionals toward development of solutions. [ABSTRACT FROM AUTHOR]

As high-speed railways develop rapidly worldwide, the problems of neutral section and power quality are becoming increasingly prominent. These problems affect the normal operation of the power grid and the electric locomotives. The co-phase power supply schemes were proposed by researchers, which can solve these problems well. Among them, the MMC-based scheme (MMC-5 L) is a representative one. The existing scheme, when applied to the auto-transformer (AT)-fed system which is usually adopted by high-speed railways, needs to install an auto-transformer on the output side. To eliminate the auto-transformer and to obtain the more suitable and superior co-phase power supply schemes to AT-fed system, two improved schemes are proposed in this paper based on the novel MMC-based scheme (MMC-6 L) we proposed before. While establishing the mathematical model, creating the control system, and carrying out simulation verification of the proposed schemes, the proposed schemes are compared with MMC-6 L and MMC-5 L in terms of topological characteristics, control system complexity, power loss, and functionality. The results show that while the proposed schemes can fulfill the functions of the co-phase power supply scheme well like the MMC-5 L and MMC-6 L, they are more suitable and superior for the AT-fed system in terms of control system complexity and power loss. Among them, MMC-5L1CB performs best in power loss, and MMC-4L2CB performs best in control system complexity. [ABSTRACT FROM AUTHOR]

With the large-scale wind power integration into the power system, the inertia and damping characteristics of the system have been weakened, which is not conducive to fulfill the grid-friendly operation of wind power. Aiming at this, an adaptive control scheme combining virtual inertia control (VIC) and supplementary damping controller (SDC) is proposed in this paper. Firstly, the mathematical model of wind grid-connected power system with VIC is established. Secondly, the polytopic linear parameter varying (LPV) system is built to describe the uncertainty of system operating points, and the gap metric-based nonlinear evaluation method is used for polytope vertex configuration. Next, Youla-Kucera parametrization are extended to polytopic LPV system to design an adaptive damping control, in which VIC and SDC are coordinated to provide damping and virtual inertia simultaneously. Finally, the proposed adaptive control scheme is compared with several existing control techniques to validate its effectiveness and advantages in suppressing system oscillation in the modified IEEE 39-bus system integrated with 2 wind turbines. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear balancing cube system is considered, the concept for which is based on an inverted pendulum. The main purpose of this work was the modelling and construction of a balancing cube with the synthesis of the control system. The control objectives included swing-up and stabilization of the cube on its vertex at an unstable equilibrium. Execution of the intended purpose required, first, deriving a cognitive mathematical model. It was based on the Lagrange method. Next, a mathematical model for control purposes was derived. The project of the physical model of the balancing cube was presented. A stabilization system based on a linear quadratic regulator (LQR) was developed. Moreover, a swing-up mechanism was used to bring the cube close to the upper equilibrium point. The algorithm switching condition was important to enable the correct functioning of the system. The developed control system was verified in the Matlab environment. Finally, verifying experiments and comparisons among models (mathematical and physical) were performed. [ABSTRACT FROM AUTHOR]

Most microgrid protection schemes found in published literature suffer from a lack of generality in that they work well for the assumed topology, including type and placement of sources. Other generic protection schemes tend to be too complicated, too expensive, or both. To overcome these drawbacks, a topology-agnostic, scalable, and cost-aware protection based on fundamental principles that work in the presence of high penetration of inverter-based resources (IBRs) is developed and tested in this paper. The protection system also implements stable automatic reconfiguration of the healthy sections of the system after clearance of fault, thus increasing resilience by self-healing. To achieve this ambitious goal, stable inverter models are developed that operate in unbalanced networks in grid-connected and islanded modes, even with 100% IBRs, share power without conflicting controls, and can ride through faults while limiting fault currents. The scheme is tested for primary and backup protection and reconfiguration on the IEEE 123-node feeder in grid-connected and islanded modes with 15 IBRs connected to the system. [ABSTRACT FROM AUTHOR]

The operation of a voltage source inverter (VSI) depends on its output LC filter and the PWM modulator delay. The VSI model includes serial equivalent resistance based on the resistances of the active inverter bridge transistors, the filter coil winding, and additional PCB elements, such as traces and connectors, in addition to the large equivalent resistances that result from power losses in the coil core and switches. These dynamic power losses depend on the switching frequency and the inverter load. This paper investigates the change in equivalent serial resistance that occurs if the standard Si-MOSFET switches are replaced with wide bandgap (WBG) transistors with correspondingly lower equivalent serial resistance. The paper further investigates how such a change influences the design of the controller, given that replacement of the switches shifts the roots of the closed-loop characteristic equation. Theoretical analyses of the influence of equivalent serial resistance for a multi-input single-output passivity-based controller and a single-input single-output coefficient diagram method are also presented. These analyses are applied to both types of switches. Two methods are used to measure the serial equivalent resistance for a given VSI using Si and WBG switches. The possibility of replacing switches with WBG technology in existing inverters was assessed, and the corresponding controller adjustment that would be required. The theoretical analysis is verified via the use of an experimental VSI. [ABSTRACT FROM AUTHOR]

In this paper, a novel distributed control strategy addressing a (feasible) psycho-social-physical welfare problem in islanded Direct Current (DC) smart grids is proposed. Firstly, we formulate a (convex) optimization problem that allows prosumers to share current with each other, taking into account the technical and physical aspects and constraints of the grid (e.g., stability, safety), as well as psycho-social factors (i.e., prosumers’ personal values). Secondly, we design a controller whose (unforced) dynamics represent the continuous time primal-dual dynamics of the considered optimization problem. Thirdly, a passive interconnection between the physical grid and the controller is presented. Global asymptotic convergence of the closed-loop system to the desired steady-state is proved and simulations based on collected data on psycho-social aspects illustrate and confirm the theoretical results. [ABSTRACT FROM AUTHOR]

The symmetry between customer expectations and operator goals, on one hand, and the digital transition of the railways, on the other hand, is one of the main factors affecting green transport sustainability. The European Train Control System (ETCS) was created to improve interoperability between different railway signaling systems and increase safety and security. While there are a lot of ETCS Level 2 deployments all over the world, the specifications of ETCS Level 3 are under development. ETCS Level 3 is expected to have a significant impact on automatic train operation, protection, and supervision. In this paper, we present an innovative control system architecture that allows the incorporation of artificial intelligence (AI)/machine learning (ML) applications. The architecture features control function virtualization and programmability. The concept of an intelligent railway controller (IRC) is introduced as being a piece of cloud software responsible for the control and optimization of railway operations. A microservices-based approach to designing the IRC's functionality is presented. The approach was formally verified, and some of its performance metrics were identified. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive Fuzzy Sliding Mode Control approach for an Assist-as-Needed (AAN) strategy to achieve effective human–exoskeleton synergy. The proposed strategy employs an adaptive instance-based learning algorithm to estimate muscle effort, based on surface Electromyography (sEMG) signals. To determine and control the inverse dynamics of a highly nonlinear 4-degrees-of-freedom exoskeleton designed for upper-limb therapeutic exercises, a modified Recursive Newton-Euler Algorithm (RNEA) with Sliding Mode Control (SMC) was used. The exoskeleton position error and raw sEMG signal from the bicep's brachii muscle were used as inputs for a fuzzy inference system to produce an output to adjust the sliding mode control law parameters. The proposed robust control law was simulated using MATLAB-Simulink, and the results showed that it could instantly adjust the necessary support, based on the combined motion of the human–exoskeleton system's muscle engagement, while keeping the state trajectory errors and input torque bounded within ± 5 × 10 − 2 rads and ± 5 N.m, respectively. [ABSTRACT FROM AUTHOR]

The authors propose a technique for reactive power compensation using a powerful regenerative controlled-speed synchronous motor drive (SMD) based on a three-level (3L) neutral point clamped (NPC) active front-end rectifier (AFE) and a voltage source inverter (VSI). The review of technical solutions for reactive power compensation showed that the limitations on the transmitted reactive power in the system under consideration still have not been studied. The paper provides a mathematical description and proposes synthesis-friendly block diagrams of the mathematical 3L-NPC-AFE-VSI and SMD models. The developed models allow defining the instantaneous values of the total 3L-NPC-AFE power consumed from the grid depending on the SMD load diagram. It is noted that the 3L-NPC-AFE-VSI-SMD system is designed without considering the opportunities for reactive power generation. It was determined that the limit value of reactive power generated by a 3L-NPC-AFE depends on the DC link voltage, the grid current consumption and the modulation index. The possibility of reactive power compensation by the SMD system through a 3L-NPC-AFE was experimentally tested on the main drive of a metal plate hot rolling mill. The analysis of the results obtained showed that during the breakdown, an SMD can generate reactive power equal to 16% of the total rated power using a 3L-NPC-AFE at a rated DC link voltage and without overcurrent. It was shown that generating reactive power is expedient in low-load SMD operation modes or at idle. Research in this area is promising due to the widespread use of high-power SMD based on a 3L-NPC-AFE-VSI and the tightening of requirements for energy saving and efficiency and supply voltage quality. The proposed reactive power control technique can be used as part of an industrial smart grid. [ABSTRACT FROM AUTHOR]

Power system control and transient stability analysis play essential roles in secure system operation. Control of power systems typically involves highly nonlinear and complex dynamics. Most of the existing works address such problems with additional assumptions in system dynamics, leading to a requirement for a complete and general solution. This paper, therefore, proposes a novel control framework for various power system control and stability problems leveraging a learning-based approach. The proposed framework includes a two-module structure that iteratively and jointly learns the candidate Lyapunov function and control law via deep neural networks in a learning module. Meanwhile, it guides the learning procedure towards valid results satisfying Lyapunov conditions in a falsification module. The introduced termination criteria ensure provable system stability. This control framework is verified through several studies handling different types of power system control problems. The results show that the proposed framework is generalizable and can simplify the control design for complex power systems with the stability guarantee and enlarged region of attraction. [ABSTRACT FROM AUTHOR]

This paper proposes an improved SOC balancing strategy for the modular energy storage system (ESS) based on low bandwidth communication (LBC) technology, aiming at solving the drawbacks of the conventional balancing strategy based on droop control. The proposed control scheme can improve the SOC balancing efficiency and remove the current deviation by using the SOC slope-adjusting and current-shifting approaches simultaneously. The average value of SOC can be derived through the LBC line, and the droop coefficient based on SOC can be controlled in the local control layer. Thus, the SOC of each sub-module can converge to the average SOC value in system dynamic process, and the balancing speed under the condition of low SOC difference between sub-modules can be improved. Furthermore, the current regulation performance in steady and transient states can be enhanced by using the proposed method. At last the effectiveness of the proposed strategy is verified by experimental results. [ABSTRACT FROM AUTHOR]

This paper presents a different Finite Control Set – Model Predictive Control (FCS-MPC) for grid-connected three-phase bidirectional power inverters. These are typically used in dc or ac renewable-based microgrids (MGs), where bidirectional operation and fast dynamic response is required. The bidirectional grid-connected inverters are an essential part of MG, which inject energy into the ac grid or demand energy from it. The dynamic behavior of the system is a major concern since the current can suddenly change depending on the hierarchical controller. This paper proposes a different cost function using sliding mode theory, which offers a good dynamic response, reduced computational burden, and a parameter-free control model. The operation principle of the proposed controller is given and evaluated using a Hardware-In-the-Loop (HIL) system, but also experimentally with a 1kW laboratory prototype. The final results demonstrate the advantages of using this approach in grid-connected three-phase bidirectional power inverters in terms of dynamic response and reduced computational burden, making this solution technically attractive and viable. [ABSTRACT FROM AUTHOR]

The high-frequency resonances (HFRs) around 700 Hz and 1.8 kHz have occurred in Yu′E project. Mechanism studies indicate that HFRs are caused by the interactions between the negative damping inductance characteristics of the MMC and the capacitive characteristics of the AC system. In this paper, two optimized methods regarding the current control loop are presented to suppress the HFRs. The first one is to use a round(x) function inserted into voltage feed-forward loop instead of low pass filter (LPF). The proposed method has less negative impact on transient characteristics of an MMC. The second one is to employ a second-order damping controller, including the parameters design, to reshape the MMC impedance around the multiple risky regions. The core of HFRs suppression is that the real part of the MMC impedance near the multiple intersection frequencies should be positive according to impedance stability theory. Combined with the proposed control methods and core of HFRs suppression, the simplified model of MMC is adopted to design the parameters using the analytical expressions. Moreover, the general steps of parameters design are presented. Finally, the optimized methods to suppress HFRs are verified by time-domain simulations. [ABSTRACT FROM AUTHOR]

Attitude determination and control systems (ADCS) represent a critical facet of CubeSat missions, orchestrating the precise orientation and stabilization of these small satellites in the space environment. This paper presents a comprehensive design and development of an ADCS tailored for CubeSats, harnessing a reaction wheel system to deliver a cost-effective and dependable solution for small satellite applications. The research begins by elucidating the requisites and specifications for the ADCS and then delves into the design phase, complemented by intricate modelling and simulation employing MATLAB Simulink and the Webots Simulator. The results of this study underscore the exceptional performance of the proposed ADCS configuration, leveraging the reaction wheel model. This system demonstrates an unparalleled capacity to achieve precise and controlled attitude adjustments, well within the defined parameters. Furthermore, this research underscores the pivotal role played by efficient system design, meticulous simulation, and rigorous testing in the triumphant implementation of ADCS, greatly enhancing CubeSat missions and their contributions to the realm of space exploration and technology innovation. This comprehensive approach to the design and testing of an ADCS for CubeSats ensures that these diminutive satellites continue to make significant strides in space missions, paving the way for an exciting future of space research and technology development. [ABSTRACT FROM AUTHOR]

This paper presents a proposal of a complex mechatronic system that enhances the effectivity of obtaining energy from renewable resources. The main focus is on the photovoltaic energy system, which obtains electricity from the conversion of solar radiation through photovoltaic crystalline silicon-based panels. The design of the complex mechatronic system consists of several steps. The structural design of the photovoltaic panel positioning unit in the form of a three-dimensional model is made in the selected modelling programming environment. Subsequently, a propulsion system is proposed for the designed structure, the functionality of which is verified in the programming environment Automated Dynamic Analysis of Mechanical Systems. The control system design using a programmable logical controller is also presented. The corresponding control algorithm is designed in the programming environment Step7 and covers the optimal positioning of photovoltaic panels. The developed application in the WinCC environment provides a visualization of the positioning control process. The conclusion is devoted to the assessment of the obtained results for the proposed complex mechatronic system for photovoltaic panel positioning in comparison with photovoltaic panels in fixed installation. The presented results were obtained by simulations. [ABSTRACT FROM AUTHOR]

Industrial robots are capable of performing automated tasks repeatedly, reliably and accurately. However, in some scenarios, human-in-the-loop control is required. In this case, having an intuitive system for moving the robot within the working environment is crucial. Additionally, the operator should be aided by sensory feedback to obtain a user-friendly robot control system. Haptic feedback is one way of achieving such a system. This paper designs and assesses an intuitive teleoperation system for controlling an industrial 6-DoF robotic manipulator using a Geomagic Touch haptic interface. The system utilises both virtual environment-induced and physical sensor-induced haptic feedback to provide the user with both a higher amount of environmental awareness and additional safety while manoeuvering the robot within its working area. Different tests show that the system is capable of fully stopping the manipulator without colliding with the environment, and preventing it from entering singularity states with Cartesian end effector velocities of up to 0.25 m/s. Additionally, an operator is capable of executing low-tolerance end effector positioning tasks (∼0.5 mm) with high-frequency control of the robot (∼100 Hz). Fourteen inexperienced volunteers were asked to perform a typical object removal and writing task to gauge the intuitiveness of the system. It was found that when repeating the same test for a second time, the participants performed 22.2% faster on average. The results for the second attempt also became significantly more consistent between participants, as the inter quartile range dropped by 82.7% (from 52 s on the first attempt to 9 s on the second). [ABSTRACT FROM AUTHOR]

In the paper we propose a fractional-piecewise-constant-order PID controller and discuss the stability and robustness of a closed loop system. In stability analysis we use the transform method and include the Nyquist-like criteria. Simulations for designed controllers are performed for the second-order plant with a delay. [ABSTRACT FROM AUTHOR]

The implementation of finite-control-set model predictive control (FCS-MPC) in voltage source inverters (VSIs) can make the system suffer from poor current harmonics performance, which may complicate the design of the required AC filter. To overcome this shortcoming, a carrier-based modulated model predictive control (CB-MMPC) strategy is proposed in this paper. This method enables the utilization of existing PWM modulation techniques with FCS-MPC, where a modulation waveform with zero-sequence signal injection is generated and compared to a triangular carrier wave, while optimizing the selection of the switching states. As it is shown, the studied CB-MMPC strategy not only considerably improves the current total harmonic distortion (THD) but also attains the performance of fast current dynamic response and robustness as the traditional FCS-MPC. Herein, the detailed implementation of the CB-MMPC control strategy is given, while considering its application to the current feedback control loop of a three-phase three-wire two-level VSI modulated at constant switching frequency. Finally, PLECS circuit simulation and a 3-kW VSI prototype are used to verify the superiority and the effectiveness of the presented CB-MMPC strategy. This is also benchmarked to the FCS-MPC and dead-beat based controllers. [ABSTRACT FROM AUTHOR]

Conventional model predictive control (MPC) for three-level active neutral point clamped converter (ANPC) utilizes weighting factors to achieve the optimal control of multiple control objectives in a single cost function. However, the selection of these weighting factors has an impact on the performance of the controlled objectives significantly. Tuning of weighting factors is usually tedious and lacks theoretical background. Moreover, the predictive and evaluation process for multiple objectives optimization have to be carried out by enumerating all admissible switching states within one loop. To simplify the complexity of this process and eliminate the effect of weighting factors, this paper proposes a cascaded predictive control scheme for a 3L-ANPC inverter fed induction machine (IM) drive. With the proposed approach, three separate cost functions for three control objectives, stator flux vector, neutral point voltage and device loss distribution are evaluated in a cascaded way, so that the optimization of these control objectives is performed independently. A 3L-ANPC inverter driven IM drive is studied in this paper to verify the effectiveness of the proposed algorithm. Experimental results in different operating conditions confirm that the proposed method achieves satisfactory steady-state and transient performances comparable to the conventional predictive control approach. The weighting factors used in the conventional method are eliminated and the computational effort is reduced by 68% compared to the conventional method without any sacrifice in the drive performance. [ABSTRACT FROM AUTHOR]

In industrial internet of things (IIoT), ultra-reliable and low-latency communication (URLLC) is proposed to guarantee the requirement of real-time wireless control systems in worst case, so as to maintain the system working in all cases. However, it is extremely challenging to maintain URLLC throughout the whole control process due to the scarcity of wireless resource. This paper develops an autonomous device-to-device (D2D) communication scheme by jointly considering reliability in URLLC and control requirement. In the proposed scheme, we consider the actual control requirement, i.e., control convergence rate, into communication design, where we find that it can be converted into a constraint on communication reliability. Then, the communication reliability constraint comes from control aspect, instead of URLLC, which leads to that the system does not need to guarantee worst case in URLLC. Second, the sensors autonomously decide whether to be activated with optimal probabilities to participate in the control process, which can maintain the communication reliability requirement with significantly less resource consumption. Simulation results show remarkable performance gain of our method. For instance, compared with fixed activation probability 40% only considering URLLC, the average power consumption of the proposed method can be reduced by at most about 100%. [ABSTRACT FROM AUTHOR]

This paper describes the scheme and algorithm for controlling a laboratory setup that result in low uncertainty and high convergence with respect to the characteristics of electric discharges under the conditions of variable parameters of a reaction medium. The article presents current and voltage oscillograms when processing hydrocarbon raw materials. Methods for calculating the energy impact of electrical discharge are described. A comparison is made between the parameters of electric discharge with current pulse limitations and those without current pulse duration limitations. The proposed approach to controlling the characteristics of electric discharges provides the same parameters of nonthermal nonequilibrium plasma and, as a result, a regular composition of the products of plasma pyrolysis of hydrocarbon raw materials. [ABSTRACT FROM AUTHOR]