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The work reported in this paper aims at developing an algorithm for system operators to solve a robust security-constrained AC optimal power flow (R-SC-ACOPF) problem, which also optimizes the settings of discrete controllers including load tap changers (LTCs) and shunt capacitor banks (SCBs). An iterative algorithm involving a master problem and a number of sub-problems is proposed. The master problem selects the optimal discrete controllers’ settings by taking into account primal SC-ACOPF constraints based on the single-component worst contingencies identified by the sub-problems. Each sub-problem is a bi-level max-min problem used to find the current worst contingency. The overall objective is to minimize the total cost, including generation and load shedding cost, while satisfying all relevant constraints. The master problem and sub-problems allow representing LTC tap positions, SCB status, and contingencies using binary variables. Two case studies are presented as applications of this novel technique. [ABSTRACT FROM AUTHOR]

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 presents a novel power flow control system for a remote military microgrid with hybrid energy storage. A combination of batteries and supercapacitors (SCs) is managed by the novel control system to increase the battery life by redirecting the higher frequency current that would have to flow in the battery if SCs were not present. This paper offers a practical solution to manage the SC current and ensure that the SCs are never overcharged or commanded to support the system when they are discharged to the lower operating limit chosen. The new controller allows the independent selection of the low-pass filter parameter and the number of SCs. By making the most out of these two degrees of freedom, we investigate different configurations, identifying the one achieving the highest cash flow for the overall system. Modeling, simulations, and experimental verification are presented and linked to the sensitivity analysis of the economics of the military microgrid. [ABSTRACT FROM AUTHOR]

This paper investigates the output consensus control problem of uncertain second-order nonlinear multiagent systems with unknown nonlinear dead zone, where the communication networks can be described as a directed graph with a fixed topology. The control input in each follower is assumed to be subject to unknown nonlinear dead zone. By the function approximation capability of neural networks (NNs), a distributed adaptive NN-based controller is designed for each follower in the graph such that all the outputs of the followers can asymptotically synchronize to the output of the leader with synchronization errors being semiglobally uniformly ultimately bounded. Based on Lyapunov stability theory and algebraic graph theory, analysis is conducted on stability and parameter convergence of the proposed algorithm. Finally, an example is provided to validate the theoretical results. [ABSTRACT FROM PUBLISHER]

The use of power converters has grown in the last years with the advances in photovoltaic and wind based power generation systems, and the progress in modern concepts such as microgrids and electric mobility. A consequence has been the development of devices allowing for the exchange of energy among different distribution buses, and feeding AC or DC loads from low DC voltage levels, whose proper operation is achieved by means of specialized control systems. Simultaneously, the power converters used for conventional industrial applications have evolved thanks to the application of new control methods, and the combination of these with well-established techniques. This special issue contributes theoretical and practical advances to the state-of-the-art field at the crossroads of power electronics and control systems. The seven included papers cover particular applications requiring either DC–DC, DC–AC or AC–DC conversion stages. [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]

This paper presents an elegant method for determining the simplest model of a power system electrical/mechanical load that will suffice for dynamic frequency power system studies and closed-loop simulation work. The strategy behind this technique is to supply the simplest load model possible that gives sufficiently accurate results for the goals of each unique modeling effort. This paper identifies the frequency characteristics of several different load types. It also identifies the level of load model detail required for testing typical power management systems, contingency-based load-shedding systems, frequency-based load-shedding systems, governor control systems, island/grid/unit autosynchronization systems, and exciter control systems. This paper describes how to lump loads without loss of fidelity, when an induction motor needs to be modeled as a single-cage or double-cage motor model, what sort of mechanical load model is appropriate, when we can assume zero inertia for a direct-on-line type of load, and how to verify the turbine/generator inertia, and load inertia from field tests. This paper concludes with a simple reference that engineers can use to specify the level of detail required when modeling industrial power system loads. [ABSTRACT FROM PUBLISHER]

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 presents an active learning strategy for robotic systems that takes into account task information, enables fast learning, and allows control to be readily synthesized by taking advantage of the Koopman operator representation. We first motivate the use of representing nonlinear systems as linear Koopman operator systems by illustrating the improved model-based control performance with an actuated Van der Pol system. Information-theoretic methods are then applied to the Koopman operator formulation of dynamical systems where we derive a controller for active learning of robot dynamics. The active learning controller is shown to increase the rate of information about the Koopman operator. In addition, our active learning controller can readily incorporate policies built on the Koopman dynamics, enabling the benefits of fast active learning and improved control. Results using a quadcopter illustrate single-execution active learning and stabilization capabilities during free fall. The results for active learning are extended for automating Koopman observables and we implement our method on real robotic systems. [ABSTRACT FROM AUTHOR]

This paper proposes a new battery management system (BMS) for a series string of battery cells. The proposed control structure is based on the duality of the adaptive droop control theory used in dc micro-grid connected sources. An adaptive virtual admittance is used in this paper similar to the virtual resistance control structure used with dc micro-grid connected sources. The virtual admittance value is adjusted according to the associated state of charge for every connected battery cell. The presented BMS control structure yields higher reliability compared to the conventional ones due to its decentralization features and its communication-less ability. Thus, balanced power-sharing is realized among the connected battery cells during charging/discharging conditions. The stability of the proposed control is analyzed using the small signal model. The proposed BMS control structure is validated using simulation results and an experimental prototype for three connected battery cells. [ABSTRACT FROM AUTHOR]

This paper reconsiders the iterative learning control (ILC) problem for variable trial lengths via compensating output data by using an auxiliary predictive model when the controlled process does not reach the desired trial length. Moreover, this paper aims to propose a general and data-driven ILC method without requiring any explicit mechanistic model information. Specifically, an iterative difference with state transition expression is performed at first over the desired trial length in iteration domain to build an auxiliary predictive model for the iterative input–output dynamics of the linear discrete-time system. Then, an auxiliary predictive compensation-based ILC (APC-ILC) method is presented by defining an expanded output variable in which the predictive output is incorporated to compensate the unavailable output data due to the shorter operation length. The learning gain is iteration-time-varying and is updated using real-time data to adapt to system changes. Furthermore, the proposed learning control law contains additional input information to further improve the control performance. Theoretical analysis and simulations further verify the effectiveness of the proposed APC-ILC. [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]

A modular multilevel converter control system, based on converter energy storage, is proposed in this paper for two different control modes: active power and dc voltage. The proposed control system decouples the submodule (SM) capacitor voltages from the dc bus voltage. One of the practical applications is the management of active redundant SMs. A practical HVDC system with 401-level MMCs, including 10% redundancy in MMC SMs, is used for validating and demonstrating the advantages of the proposed control system. This paper also presents a novel capacitor voltage balancing control based on \max–\min functions. It is used to drastically reduce the number of switchings for each SM and enhances computational efficiency. [ABSTRACT FROM AUTHOR]

The position or movement control of an automated guided vehicle (AGV) is crucial for its operation. However, choosing the AGV position sensor is not a trivial task. This paper investigates the sensors and sensing techniques in machine vision applied in AGV position control in the past 5 years of published academic research. Using a systematic literature review method, we seek to answer the main research question: which sensors and sensing techniques are used in indoor AGV positioning control problems according to the past 5 years of published research and their technological impact. In doing so, we address three sub-question: (i) is the sensor/sensing technique related to the AGV application area; (ii) is the sensor/sensing technique applied to the problem related to the control strategy and/or the AGV guide; (iii) is the sensor/sensing technique related to the required AGV accuracy/sensitivity level. The paper contributions are the application of a systematic method of literature review in AGV position sensors, the research area overview from the selected 31 articles of the past 5 years, and a research agenda proposal. [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]

This paper contributes to the accurate and efficient computation of control system equations in electromagnetic-transient simulation tools. The proposed approach is based on the formulation of a reduced rank Jacobian matrix in a fully iterative Newton method. In addition, this paper compares the accuracy and efficiency for the proposed method's variants, including a hybrid approach with a fixed-point solution. [ABSTRACT FROM PUBLISHER]

This paper proposes an evolutionary algorithm-based energy-saving control strategy to control a highly nonlinear and time-varying active magnetic bearing (AMB) positioning system that considers energy efficiency and control performance simultaneously. Most AMB control schemes use a bias current with a superimposed control current to improve the linearity and dynamic performance of the system. However, the bias current causes power losses even if no electromagnetic force is required. As such, a recurrent wavelet fuzzy neural network with adaptive differential evolution (RWFNN-ADE)-based dynamic bias current control strategy is proposed in this paper so as to minimize the energy consumed by an AMB without altering its positioning performance and robustness. To begin with, this paper analyzes the operation principle of the AMB positioning system with a differential driving mode. Subsequently, the proposed RWFNN-ADE control scheme, in which the control current and bias current are controlled by the RWFNN and ADE, respectively, is introduced in detail. Finally, the experimental results demonstrate the high-accuracy control and significant energy-saving performances of the proposed RWFNN-ADE-controlled AMB positioning system. In the tests corresponding to operation periods of 10 and 50 s, the energy improvements compared to the baseline values were 20.24% and 17.65%, respectively, in nominal cases, and 18.89% and 18.68%, respectively, in parameter variation cases, for the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper clearly demonstrates the structure of Experimental Advanced Superconducting Tokamak (EAST) power supply system and analyzes principles of the finite-state machine (FSM) elaborately. Depending on the characteristics of EAST power supply system and the requirements of it, this paper chooses the real-time Linux as system platform and experimental physics and industrial control system (EPICS) as development tool to design a control system of the EAST poloidal field power system supply. This paper utilizes a temporal logic control based on the FSM in order to regulate the operation process of real-time sequence logic control of 12 sets of power controllers. This design is evaluated and tested, and it completely meets the real-time requirement of the poloidal field power supply (PFPS) control system. Several experiments have proved that this design definitely meets the real-time sequence logic control requirement of the PFPS control system in the complex situations under magnetic fields. [ABSTRACT FROM AUTHOR]

Smart cyber-physical systems (S-CPSs) are complex engineered systems empowered by cyber-physical computing and equipped with the capability of reasoning, learning, adapting, and evolving. As an outcome of data-driven dynamic computing, reasoning capabilities, and the run-time obtained own knowledge, nonlinear and emergent behavior of S-CPSs whilst in operation is an open issue, not experienced in the case of conventional technical systems. This paper analyzes the technical issues of run-time operation and emergent behavior of S-CPSs, reviews the current understanding and state of advancement in designing S-CPSs for run-time, explores the paradox, and issues of designing for run-time adaptation, and synthesizes some general principles that can be taken into consideration when addressing the challenges, first of all, in the context of advanced manufacturing systems. This paper introduces four levels of CPSs according to reasoning capabilities and adaptation freedom of systems, and recognizes the paradox that a system with a higher level of freedom requires a higher level of self-control and resource management according to the overall objective of operation. Specific and common design principles are presented and critically assessed for each advancement level of CPSs. The principles synthesized by the authors provide only a partial fulfillment of the generic need. The planned future research addresses these issues and proposes (largely implementation and application independent) genuine principles for system developers. [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]

Collaboration is complex. To solve a problem occurring in collaboration, using computers, we must first define and specify the problem. This paper presents a challenging problem in collaboration, called group role assignment with cooperation and conflict factors (GRACCFs). This problem’s solution aims at creating a high-performance group by role assignment with consideration of cooperation and conflicts between agents. The contribution of this paper is the formalization of the proposed problem, a confirmation of the complexity of the problem, a practical solution that uses the IBM ILOG CPLEX optimization package (ILOG), a verification of the benefits of solving the GRACCF problem by simulations and a practical way of collecting the required factors to support decision makers in solving such a problem within a real-world scenario. Experiments are used to verify the efficiency of the proposed ILOG solution. [ABSTRACT FROM AUTHOR]

Contribution: This paper illustrates how to design and implement curricula in terms of the combined use of flipped learning and inquiry-based learning in an engineering course. Background: Elementary courses in engineering schools are conventional and foundational, and involve a considerable amount of knowledge. Throughout such courses, students are also expected to develop insight, which cannot be obtained by only listening to instructors. Having relevant discussions is also difficult for most instructors. Intended Outcomes: The combined use of flipped learning and inquiry-based learning would be beneficial to broaden student achievement. Application Design: Based on an epistemological approach about knowledge and knowing, this paper applies the combined use of flipped learning and inquiry-based learning to enhance student knowledge and advance ways of thinking on a System Modeling and Control course. Findings: The extended learning time and the collective responsibility for learning are discussed as critical issues in applying the combined use of flipped learning and inquiry-based learning in an engineering school. [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]

This paper presents a multi-stage series model predictive control (MS-MPC) for PMSM drives in order to further improve the control performance of MPC. Firstly, the basic principle of conventional MPC is introduced. Then, the multi-stage series MPC is proposed in this paper, in which the cost functions of different prediction instant are adopted to form series control structure. In this method, the current prediction trajectory of one voltage vector is extrapolated to multiple control periods, and the control performances of every voltage vector during multiple control periods are evaluated by multi-stage series cost functions. Additionally, the implementation process of the proposed method is described. Finally, the comparison experiments between the conventional MPC and the proposed method show that the proposed method can effectively reduce the switching frequency under the same control frequency. In addition, the improvement of current control performance can be achieved by the proposed method under the condition of the same switching frequency. [ABSTRACT FROM AUTHOR]

This paper deals with the speed synchronization control of a connected vehicle subject to a replay attack. A large number of replay attack signals are injected into controller area network (CAN) through external network, which greatly reduces the real-time control performance of a connected integrated motor-transmission (IMT) system. In order to ensure the performance of an IMT speed tracking system under large random message delays, a robust reset controller combined with a delay-robust speed synchronization controller satisfying energy-to-peak performance is designed in this paper. The uncertain impact caused by a replay attack is described by large random network delays which are modeled by polytopic inclusion. Then, a dynamic output-feedback controller considering the uncertainty caused by attack-delays is proposed for online speed tracking. Moreover, a robust reset controller is designed to obtain comparatively better transient response in the case of large attack-delays. In this control strategy, once the reset condition is triggered, the after-reset value calculated by linear matrix inequalities (LMIs) would replace the dynamic state vector. Finally, the effectiveness of the proposed controller is verified by comparing it with model predictive control (MPC), existing PD control considering delays and energy-to-peak robust control in terms of performance. [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]

A large class of three-phase electrical power systems possess symmetry conditions that make it possible to describe their behavior using single-input single-output transfer functions with complex coefficients. In such cases, an extended root locus method can be used to design control laws, even though the actual systems are multi-input multi-output. In this paper, the symmetric conditions for a large class of power systems are analyzed. Then, the root locus method is revisited for systems with complex coeffcients and used for the analysis and control design of power systems. To demonstrate the benefits of the approach, this paper includes two examples: 1) a doubly fed induction machine and 2) a three-phase LCL inverter. [ABSTRACT FROM PUBLISHER]