Search Results (612)

As stability is one of the most important property of any system, studying it is paramount when performing a power-hardware-in-the-loop simulation in an experimental setup. To guarantee the proper operation of such a system, a thorough understanding of the critical issues regarding the dynamics of the power amplifier, the real-time simulated system and the hardware under test is required. Thus, this paper provides a detailed analysis of the correct design of the real-time simulation modeling for the secure and reliable execution of power-hardware-in-the-loop simulations involving power electronic devices in an experimental setup. Specifically, the stability region of a power-hardware-in-the-loop simulation in an experimental AC microgrid setup involving two parallel three-phase grid-following inverters with LCL filters is studied. Through experimental testing, the stability boundaries of the power-hardware-in-the-loop simulation in the experimental setup is determined, demonstrating a direct relationship between the short-circuit ratio of the utility grid and the cutoff frequency of the feedback current filter. Experimental evidence confirms the capability of the AC microgrid setup to achieve smooth transitions between diverse operating conditions and determine stability boundaries with parameter variations. This research provides practical design guidelines for modeling and the real-time simulation to ensure stability in the power-hardware-in-the-loop simulations in experimental setups involving actual grid-following inverters, specifically using an Opal-RT platform with a voltage-source ideal transformer model and parameter variations in the short-circuit ratio from 2 to 20, the line impedance ratio $X/R$ from 7 to 10, and the feedback-current-filter cutoff frequency from 100 to 1000 kHz. Full article

This article presents a compact tip-tilting platform designed for hardware-in-the-loop emulation of spacecraft relative dynamics and a physical setup for testing tethered systems. The architecture consists of a granite slab supported by a universal joint and two linear actuators to control its orientation. This configuration allows a Floating Spacecraft Simulator to move on the surface in a quasi-frictionless environment under the effect of gravitational acceleration. The architecture includes a dedicated setup to emulate tethered satellite dynamics, providing continuous feedback on the tension along the tether through a mono-axial load cell. By adopting the Buckingham “$\pi$” theorem, the dynamic similarity is introduced for the ground-based experiment to reproduce the orbital dynamics. Proof-of-concept results demonstrate the testbed’s capability to accurately reproduce the Hill–Clohessy–Wiltshire equations. Moreover, the results of the deployed tethered system dynamics are presented. This paper also details the system architecture of the testbed and the methodologies employed during the experimental campaign. Full article

With the increasing demands of the grid on power electronic converters, active neutral-point-clamped (ANPC) converters have been widely adopted due to their flexible modulation strategies and wide-range power regulation capabilities. To address grid-integration testing requirements for ANPC converters, this paper comparatively studies three electromagnetic transient (EMT) modeling approaches: switch-state prediction method (SPM), associated discrete circuit (ADC), and time-averaged method (TAM). Steady-state and transient simulations reveal that the SPM model achieves the highest accuracy (error ≤ 0.018%), while the TAM-based switching function model optimizes the efficiency–accuracy trade-off with 6.4× speedup versus traditional methods and acceptable error (≤2.62%). Consequently, the TAM model is implemented in a real-time hardware-in-the-loop (HIL) platform. Validation under symmetrical/asymmetrical grid faults confirms both the model’s efficacy and the controller’s robust fault ride-through capability. Full article

This paper presents a hardware-in-the-loop (HIL) simulation case study on the application of High-Order Sliding Mode Control (HOSMC) to a flexible-link robotic arm. The developed HIL platform combines physical hardware components with a simulated plant model, enabling real-time testing of control algorithms under realistic operating conditions without requiring a full-scale prototype. HOSMC, an advanced nonlinear control strategy, mitigates the chattering effects inherent in conventional sliding mode control by driving the system to a reduced-order sliding manifold within a finite time, resulting in smoother actuator commands and reduced mechanical stress. Flexible-link arms, while lightweight and energy-efficient, are inherently nonlinear and prone to vibration, posing significant control challenges. In this case study, the experimental HIL environment is used to evaluate HOSMC performance, demonstrating improved trajectory tracking, reduced overshoot, and minimized steady-state error. The results confirm that HIL simulation offers an effective bridge between theoretical control design and practical implementation for advanced robotic systems. Full article

The growing integration of renewable-based distributed energy resources within local energy communities is significantly reshaping the operational dynamics of medium voltage distribution networks, particularly affecting their reliability and protection schemes. This work investigates the technical impacts of the high penetration of distributed generation within sustainable local energy communities on the effectiveness of fault detection, location, isolation, and service restoration processes, from the point of view of Distribution System Operators. From a supply continuity perspective, the methodology of the present work comprises a comprehensive, quantitative, system-level assessment based on probabilistic, scenario-based simulations of fault events on a CIGRE benchmark distribution network. The models incorporate component fault rates and repair times derived from EPRI databases and compute standard IEEE indices over a one-year horizon, considering manual, hybrid, and fully automated operation scenarios. The results highlight the significant potential of automation to enhance supply continuity. However, the qualitative assessment carried out through laboratory-based Hardware-in-the-Loop tests reveals critical vulnerabilities in fault-detection devices, particularly when inverter-based distributed generation units contribute to fault currents. Consequently, quantitative evaluations based on a sensitivity analysis incorporating these findings, varying the reliability of fault-detection systems, indicate that the reliability improvements expected from increased automation levels are significantly deteriorated if protection malfunctions occur due to fault current contributions from distributed generation. These results underscore the need for the evolution of protection technologies in medium voltage networks to ensure reliability under future scenarios characterised by high shares of distributed energy resources and local energy communities. Full article

Microgrid systems play a vital role in managing distributed energy resources like solar, wind, batteries, and supercapacitors. However, maintaining stable AC/DC bus voltages and minimizing grid reliance under dynamic conditions is challenging. Traditional control methods such as Sliding Mode Controllers (SMCs) suffer from issues like chattering and slow convergence, reducing practical effectiveness. This paper proposes a hybrid AC/DC microgrid that operates in both grid-connected and islanded modes while ensuring voltage stability and efficient energy use. A Conditional-Based Super-Twisting Sliding Mode Controller (CBSTSMC) is employed to address the limitations of conventional SMCs. The CBSTSMC enhances system performance by reducing chattering, improving convergence speed, and offering better tracking and disturbance rejection. To further refine controller performance, an Improved Grey Wolf Optimization (IGWO) algorithm is used for gain tuning, resulting in enhanced system robustness and precision. An Energy Management System (EMS) is integrated to intelligently regulate power flow based on renewable generation and storage availability. The proposed system is tested in real time using a Texas Instruments Delfino C2000 microcontroller through a Controller-in-the-Loop (CIL) setup. The simulation and hardware results confirm the system’s ability to maintain stability and reliability under diverse operating scenarios, proving its suitability for future smart grid applications. Full article

Brushless DC (BLDC) motors are commonly used in electric vehicles (EVs) because of their efficiency, small size and great torque-speed performance. These motors have a few benefits such as low maintenance, increased reliability and power density. Nevertheless, BLDC motors are highly nonlinear and their dynamics are very complicated, in particular, under changing load and supply conditions. The above features require the design of strong and adaptable control methods that can ensure performance over a broad spectrum of disturbances and uncertainties. In order to overcome these issues, this paper uses a Fractional-Order Proportional-Integral-Derivative (FOPID) controller that offers better control precision, better frequency response, and an extra degree of freedom in tuning by using non-integer order terms. Although it has the benefits, there are three primary drawbacks: (i) it is not real-time adaptable, (ii) it is hard to choose appropriate initial gain values, and (iii) it is sensitive to big disturbances and parameter changes. A new control framework is suggested to address these problems. First, a Reinforcement Learning (RL) approach based on Deep Deterministic Policy Gradient (DDPG) is presented to optimize the FOPID gains online so that the controller can adjust itself continuously to the variations in the system. Second, Snake Optimization (SO) algorithm is used in fine-tuning of the FOPID parameters at the initial stages to guarantee stable convergence. Lastly, cascade control structure is adopted, where FOPID controllers are used in the inner (current) and outer (speed) loops. This construction adds robustness to the system as a whole and minimizes the effect of disturbances on the performance. In addition, the cascade design also allows more coordinated and smooth control actions thus reducing stress on the power electronic switches, which reduces switching losses and the overall efficiency of the drive system. The suggested RL-enhanced cascade FOPID controller is verified by Hardware-in-the-Loop (HIL) testing, which shows better performance in the aspects of speed regulation, robustness, and adaptability to realistic conditions of operation in EV applications. Full article

This paper addresses a common challenge in space systems: how to effectively manage multiple actuators under demanding mission conditions. We introduce a flexible, optimization-based algorithm designed to dispatch control commands among a set of available actuators while focusing on minimizing resource usage, such as power and fuel. The method guarantees feasible solutions even in the presence of actuator failures, making it highly suitable for space applications. To illustrate its versatility, we show how the algorithm can be tailored to different mission scenarios with minimal effort. Several benchmark problems were implemented and tested on space-graded hardware for processor-in-the-loop verification. For this purpose, a customized solver was developed, ensuring high numerical efficiency. This paper highlights key results that demonstrate the algorithm’s practical value and mission readiness. Full article

Multi-camera systems (MCSs) are pivotal in aviation surveillance and autonomous navigation due to their wide coverage and high-resolution sensing. However, challenges such as complex setup, time-consuming data acquisition, and costly testing hinder research progress. To address these, we introduce MCS-Sim, a photo-realistic MCSsimulator for UAV visual perception research. MCS-Sim integrates vision sensor configurations, vehicle dynamics, and dynamic scenes, enabling rapid virtual prototyping and multi-task dataset generation. It supports dense flow estimation, 3D reconstruction, visual simultaneous localization and mapping, object detection, and tracking. With a hardware-in-loop interface, MCS-Sim facilitates closed-loop simulation for system validation. Experiments demonstrate its effectiveness in synthetic dataset generation, visual perception algorithm testing, and closed-loop simulation. Here we show that MCS-Sim significantly advances multi-camera UAV visual perception research, offering a versatile platform for future innovations. Full article

To address the poor trajectory tracking of mining trucks in narrow, high-curvature paths, this study explores the impact of four-wheel steering (4WS) and direct yaw moment control (DYC) on vehicle stability. A validated two-degree-of-freedom 4WS vehicle model was developed. A fuzzy logic controller with dual inputs (yaw rate and yaw angular acceleration) and a single output (compensatory yaw moment) was designed, alongside an optimal torque distribution controller based on tire friction circle theory to allocate the resultant yaw moment. A co-simulation platform integrating TruckSim and MATLAB/Simulink was established, and experiments were conducted under steady-state and double-lane-change conditions. Comparative analysis with traditional front-wheel steering and alternative control methods reveals that the 4WS mining truck with fuzzy-controlled optimal torque distribution achieves a reduced turning radius, enhancing maneuverability and stability. Hardware-in-the-loop (HIL) testing further validates the controller’s effectiveness in real-time applications. Full article

Wideband oscillation events, with frequencies ranging from several hertz to several kilohertz, have been frequently reported in modern power systems, posing significant challenges to grid stability and sustainability. In response, technologies for oscillation monitoring and analysis have received increasing attention. However, most existing technologies still rely primarily on traditional wide-area measurement systems, which struggle to meet the requirements for wideband oscillation monitoring. This paper first presents a comprehensive review of recent wideband oscillation events reported worldwide, highlighting their causes and adverse impacts on equipment security and system stability. Subsequently, a novel framework for a wideband dynamic monitoring and control system (WDMCS) is proposed, along with detailed descriptions of its principal components and key functions related to wideband oscillations. Finally, a demonstration of WDMCS has been developed, and its effectiveness has been validated through tests conducted on a hardware-in-the-loop platform. The potential and challenges of the proposed system in various domains of power system stability assessment and control are also discussed. Full article

Power converters play an important role in incorporating renewable energy sources into power systems. Among different converter designs, Buck and Boost converters are popular, as they use fewer components and deliver cost savings and high efficiency. However, Boost converters are known as non–minimum phase systems, imposing harder constraints for designing a robust converter. Developing an efficient controller for these topologies can be difficult since they exhibit nonlinearity and distortion in high frequency modes. The Lyapunov-based Adaptive Backstepping Control (ABSC) technology is used to regulate suitable outputs for these structures. This approach is an updated version of the technique that uses the stability Lyapunov function to produce increased stability and resistance to fluctuations in real-world circumstances. However, in real-time situations, disturbances with larger ranges such as supply voltage changes, parameter variations, and noise may have a negative impact on the operation of this strategy. To increase the controller’s flexibility under more difficult working settings, the most appropriate first gains must be established. To solve these concerns, the ABSC’s performance is optimized using the Reinforcement Learning (RL) adaptive technique. RL has several advantages, including lower susceptibility to error, more trustworthy findings obtained from data gathering from the environment, perfect model behavior within a certain context, and better frequency matching in real-time applications. Random exploration, on the other hand, can have disastrous effects and produce unexpected results in real-world situations. As a result, we choose the Deep Deterministic Policy Gradient (DDPG) approach, which uses a deterministic action function rather than a stochastic one. Its key advantages include effective handling of continuous action spaces, improved sample efficiency through off-policy learning, and faster convergence via its actor–critic architecture that balances value estimation and policy optimization. Furthermore, this technique uses the Grey Wolf Optimization (GWO) algorithm to improve the initial set of gains, resulting in more reliable outcomes and quicker dynamics. The GWO technique is notable for its disciplined and nature-inspired approach, which leads to faster decision-making and greater accuracy than other optimization methods. This method considers the system as a black box without its exact mathematical modeling, leading to lower complexity and computational burden. The effectiveness of this strategy is tested in both modeling and experimental scenarios utilizing the Hardware-In-Loop (HIL) framework, with considerable results and decreased error sensitivity. Full article

To address the challenges of high fuel consumption and emissions in traditional diesel-powered inland law enforcement vessels, this study proposes a methanol–electric hybrid propulsion system retrofitted with a novel energy management strategy (EMS) based on the integration of Dynamic Programming (DP) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DP-ANFIS algorithm combines the global optimization capability of DP with the real-time adaptability of ANFIS to achieve efficient power distribution. A high-fidelity simulation model of the hybrid system was developed using methanol engine bench test data and integrated with models of other powertrain components. The DP algorithm was used offline to generate an optimal control sequence, which was then learned online by ANFIS to enable real-time energy allocation. Simulation results demonstrate that the DP-ANFIS strategy reduces total energy consumption by 78.53%, increases battery state of charge (SOC) by 3.24%, decreases methanol consumption by 64.95%, and significantly reduces emissions of CO, HC, NOx, and CO₂ compared to a rule-based strategy. Hardware-in-the-loop tests confirm the practical feasibility of the proposed approach, offering a promising solution for intelligent energy management in marine hybrid propulsion systems. Full article

Among other uses, DC-DC converters are employed in the auxiliary power modules (APMs) of electric vehicles (EVs), connecting the high-voltage traction battery to the low-voltage auxiliary system (AS). Traditionally, the APM is an isolated two-port, two-level (2L) DC-DC converter, and the auxiliary loads are fed at a fixed voltage level, e.g., 12 V in passenger cars. Dual-active-bridge (DAB) converters are commonly used for this application, as they provide galvanic isolation, high power density and efficiency, and bidirectional power flow capability. However, the auxiliary loads do not present a uniform optimum supply voltage, hindering overall efficiency. Thus, a more flexible approach, providing multiple supply voltages, would be more suitable for this application. Multiport DC-DC converters capable of feeding auxiliary loads at different voltage levels are a promising alternative. Multilevel neutral-point-clamped (NPC) DAB converters offer several advantages compared to conventional two-level (2L) ones, such as greater efficiency, reduced voltage stress, and enhanced scalability. The series connection of the NPC DC-link capacitors enables a multiport configuration without additional conversion stages. Moreover, the modular nature of the ML NPC DAB converter enables scalability while using semiconductors with the same voltage rating and without requiring additional passive components, thereby enhancing the converter’s power density and efficiency. This paper proposes a modulation strategy and decoupled closed-loop control strategy for the generalized multiport 2L-NL NPC DAB converter interfacing the EV traction battery with the AS, and its performance is validated through hardware-in-the-loop testing and simulations. The proposed modulation strategy minimizes conduction losses in the converter, and the control strategy effectively regulates the LV battery modules’ states of charge (SoC) by varying the required SoC and the power sunk by the LV loads, with the system stabilizing in less than 0.5 s in both scenarios. Full article

To enhance the speed regulation accuracy and robustness of permanent magnet synchronous motor (PMSM) drives under complex operating conditions, this paper proposes a dual-loop active disturbance rejection control strategy optimized by an opposition-based learning hybrid optimization algorithm (DLADRC-OBLHOA). First, the vector control system and ADRC model of the PMSM are established. Then, a nonlinear function, ifal, is introduced to improve the performance of the speed-loop ADRC. Meanwhile, an active disturbance rejection controller is also introduced into the current loop to suppress current disturbances. To address the challenge of tuning multiple ADRC parameters, an opposition-based learning hybrid optimization algorithm (OBLHOA) is developed. This algorithm integrates chaotic mapping for population initialization and employs opposition-based learning to enhance global search capability. The proposed OBLHOA is utilized to optimize the speed-loop ADRC parameters, thereby achieving high-precision speed control of the PMSM system. Its optimization performance is validated on 12 benchmark functions from the IEEE CEC2022 test suite, demonstrating superior convergence speed and solution accuracy compared to conventional heuristic algorithms. The proposed strategy achieves superior speed regulation accuracy and reliability under complex operating conditions when deployed on high-performance processors, but its effectiveness may diminish on resource-limited hardware. Moreover, simulation results show that the DLADRC-OBLHOA control strategy outperforms PI control, traditional ADRC, and ADRC-$ifal$ in terms of tracking accuracy and disturbance rejection capability. Full article