Simulation Platform Research Articles

An adaptive PID controller for path following of autonomous underwater vehicle based on Soft Actor–Critic

In recent years, autonomous underwater vehicles (AUVs) have witnessed rapid development, and its motion control has garnered increasing attention. Meanwhile, in industries, PID controllers are still wildly employed by most AUVs due to their simplicity, ease of deployment, and a certain level of robustness. However, they are facing significant challenges in parameter tuning, especially when dealing with various control missions and changing external environments. Deep reinforcement learning, as a data-driven approach, has gradually made its impact in AUV control. However, its lack of interpretability has hindered its deployment in relevant experiments. To address these issues, this paper proposed an adaptive PID controller for path following of AUVs based on the Soft Actor–Critic (SAC). This controller combines the interpretability of PID with the intelligence of reinforcement learning. A simulation platform was established and compared with other typical control methods, demonstrating the superiority of the proposed controller. Finally, the feasibility of the proposed SAC-PID controller was validated by lake trials. The results showed that the SAC-PID controller significantly outperformed the PID and Proximal Policy Optimization (PPO) PID controllers in multiple dimensions, such as control precision and convergence speed.

A hybrid wave vibration energy harvester with electromagnetic double-speed and piezoelectric up-frequency driven by a rotating ball

The energy crisis and environmental pollution have driven the development of ambient energy harvesting technologies, and ocean waves usually contain abundant vibration energy, making the study of wave energy harvesting technology of profound value. This paper proposes a hybrid wave vibration energy harvester with electromagnetic double-speed and piezoelectric up-frequency driven by a rotating ball. For the electromagnetic generator (EMG), the excitation magnet and coil move simultaneously, resulting in double the flux variation rate compared with traditional structures, enhancing the output voltage. For the piezoelectric transducer (PZT), four piezoelectric cantilever beams are magnetically coupled with the EMG, generating power through bistable motion and broadening the working frequency band of the cantilever beam structure. The harvester is modeled and simulated, and its performance is tested on a simulated vibration platform, with simulation and experimental results in good agreement. Under external excitation at 0.8 Hz, the optimal load and maximum power for each EMG are 8.2 Ω and 207.2 mW, respectively, and the optimal load and maximum power for each PZT are 100 kΩ and 1.52 mW, respectively. The harvester can produce a maximum output power of 420.48 mW, demonstrating high efficiency in energy capture under low-frequency and multidirectional wave excitation.

RCEP and China: An Application of GE-PPML Model to Goods, Services, and Value Chains

This study utilizes a flexible estimation and simulation platform based on the GE-PPML model to analyze the trade and welfare implications of the Regional Comprehensive Economic Partnership (RCEP) for member countries, with a particular focus on China. Our findings suggest that RCEP has the potential to yield significant export gains for member economies. Furthermore, by considering heterogeneity in terms of sectors and product usage, our results indicate that RCEP holds significant potential for deepening value chain trade among member countries, particularly in the manufacturing industry. This study underscores the importance and uniqueness of examining the actual impact of RCEP on member countries’ trade and welfare. By providing clearer insights into these impacts, we aim to contribute to a better understanding of the potential benefits and challenges associated with RCEP implementation.

Multi-objective performance analysis of different SCO2 Brayton cycles on hypersonic vehicles

To provide the continuous and stable power supply of hypersonic vehicles, this study investigates four candidate cycles on the basis of three critical parameters. Specifically, the effects of cycle pressure ratio (PR), recompression split ratio (x), and cycle intermediate pressure ratio (RPR) on the regenerative, recompression, precompression, and partial cooling supercritical carbon dioxide (SCO2) Brayton cycles (BCs) are emphasized. The analysis is carried on by using an established thermodynamic simulation platform. Using PR as the working condition parameter, the influence laws of x and RPR on each cycle at common working conditions are given. The Non-dominated Solution Genetic Algorithm-II (NSGA-II) performs multi-objective optimization for different cycle types. The performance of these cycles is then compared under optimal conditions. The results show that the regenerative SCO2 BC could maintain relatively high output power while keep the structure simple, compared with other three cycles. The optimum power generation in the study range and the common operating conditions of regenerative SCO2 BC is 203.49 kW and 154.03 kW, respectively. Therefore, the regenerative SCO2 BC preferably satisfies the requirements of the hypersonic vehicles.

PV based Systems with Advanced Control Strategies for Load Balancing in Multilevel Inverter

In an era driven by sustainable energy solutions, the synergy of photovoltaic (PV) system stands as a beacon of hope for meeting the world's growing energy demands while minimizing environmental impact. This research ventures into the domain of renewable energy integration by seamlessly including a PV system, ingeniously controlled by Chaotic Flower Pollination Optimized Adaptive Neuro Fuzzy Inference System (ANFIS) based MPPT (Maximum Power Point Tracking) controller capable of optimizing the efficiency in the face of ever-changing weather dynamics. The PV system's quest for optimal efficiency receives a substantial boost through the implementation of the High Gain Modified Luo Converter. Designed to achieve an optimal PV output voltage, this converter's prowess finds its true calling in grid applications, where precision and efficiency are paramount. Furthermore, this research extends its purview to incorporate a bidirectional converter linked to an energy storage solution, such as a battery, through a common DC link. The output power is then passed to the Flyback Converter, seamlessly connected to a 31 level Cascaded H Bridge Multi-Level Inverter (31-level CHB MLI) controlled by PI controller. This formidable inverter architecture facilitates the efficient delivery of power to the grid, ensuring a smooth and controlled integration of renewable energy resources. This strategic integration bolsters the system's adaptability, enabling the seamless management of energy flows and grid interactions along with load balancing in MLI. The MATLAB simulation platform is used for confirming the system's overall performance. According to the simulation results, the proposed approach achieves the maximum efficiency with the lowest THD value of 94.5% and 2.5%, respectively.

CrowdBot: An Open-Environment Robot Management System for On-Campus Services

In contemporary campus environments, the provision of timely and efficient services is increasingly challenging due to limitations in accessibility and the complexity and openness of the environment. Existing service robots, while operational, often struggle with adaptability and dynamic task management, leading to inefficiencies. To overcome these limitations, we introduce CrowdBot, a robot management system that enhances service in campus environments. Our system leverages a hierarchical reinforcement learning-based cloud-edge hybrid scheduling framework (REDIS), for efficient online streaming task assignment and dynamic action scheduling. To verify the REDIS framework, we have developed a digital twin simulation platform, which integrates large language models and hot-swapping technology. This facilitates seamless human-robot interaction, efficient task allocation, and cost-effective execution through the reuse of robot equipment. Our comprehensive simulations corroborate the system's remarkable efficacy, demonstrating significant improvements with a 24.46% reduction in task completion times, a 9.37% decrease in travel distances, and up to a 3% savings in power usage. Additionally, the system achieves a 7.95% increase in the number of tasks completed and a 9.49% reduction in response time. Real-world case studies further affirm CrowdBot's capability to adeptly execute tasks and judiciously recycle resources, thereby offering a smart and viable solution for the streamlined management of campus services.

Study of an LLC Converter for Thermoelectric Waste Heat Recovery Integration in Shipboard Microgrids

Static waste heat recovery, by means of thermoelectric generator (TEG) modules, constitutes a fast-growing energy harvesting technology on the way towards greener transportation. Many commercial solutions are already available for small internal combustion engine (ICE) vehicles, whereas further development and cost reductions of TEG devices expand their applicability at higher-power transportation means (i.e., ships and aircrafts). In this light, the integration of waste heat recovery based on TEG modules in a shipboard distribution network is studied in this work. Several voltage step-up techniques are considered, whereas the most suitable ones are assessed via the LTspice simulation platform. The design procedure of the selected LLC resonant converter is presented and analyzed in detail. Furthermore, a flexible control strategy is proposed, capable of either output voltage regulation (constant voltage) or maximum power point tracking (MPPT), according to the application demands. Finally, both simulations and experiments (on a suitable laboratory testbench) are performed. The obtained measurements indicate the high efficiency that can be achieved with the LLC converter for a wide operating area as well as the functionality and adequate performance of the control scheme in both operating conditions.

Stability assessment of inverter‐based renewable energy sources integrated to weak grids

AbstractThe worldwide electricity network is undergoing a crucial transformation, shifting from traditional synchronous generators to inverter‐based renewable energy sources (IRESs). This shift is expected to reduce the grid's available fault level (AFL), potentially impacting grid functionality, particularly during the integration of IRESs into weak grids. This paper examines the challenges associated with weak grids, focusing on the steady‐state and dynamic stability of IRES when integrated into these systems. In the steady‐state analysis, the effects of AFL, injected power volume, and grid characteristics on the steady‐state voltage at the point of interconnection were explored. For dynamic stability, eigenvalue and H2 norm analyses are used for evaluation. Sensitivity analysis is conducted to assess the impact of these factors on the stability of IRESs connected to weak grids. A detailed case study using the IEEE 39 bus test power system is included to demonstrate our findings, where the steady‐state and dynamic stability of IRES connected to the test system are assessed using the proposed methods. The accuracy of these analyses is confirmed by extensive simulation studies on the OPAL‐RT real‐time digital simulator platform.

Electromagnetic scattering and imaging simulation of extremely large-scale sea-ship scene based on GPU parallel technology

Aiming to solve the bottleneck problem of electromagnetic scattering simulation in the scenes of extremely large-scale seas and ships, a high-frequency method by using graphics processing unit (GPU) parallel acceleration technique is proposed. For the implementation of different electromagnetic methods of physical optics (PO), shooting and bouncing ray (SBR) and physical theory of diffraction (PTD), a parallel computing scheme based on the central processing unit (CPU)-GPU parallel computing scheme is realized to balance computing tasks. Finally, a multi-GPU framework is further proposed to solve the computational difficulty caused by the massive number of ray tubes in the ray tracing process. By using the established simulation platform, signals of ships at different seas are simulated and their images are achieved as well. It is shown that the higher sea states degrade the averaged peak signal-to-noise ratio (PSNR) of radar image.

Evaluating polyester resin as a viable substitute for PMMA in computed tomography dosimetry phantoms

The current study aimed to evaluate the suitability of polyester resin as an alternative material to polymethyl methacrylate (PMMA) for computed tomography (CT) dosimetry phantoms using the GEANT4/GATE Monte Carlo simulation platform. Cylindrical phantoms (32 cm diameter) constructed of polyester resin and PMMA were simulated and compared in terms of atomic composition, effective atomic number, electron density, mass density, and photon interaction mechanisms. Weighted CT dose index (CTDIw) values were calculated for each phantom at 80, 110, and 130 kVp tube voltages based on measurements of CTDI100,c and CTDI100,p. Results demonstrated that the physical properties of polyester closely matched those of PMMA, and the polyester phantom displayed equivalent dosimetric behavior to the PMMA phantom at all tube voltages tested. CTDIw values from the polyester phantom were within 1.4 % of the PMMA phantom across all tube voltages. Conversion coefficients were derived to equate polyester CTDIw values to PMMA dose equivalents. This study found that a polyester resin phantom exhibited radiation dosimetry commensurate with the standard PMMA phantom for CT dose assessment. Consequently, polyester resin represents a viable substitute material when PMMA is unavailable for construction of CT dosimetry phantoms.

Compensation characterization of the UPQC system under an improved nonlinear controller based on the MSTOGI-PLL device

To solve the delay problem of a unified power quality conditioner (UPQC) system during the separation of the fundamental positive-order components and to better filter out the DC and harmonic components to realize accurate phase locking, a mixed second- and third-order generalized integrator phase-locked loop (MSTOGI-PLL) has been designed to replace the traditional synchronous reference frame phase-locked loop (SRF-PLL). Under the premise of adopting the new phase-locking device of MSTOGI-PLL, the active disturbance rejection control (ADRC) controller or the super-twisting algorithm (STA) sliding mode controller is used in the DC voltage control module instead of the traditional PI controller, and the suitability of the two nonlinear controllers with the MSTOGI-PLL device is investigated. First, the new MSTOGI-PLL device is designed, and the new phase-locking method is applied to make the UPQC realize accurate phase locking under the non-ideal situation of the grid voltage containing unbalance, DC component, harmonics, and so on. Based on the above foundation, the ADRC or STA controller is independently adopted to replace the PI controller to construct the UPQC system with the ADRC + MSTOGI phase-locking device and the second-order STA + MSTOGI phase-locking device. Finally, a simulation comparison is carried out in a Simulink simulation platform regarding the UPQC system under different phase-locking devices, and the simulation results demonstrate that MSTOGI-PLL can successfully filter out the DC component and resolve the phase-locking process delay issue. Additionally, the UPQC system with ADRC + MSTOGI-PLL exhibits superior immunity and response speed to the PI controller and the second-order STA controller.

Validation of an Ultrasonic Sensor Model for Application in a Simulation Platform

Validation of an Ultrasonic Sensor Model for Application in a Simulation Platform

Integrated simulation and control environment for the development and safe start-up of cable driven parallel robots

ABSTRACT This article presents a new environment designed to facilitate the conceptualization and automation of CDPRs (Cable Driven Parallel Robots). Utilizing a platform for robotic simulation, an industrial controller, and a data gateway to communicate both systems, it is possible to emulate CDPR motion in early design, development, and start-up phases. Thus, this simulation environment allows to test how the robot will behave in advance in order to obtain a safer and more reliable first operation with the real robot. An spatially under-constrained CDPR with four cables was used to validate the capabilities of the proposed integrated environment, comparing its performance against an industry-standard hardware prototype. Both the simulation model and the real prototype performed the same trajectory in order to assess a time delay and position errors between them. Evaluation results revealed that the simulation accurately replicated the performance of its industrial counterpart, with a peak divergence of 0.27% in the position of the robot under various speed scenarios. This occurs even when accounting for latency arising from data exchange connecting the industrial control unit to the simulation. The results have shown that the environment is suitable for trajectory control of new CDPR architectures under different dynamic conditions.

Modeling, Analysis and Evaluation of a Novel Compact 6-DoF 3-RRRS Needle Biopsy Robot

Robot-assisted surgical systems have been widely applied for minimally invasive needle biopsies thanks to their excellent accuracy and superior stability compared to manual surgical operations, which lead to possible fatigue and misoperation due to long procedures. Current needle biopsy robots are normally customed designed for specific application scenarios, and only position-level kinematics are derived, preventing advanced speed control or singularity analysis. As a step forward, this paper aims to design a universal needle biopsy robot platform which features 6 DoF 3-RRRS (Revolute–Revolute–Revolute–Spherical) parallel structure. The analytical solutions to its nonlinear kinematic problems, including forward kinematics, inverse kinematics, and differential kinematics are derived, allowing fast and accurate feedback control calculations. A multibody simulation platform and a first-generation prototype are established next to provide comprehensive verifications for the derived robotic model. Finally, simulated puncture experiments are carried out to illustrate the effectiveness of the proposed method.

New Estimates of Nitrogen Fixation on Early Earth.

Fixed nitrogen species generated by the early Earth's atmosphere are thought to be critical to the emergence of life and the sustenance of early metabolisms. A previous study estimated nitrogen fixation in the Hadean Earth's N2/CO2-dominated atmosphere; however, that previous study only considered a limited chemical network that produces NOx species (i.e., no HCN formation) via the thermochemical dissociation of N2 and CO2 in lightning flashes, followed by photochemistry. Here, we present an updated model of nitrogen fixation on Hadean Earth. We use the Chemical Equilibrium with Applications (CEA) thermochemical model to estimate lightning-induced NO and HCN formation and an updated version of KINETICS, the 1-D Caltech/JPL photochemical model, to assess the photochemical production of fixed nitrogen species that rain out into the Earth's early ocean. Our updated photochemical model contains hydrocarbon and nitrile chemistry, and we use a Geant4 simulation platform to consider nitrogen fixation stimulated by solar energetic particle deposition throughout the atmosphere. We study the impact of a novel reaction pathway for generating HCN via HCN2, inspired by the experimental results which suggest that reactions with CH radicals (from CH4 photolysis) may facilitate the incorporation of N into the molecular structure of aerosols. When the HCN2 reactions are added, we find that the HCN rainout rate rises by a factor of five in our 1-bar case and is about the same in our 2- and 12-bar cases. Finally, we estimate the equilibrium concentration of fixed nitrogen species under a kinetic steady state in the Hadean ocean, considering loss by hydrothermal vent circulation, photoreduction, and hydrolysis. These results inform our understanding of environments that may have been relevant to the formation of life on Earth, as well as processes that could lead to the emergence of life elsewhere in the universe.

Screen-based Simulation Supporting Problem-based Learning to Improve Football Tactics

Introduction This study measured the effect of Problem-Based Learning (PBL) with Screen-Based Simulation (SBS) on undergraduate football tactical decision-making, tactical skills, and student engagement. The Screen-Based Simulation showed tactical scenarios in real games to learners, promoting the identification and analysis of tactical problems in learning. Problem-Based Learning enabled learners to get a deeper understanding of the tactical problems and discuss them effectively. Materials and Methods Two simulation tools were used in this study. The first one, ‘football match basic offensive and defensive tactical simulation experiment platform,’ is scaffolding in football tactics teaching. Students could use the simulation platform to find tactical problems and learn tactics. The second one, TacticUP, is a screen-based simulation tool to test football tactical decision-making. We used second-year students majoring in physical education at a Chinese university. Seventy-nine students were divided into an experimental group using PBL-SBS and a group taught traditionally. Before the experiment, the tactical decision-making of both groups was assessed in a pretest, and at the end of the six-week experiment, the students were tested again. They also completed a questionnaire on tactical skills and student engagement. Results There was no significant difference between the pretest scores on tactical decision-making between the two groups (independent-sample t-test, sig = 0.997 > 0.05). However, after the experiment, significantly better improvement was observed in tactical decision-making in the experimental group. The pretest mean score (59) was significantly lower than the post-test one (67) on a scale of 100 (paired sample t-test, sig <0.01). ANOVA showed that the experimental group performed better in all aspects, namely tactical decision-making, tactical skill, and student engagement, than the traditional group (Sig values were all less than 0.01). Conclusion Compared with traditional teaching, PPL-SBS students performed better in tactical decision-making, tactical skills, and student engagement than students in the traditional teaching group.

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control functions, and its long-term development, calls for a different approach than the design and short-term deployment of individual controllers. It requires, in the first place, a flexible implementation strategy and system architecture that allows system re-configuration and optimization throughout its development. Secondly, a model-based system engineering approach is carried out, for the complete PCS development, i.e. both its design and deployment. It requires clear definitions for both the PCS role and its functionality, as well as definitions of the design and deployment process itself. The design and deployment process is shown to allow tracing the relationships of the many individual design and deployment aspects, such as system requirements, assumed operation use-cases and response models, and eventually verification and functional validation of the system design. The functional validation will make use of a dedicated PCS simulation platform that includes the description of the control function design as well as plant, actuator and sensor models that enable the simulation of these functions. By establishing a clear understanding of the interconnected steps involved in designing, implementing, commissioning, and operating the system, a more systematic approach is achieved. This ensures the completion of a comprehensive design that can be deployed efficiently, hence preventing the loss of precious operational time needed to debug and retune control functions and more importantly avoiding tokamak discharge disruptions.

Atomic Quantum Technologies for Quantum Matter and Fundamental Physics Applications

Physics is living an era of unprecedented cross-fertilization among the different areas of science. In this perspective review, we discuss the manifold impact that state-of-the-art cold and ultracold-atomic platforms can have in fundamental and applied science through the development of platforms for quantum simulation, computation, metrology and sensing. We illustrate how the engineering of table-top experiments with atom technologies is engendering applications to understand problems in condensed matter and fundamental physics, cosmology and astrophysics, unveil foundational aspects of quantum mechanics, and advance quantum chemistry and the emerging field of quantum biology. In this journey, we take the perspective of two main approaches, i.e., creating quantum analogues and building quantum simulators, highlighting that independently of the ultimate goal of a universal quantum computer to be met, the remarkable transformative effects of these achievements remain unchanged. We wish to convey three main messages. First, this atom-based quantum technology enterprise is signing a new era in the way quantum technologies are used for fundamental science, even beyond the advancement of knowledge, which is characterised by truly cross-disciplinary research, extended interplay between theoretical and experimental thinking, and intersectoral approach. Second, quantum many-body physics is unavoidably taking center stage in frontier’s science. Third, quantum science and technology progress will have capillary impact on society, meaning this effect is not confined to isolated or highly specialized areas of knowledge, but is expected to reach and have a pervasive influence on a broad range of society aspects: while this happens, the adoption of a responsible research and innovation approach to quantum technologies is mandatory, to accompany citizens in building awareness and future scaffolding. Following on all the above reflections, this perspective review is thus aimed at scientists active or interested in interdisciplinary research, providing the reader with an overview of the current status of these wide fields of research where cold and ultracold-atomic platforms play a vital role in their description and simulation.

End-to-End lightweight Transformer-Based neural network for grasp detection towards fruit robotic handling

Robotic picking and placing are common operations for fruits and vegetables in grading, sorting or packaging systems. However, due to the diverse shapes and irregular surfaces of fruits and vegetables, improper handling during the picking process can result in detachment or damage. To ensure the correct grasping positions, it is necessary to design targeted neural network algorithms for achieving intelligent sorting. Therefore, this study focuses on 20 common fruit and vegetable agricultural products to develop a deep learning-based grasping detection algorithm model. By combining local features from convolutional neural networks with global features from Transformers, a lightweight end-to-end fruit and vegetable grasping detection network, MDETR, is constructed. Experimental results demonstrate that the MDETR algorithm not only achieves high accuracy in fruit and vegetable grasping detection but also improves the speed of pose detection. The average time required for detecting a single image is approximately 29.6 ms, meeting real-time requirements. The algorithm achieves a pose detection accuracy rate of 96 %, enabling precise detection and positioning of fruit and vegetable poses and achieving fast and accurate picking and placing. Additionally, a Pybullet simulation platform is developed for conducting grasping experiments, where the MDETR model achieves a grasping success rate of 88.9 %. This validates the robustness and generalization capabilities of the proposed detection algorithm model, designed specifically for fruit and vegetable grasping tasks.

A new target accessibility control method based on SMC

ABSTRACT In this paper, a sliding mode control method based on improved intelligent decision (IID-SMC) algorithm is proposed to improve the accuracy of the puncture needle to reach the target and reduce the time required in the puncture process. First of all, around the straight line of the puncture needle and the direction of the rotation of the needle, the independent control law is designed to realise the mutual decoupling and reduce the mutual interference. Secondly, the error range of this method in the process of puncture is analysed, and the upper bound of the error in the process of puncture is given. Finally, the method is verified by simulation and experiment platform.