Semi-physical Simulation Platform Research Articles

Model Predictive Control for Cascaded H-Bridge PV Inverter with Capacitor Voltage Balance

We designed an improved direct-current capacitor voltage balancing control model predictive control (MPC)for single-phase cascaded H-bridge multilevel photovoltaic (PV) inverters. Compared with conventional voltage balancing control methods, the method proposed could make the PV strings of each submodule operate at their maximum power point by independent capacitor voltage control. Besides, the predicted and reference value of the grid-connected current was obtained according to the maximum power output of the maximum power point tracking. A cost function was constructed to achieve the high-precision grid-connected control of the CHB inverter. Finally, the effectiveness of the proposed control method was verified through a semi-physical simulation platform with three submodules.

Research on the mechanism and transmission path of the oscillation in DFIG-connected flexible DC transmission system

Concerning the oscillations in DFIG (doubly-fed induction generator)-connected flexible DC transmission system caused by large disturbances, an analysis method based on subsystem partitioning and dynamic energy modeling is put forward. Firstly, the complex high-order system is partitioned into several low-order subsystems, and the dynamic energy model of each subsystem is built using the first integration method. Then, by analyzing the directions and variation patterns of the interaction energy flows between different subsystems in the oscillation process, the redistribution of the primary flow paths of the system’s oscillation energy after large disturbances occur is determined. And then, an oscillation tracing method based on the response characteristics of the oscillation energy links of the subsystems is proposed. In the oscillation process, the interaction energy links between different subsystems are categorized into 'oscillation gaining links', 'oscillation maintaining links' and 'oscillation damping links', according to the contribution of each interaction energy link to the system’s oscillation energy. By analyzing the ‘oscillation gaining links’ corresponding to the dominant interaction energy links of different subsystems, the transmission paths by which the dominant oscillation energy links keeps gaining can be obtained, and the energy source that induces oscillation can be located. Finally, hardware-in-loop tests are conducted on the RTLAB semi-physical simulation platform, the results of which verify the effectiveness of the proposed method. This research paper can provide theoretical support for suppressing the oscillation by adding compensation branches between the subsystems (i.e. damping control strategies based on supplementary compensation branches).

Control Optimization Method for Ship Direct Current Microgrid Based on Impedance Reshaping

In response to the constant power negative impedance characteristics on the load side of a ship DC microgrid, leading to voltage oscillation issues in the DC bus, this paper proposes a control optimization method based on impedance reshaping using bus voltage feedback. First, a simplified small-signal diagram of a lithium battery energy storage system converter is analyzed. Combining active damping control technology, an impedance regulator is introduced, and its parameters are optimized to effectively reduce the output impedance magnitude on the power source side. Subsequently, a ship DC microgrid simulation model is constructed using MATLAB R2022a/Simulink for validation, and comparative analysis is conducted on the anti-interference ability of the DC bus voltage before and after impedance reshaping. Finally, a model is built on a semi-physical simulation platform to experimentally verify the proposed method. The research results indicate that the proposed control optimization method can effectively increase the system’s stability margin, suppress DC bus oscillations, and enhance the anti-interference ability of the ship DC microgrid’s bus voltage when facing significant power load variations.

Approach and Landing Energy Prediction Based on a Long Short-Term Memory Model

The statistical analysis of civil aircraft accidents reveals that the highest incidence of mishaps occurs during the approach and landing stages. Predominantly, these accidents are marked by abnormal energy states, leading to critical situations like stalling and heavy landings. Therefore, it is of great significance to accurately predict the aircraft energy state in the approach and landing stages to ensure a safe landing. In this study, a deep learning method based on time sequence data for the prediction of the aircraft approach and landing energy states is proposed. Firstly, by conducting an extensive overview of the existing literature, three characteristic parameters of altitude, velocity, and glide angle were selected as the indicators to characterize the energy state. Following this, a semi-physical simulation platform for a certain type of aircraft was developed. The approach and landing experiments were carried out with different throttle sizes and flap deflection under different wind speeds and wind directions. Then, a deep learning prediction model based on Long Short-Term Memory (LSTM) was established based on the experimental data to predict the energy state indicators during the approach and landing phases. Finally, the established LSTM model underwent rigorous training and testing under different strategies, and a comparative analysis was carried out. The results demonstrated that the proposed LSTM model exhibited high accuracy and a strong generalization ability in predicting energy states during the approach and landing phases. These results offer a theoretical basis for designing energy early warning systems and formulating the relevant flight control laws in the approach and landing stages.

Semi-physical simulation and coordinated control of SOFC-PV/T-HP system

Due to the differences in the dynamic characteristics of various energy processes, the operation and control of multi-energy coupled integrated energy systems (IES) pose significant challenges. This paper focuses on the semi-physical simulation and coordinated control of SOFC-PV/T-HP thermoelectric system, which includes solid oxide fuel cells, a solar photovoltaic/thermal panel and a heat pump. In order to enhance the experimental safety and reliability of the research findings, a semi-physical simulation platform is developed by integrating physical equipment and dynamic models. The operational characteristics of the cogeneration system are investigated and controlled using an extended state-space based model predictive algorithm. The experimental results demonstrate that the designed centralized model predictive controller effectively stabilizes the demand power of the battery. The standard deviation of the battery demand power is reduced from 2.39 W to 0.66 W within 500 s, which alleviates the regulation burden of the battery. At the same time, the hot water temperature is also well controlled. The fluctuation of hot water supply temperature does not exceed 0.11℃ after stability. The system can maintain stable operation under external disturbance, and maintain the balance between electricity/heat supply and demand.

Research on the Optimal Output Power of Proton‐Exchange Membrane Fuel Cell Based on Improved Model Predictive Control Strategy

To achieve optimal power output of proton‐exchange membrane fuel cell (PEMFC) under load variation and noise disturbance, this article proposes a recursive subspace model predictive control based on Laguerre function (RSMPCL) strategy. First, a fractional PEMFC identification model is established, and an optimal power setter is introduced to provide an optimal power value corresponding to the current load. Second, during the predictive process, a subspace predictor is updated in real time where a Householder transformer is applied to decrease the computation time of the frequent QR decomposition, and a variable forgetting factor is introduced to enhance the sensitivity and accuracy of predictive control. In the control process, a Laguerre function is employed to transform the problem of computing the input increment at the next step into calculating the coefficients of the input variables. This transformation reduces the computation time of the control quantities. Finally, load and disturbance tests conducted on a dSPACE semiphysical simulation platform indicate that compared with constrained subspace model predictive control, the proposed RSMPCL strategy can help the fuel cells achieve the optimal power point with control accuracy, robustness, and calculation speed.

Reliability Analysis of CTCS-3 Train-Ground Communication System Based on 5G-R

The reliability of Chinese Train Control System Level 3 (CTCS-3) train-ground communication system is of great importance to ensure the safe operation of trains. The fifth Generation Mobile Communication for Railway (5G-R) is prospective for train-ground communication in the future. In this paper, the train-ground communication procedure of 5G-R (e.g., connection reestablishment, handover and train-ground data transmission) is tested by a semi-physical simulation platform. The test results, including the delay of different procedures together with the handover success rate, all can satisfy the quality of service (QoS) requirements. According to the communication procedure, deterministic and stochastic Petri net (DSPN) models of communication links and train-ground communication scenarios are established. Furthermore, the parameters of models are calibrated with the test data and protocol standards. We utilize <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pi$</tex-math></inline-formula> -tool to simulate and analyze the reliability of the train-ground communication system under the interaction of multiple fault factors. The results show that even in the worst handover scenario where the station distance is 1 km and the train speed is 400 km/h, the reliability of the train-ground communication system based on 5G-R can still reach 99.9963 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> . It not only meets the requirements of the train control services for the train-ground communication system, but also is better than the reliability of the GSM-R based communication system.

ROV Sliding Mode Controller Design and Simulation

Underwater robots play a vital role in the exploration and development of marine resources and the inspection and maintenance of offshore platforms. In this paper, the motion control technology of ROV is studied, the kinematics and dynamics of ROV are analyzed, the kinematics and dynamics models of ROV are established, and the degrees of freedom of the models are decouple according to the control requirements. The fluid damping coefficient of ROV was obtained using Fluent software, and an ROV control system based on sliding mode variable structure was designed. The saturation function was introduced into the sliding mode controller to reduce the adverse effects of buffeting. The classical PID controller, fuzzy PID controller, and sliding mode controller designed in this paper were simulated and analyzed by Simulink. A semi-physical simulation platform based on Unity3D was established. It can be seen from the simulation results and the pool experiment results that the performance of the sliding mode controller designed in this paper is better than the classical PID controller and the fuzzy PID controller. The sliding mode control method is used to control the ROV motion, which has better control effect and precision.

Virtual Synchronous Generator (VSG) Control Strategy Based on Improved Damping and Angular Frequency Deviation Feedforward

The output active power of a grid-connected inverter controlled by a traditional virtual synchronous generator (VSG) has the problems of oscillation and steady-state errors. A VSG control strategy based on improved damping and angular frequency deviation feedforward is proposed. This strategy reduces the steady-state error of active power by adding a transient damping link to a traditional VSG damping feedback channel. At the same time, the angular frequency deviation feedforward compensation is used to improve the response speed of the VSG to the active power instruction and reduce the active power overshoot in the dynamic process. First, the VSG active power closed-loop small-signal model is established. The effects of inertia and damping on the dynamic and steady-state performance of the VSG are analyzed by the root locus method. The effect of the proposed control strategy on the system is analyzed by using a closed-loop zero-pole diagram. This strategy improves the precision of active power control the dynamic performance of the system effectively. Finally, the effectiveness and superiority of the proposed control strategy are verified by Matlab/Simulink simulation and semi-physical simulation platform RT-LAB.

Data-driven integral sliding mode control based on disturbance decoupling technology for electric multiple unit

The controller with high reliability and excellent tracking effect is essential for electric multiple unit (EMU) operation system. Nevertheless, similar to many complex systems, the EMU operation process is multivariable, strong coupled, nonlinear and time-varying. In particular, the coupling relationship between the variables in the system seriously affects the performance of the control system. Disturbance decoupling technology is an effective method to address the above problem, so this paper proposes a multi-input-multi-output (MIMO) data-driven integral sliding mode decoupling control (DISMDC) algorithm for the automatic train operation (ATO) system. Based on dynamic linearization (DL) technology, DISMDC equates the EMU operation process with a full format dynamic linearization (FFDL) data model, and uses FFDL data model to design a discrete integral sliding mode control (SMC) law. Meanwhile, the discrete extended state observer (DESO) is introduced to estimate the unmodeled dynamics, unknown disturbances and coupling between variables of the FFDL data model in real time, which further improves the equivalent description of the system and enhances the decoupling effect and control performance. The DISMDC method is tested on a semiphysical simulation platform of CRH380A EMU equipped in the laboratory, and compared with some traditional model-based and data-driven methods. The simulation results show that the control performance of DISMDC algorithm is better than some traditional methods. The velocity tracking error of each power unit of the EMU is within ±0.15 km/h, the control force and acceleration are within [−51 kN, 42 kN] and [−0.8532 m/s2, 0.7810 m/s2], respectively, and the variations are stable. The decoupling control of EMU under disturbance is realized.

Efficient Terrain-Aided Navigation System with Submap-Size Calculation and Embedded System

Abstract Underwater terrain-aided navigation (TAN) holds high potential for long-term underwater accurate navigation of autonomous underwater vehicles. TAN can locate a vehicle by calculating the similarity between an a priori map and a vehicle's real-time observation consisting of a set of bathymetric measurement points. However, the amount of measurement points in the real-time observation affects both positioning accuracy and computational consumption of the TAN system, making it challenging to calculate a suitable size of real-time observation in TAN. With a smooth seabed terrain, a small observation area leads to insufficient topographic features and finally an inaccurate matching result, while a large area with a mount of features results in high computational cost. This paper proposes a method to restrain the size of observation in TAN systems based on terrain entropy and difference of normals. Meanwhile, this paper implements the TAN algorithm into an embedded system architecture used by actual underwater vehicles that are already in service to reduce the power consumption of the TAN system. The effectiveness of the algorithm has been demonstrated through playback experiments based on a semi-physical simulation platform using a PC/104-embedded computer.

A Line Segment Detector for Space Target Images Robust to Complex Illumination

The relative pose estimation of the space target is indispensable for on-orbit autonomous service missions. Line segment detection is an important step in pose estimation. The traditional line segment detectors show impressive performance under sufficient illumination, while it is easy to fail under complex illumination conditions where the illumination is too bright or too dark. We propose a robust line segment detector for space applications considering the complex illumination in space environments. An improved two-dimensional histogram construction strategy is used to optimize the Otsu method to improve the accuracy of anchor map extraction. To further improve line segment detection’s effect, we introduce an aggregation method that uses the angle difference between segments, the distance between endpoints, and the overlap degree of segments to filter the aggregation candidate segments and connect disjoint line segments that probably came from the same segment. We demonstrate the performance of the proposed line segment detector using a variety of images collected on a semiphysical simulation platform. The results show that our method has better performance than traditional line segment detectors including LSD, Linelet, etc., in terms of line detection precision.

Design and Experimental Study of a Novel Semi-Physical Unmanned-Aerial-Vehicle Simulation Platform for Optical-Flow-Based Navigation

In the process of unmanned aerial vehicle (UAV) visual-navigation-algorithm design and accuracy verification, the question of how to develop a high-precision and high-reliability semi-physical simulation platform has become a significant engineering problem. In this study, a new UAV semi-physical-simulation-platform architecture is proposed, which includes a six-degree-of-freedom mechanical structure, a real-time control system and real-time animation-simulation software. The mechanical structure can realistically simulate the flight attitude of a UAV in a three-dimensional space of 4 × 2 × 1.4 m. Based on the designed mechanical structure and its dynamics, the control system and the UAV real-time flight-animation simulation were designed. Compared with the conventional simulation system, this system enables real-time flight-attitude simulation in a real physical environment and simultaneous flight-attitude simulation in virtual-animation space. The test results show that the repeated positioning accuracy of the three-axis rotary table reaches 0.006°, the repeated positioning accuracy of the three-axis translation table reaches 0.033 mm, and the dynamic-positioning accuracy reaches 0.04° and 0.4 mm, which meets the simulation requirements of high-precision visual UAV navigation.

Model Predictive Control With Disturbance Observer for Marine Diesel Engine Speed Control

The application of model predictive control (MPC) algorithm in the fixed phase control of marine diesel engine speed is studied under the premise of considering model mismatch and external disturbance. Firstly, the steady-state error problem of conventional MPC controller is solved by changing nonlinear model to incremental form. Furthermore, discrete disturbance observer (DO) is introduced in the feedback correction, which can filter out the high-frequency disturbance and reduce the requirement of algorithm on the accuracy of model. Then, considering that nonlinear MPC based on DO (DONMPC) requires a large amount of online computation, the algorithm is simplified by preliminarily converting the nonlinear model to linear model. Through analysis, the controller performance of the two models is similar. Furthermore, considering that the speed of marine diesel engine is usually set to a few fixed reference values, a linear multi-model predictive controller based on DO (DOLMMPC) with less online calculation is proposed. Finally, the designed controllers are verified by experiments. The software simulations of the designed controllers and the PID controller are carried out on the cylinder-by-cylinder mean value engine model (MVEM). It is proved that the algorithm simplification method retains the control performance of the DONMPC algorithm, and the control performance of the designed two controllers is better than the PID controller. Moreover, the DOLMMPC controller and PID controller are tested on the semi-physical simulation platform. The results demonstrate that the DOLMMPC controller can meet the computational power limit of the microprocessor in practical engineering.

Hybrid Adaptive Dynamic Inverse Compensation for Hypersonic Vehicles with Inertia Uncertainty and Disturbance

This paper studies an intelligent hybrid compensation scheme for the uncertain parameter and disturbance of hypersonic flight vehicles (HFV). For the longitudinal model of HFV with modeling errors, a nominal nonlinear dynamic inverse (NDI) controller ensures that the system output can accurately track the reference command. In the presence of rotational inertia uncertainty, a multi-learning law adaptive NDI controller is proposed to directly compensate for its impact on tracking performance, making the system robust to the uncertainty and reducing high maneuvering attitude angles and velocities vibration. Then, an improved adaptive NDI controller with a sliding mode disturbance observer is designed to actively compensate for the elastic mode disturbance, and continuously ensure the system’s anti-disturbance flight quality. Ultimately, this active–passive hybrid control scheme compensates for both high maneuvering inertia uncertainty and global disturbance. The Lyapunov functions prove the system’s stability, and the semi-physical simulation platform verifies the effectiveness of the method.

Research on Semi-physical Simulation of Direct Drive Fan Based on ADPSS

A high proportion of new energy equipment brings problems such as increased power source uncertainty and weaker moment of inertia to the power grid. Through large-scale grid simulation with refined models of new energy equipment, potential grid risks can be discovered and grid security can be effectively improved. The modeling accuracy of the new energy equipment model affects the simulation accuracy of the large power grid. In order to solve the accuracy problem of the new energy equipment model, a semi-physical simulation platform close to the actual equipment is used to carry out simulations of different working conditions. Based on ADPSS, a semi-physical simulation electromagnetic model of a dual-motor dual-power unit two-level direct-drive fan was built, and simulation data of different working conditions were obtained. The direct frequency control method is adopted to optimize the motor model, which reduces the steady-state fluctuation of the semi-physical simulation and improves the simulation accuracy.

A Multi-Target Consensus-Based Auction Algorithm for Distributed Target Assignment in Cooperative Beyond-Visual-Range Air Combat

With recent advances in airborne weapons, air combat tends to occur in the form of beyond-visual-range (BVR) combat and multi-aircraft cooperation. Target assignment is critical in multi-aircraft BVR air combat decision-making. Most previous research on target assignment for multi-aircraft cooperative BVR air combat has focused on centralized algorithms, which can be time-consuming and unreliable. This paper proposes an efficient distributed target assignment algorithm called the multi-target consensus-based auction algorithm (MTCBAA). First, by analyzing the main geometric aspects of BVR air combat, a target assignment model for cooperative BVR air combat was established. Next, based on a consensus-based auction algorithm (CBAA), the MTCBAA was developed to solve the target assignment problem by introducing a cooperative decision-making variable. Although the MTCBAA is based on a greedy mechanism, it can guarantee at least 50% global optimization performance, which was proven through a demonstration of the minimum optimization performance of a centralized target assignment algorithm, since the centralized algorithm is equivalent to the MTCBAA. Finally, experiments were conducted, including an experiment that illustrates the operation of the proposed algorithm, Monte Carlo comparisons with a centralized target assignment method based on the immune algorithm, and deployment experiments on a semi-physical simulation platform. Compared with the heuristic target assignment algorithm, the proposed algorithm significantly improved the target assignment efficiency. The practicality of the proposed algorithm was further verified through a distributed semi-physical simulation experiment.

Design and Implementation of Semi-Physical Platform for Label Based Frame Switching in Integrated Satellite Terrestrial Networks

With the explosion of traffic demand in recent years, the integration of satellite optical networks and terrestrial networks (ISTN) creates a promising networking solution for future low-latency, high-rate, and high-capacity communications. Owing to the high cost of deploying and maintaining a satellite optical network, it is critical to carefully design and plan the network to ensure the performance of the network. Thus, a semi-physical simulation platform based on software-defined networks (SDNs) is developed to simulate a satellite optical network and evaluate the performance of the proposed label-based advanced orbiting system (AOS) frame switching method that adheres to the Consultative Committee for Space Data Systems’ recommended standard (CCSDS). The semi-physical simulation platform has two major innovations: (1) adapting and integrating network protocols between the CCSDS and open system interconnect (OSI) reference models, particularly at the data link layer, and (2) the foundation for an SDN-based satellite optical network. In the control plane, real-time VxWorks Simulators serve as controllers to establish and manage various network protocols and the link manager protocol (LMP). Here, network protocols include open shortest path first (OSPF) for routing managing and controlling messages, constraint shortest path first–traffic engineering (CSPF-TE), and constraint-label distribution protocol (CR-LDP) for routing data services. LMP is used to assign and reserve satellite optical link resources. The performance of the architecture and protocols is evaluated via a semi-physical simulation platform.

Hardware-in-the-loop simulation of inverter power supply controller based on StarSim and DSP

Aiming at the contradiction between the requirements for rapid development and verification of inverter power supply controller products and the actual construction of real inverter power supply circuit topology, this paper proposes to build a semi-physical simulation platform based on StarSim and DSP. This paper takes the single-phase full-bridge inverter power supply as an example, use Shanghai ModelingTech company’s StarSim real-time simulator as the hardware platform, establish the circuit model in Matlab/Simulink and select NI PXIe-7846R board to run circuit extensions, and use TMS320F28335 as controller of the phase inverter power supply, based on StarSim HIL host computer program to load the model, configure the IO, and test and verify. The experimental results show that the semi-physical test platform has high accuracy and feasibility, shortens the development cycle of the controller, and greatly reduces the development cost of the controller.

Fault Tolerance Method of Low-Resolution Hall Sensor in Permanent Magnet Synchronous Machine

The estimation of the motor rotor positions with high-precision based on low-resolution Hall sensors becomes an important trend to realize the vector control in low-cost permanent magnet synchronous machine (PMSM) based control systems. Most existing studies focus on the methods to improving the estimating precision of rotor positions, while the estimating precision of failed Hall sensors and the corresponding control strategies for fault tolerance is rarely explored. This paper proposes a method that can online estimate the position of a PMSM rotor with fault detection and fault tolerance. Such a method is able to achieve both stable and precise estimations on rotor position even when one or two Hall sensors fail. Meanwhile, it can meet the needs of vector control under variable speed and load on the PMSM. Finally, a dSPACE-based semi-physical simulation platform is established, which is used to validate the effectiveness of the proposed method with multiple experiments.