Software-in-the-loop Simulation Research Articles

Comparison of Flight Parameters in SIL Simulation Using Commercial Autopilots and X-Plane Simulator for Multi-Rotor Models

Modern aviation technology development heavily relies on computer simulations. SIL (Software-In-The-Loop) simulations are essential for evaluating autopilots and control algorithms for multi-rotors, including drones and other UAVs (Unmanned Aerial Vehicle). In such simulations, it is possible to compare the flight parameters achieved by flying platforms using various commercial autopilots widely used in the UAV sector. This research aims to provide objective and comprehensive insights into the effectiveness of different autopilot systems This article examines the simulated flight test results of a drone performing the same mission using different autopilot systems. The X-Plane software was used as an environment to simulate the dynamics of the drone and its surroundings. Matlab/Simulink r2023a provided the interface between autopilot software and X-Plane models. Those methods allowed us to obtain an appropriate comparison of the autopilot systems and indicate the main differences between them. This research focused on analyzing UAV flight characteristics such as stability, trajectory tracking, response time to control changes, and the overall effectiveness of autopilots. Various flight scenarios including take-off, landing, flight at a constant altitude, dynamic manoeuvrers and, flight along a planned trajectory were also examined. In order to obtain the most accurate and realistic results, the tests were carried out in various weather conditions. The aim of this research is to provide objective data and analysis to compare the performance of commercial autopilots. This method offers several advantages, including cost-effective testing, the ability to test in diverse environmental conditions, and the evaluation of autopilot algorithms without the need for real hardware. The findings of this study may have a considerable impact on how autopilot designers and developers choose the best platforms and technologies for their projects. Future research on this topic will compare the obtained data with flight test data.

Analysis of UTM Tracking Performance for Conformance Monitoring via Hybrid SITL Monte Carlo Methods

Conformance monitoring supports UTM safety by observing if unmanned aircraft (UA) are adhering to declared operational intent. As a supporting system, robust cooperative tracking is critical. Nevertheless, tracking systems for UAS traffic management (UTM) are in an early stage and under-standardized, and existing literature hardly addresses the problem. To bridge this gap, this study aims to probabilistically evaluate the impact of the change in tracking performances on the effectiveness of conformance monitoring. We propose a Monte Carlo simulation-based method. To ensure a realistic simulation environment, we use a hybrid software-in-the-loop (SITL) scheme. The major uncertainties contributing to the stochastic evaluation are measured separately and are integrated into the final Monte Carlo simulation. Latency tests were conducted to assess the performance of different communication technologies for cooperative tracking. Flight technical error generation via SITL simulations and navigational system error generation based on flight experiments were employed to model UA trajectory uncertainty. Based on these tests, further Monte Carlo simulations were used to study the overall impacts of various tracking key performance indicators in UTM conformance monitoring. Results suggest that the extrapolation of UA position enables quicker non-conformance detection, but introduces greater variability in detection delay, and exacerbates the incidence of nuisance alerts and missed detections, particularly when latencies are high and velocity errors are severe. Recommendations for UA position update rates of ≥1 Hz remain consistent with previous studies, as investments in increasing the update rate do not lead to corresponding improvements in conformance monitoring performance according to simulation results.

Semi-automatic of steer by wire system using fuzzy logic control and swarm optimization

<span lang="EN-US">The semi-automatic steer by wire system is a vehicle steering system that does not use a mechanical link but uses an electric drive, so that the steer wheel is equipped with an angle sensor as a control system input to adjust the electric drive rotation when determining the direction of the front wheels of the vehicle. The control system uses fuzzy logic control (FLC) is optimized using swarm-based optimization. Performance testing of the optimal control system is carried out using Software in the loop simulations and hardware in the loop simulations which were then applied to the steering system prototype equipped with rack-pinion and wheel steer. The test results show that the optimal control system performance reaches a C-RMS error of 6.712. The prototype that was built has two kinds of ratios between the steering angle and the vehicle wheel angle, namely a ratio of 1:6.25 for speeds below 10 km/h making it suitable for operation when the vehicle is maneuvering in the parking area and a ratio of 1:25 for speeds above 10 km/h which is suitable for operation when the vehicle is traveling at medium or high speed.</span>

Development Steps of Avionics and Flight Control System of Flight Vehicle

The success of a research is highly dependent on the method adopted, especially research related to dangerous and expensive matters which will certainly require special handling in the development or maintenance steps. One of them is research related to space technology such as aviation and rocketry technology, which is very dependent on the design model of the flying vehicle and, in general, will always use simulation to ensure that the entire system being built is carried out safely and can be implemented properly according to plan. In the development of the prototype flying vehicle, especially the development of the avionics and flight control system, the vehicle will go through sequential simulation steps from Software in the Loop Simulation (SILS), Hardware in the Loop Simulation (HILS), and Ready-to-Fly System (RTFS). In this paper, the simulation steps will be described with the intention of facilitating integration and testing of each sub-system being developed, testing the control strategy applied or eliminating bugs if something goes wrong. In the end, with a series of flying vehicle simulations, it can be developed quickly and cost-effectively, including saving human resources.

Acquisition and Processing of UAV Fault Data Based on Time Line Modeling Method

The number of Unmanned Aerial Vehicles (UAVs) used in various industries has increased exponentially, and abnormal detection of UAVs is one of the primary technical means to ensure that UAVs can work normally. Currently, most anomaly detection models are trained using on-board logs from drones. However, in some cases, using these logs can be problematic due to data encryption, inconsistent descriptions of characteristics, and imbalanced positive and negative samples. Consequently, the on-board logs of UAVs may not be directly usable for training anomaly detection models. Given the above problems, this paper proposes a Time Line Modeling (TLM) method based on the UAV software-in-the-loop (SITL) simulation environment to obtain and process the on-board failure logs of drones. The Time Line Modeling method includes two stages: the Fault Time Point Anchoring Method and Fault Time Window Stretching Method. First, based on the SITL simulation environment, multiple flight missions were constructed. Failures of several common components of UAVs are designed. Secondly, the fault’s initial location and end location are determined by the method of Fault Time Point Anchoring, and the original collection of tagged UAV’s on-board data is realized. Then, in terms of data processing, the features that are not universal are removed, and the flight data of the UAV is optimized by using the data balance method of Time Window Stretching to achieve the balance of normal data and abnormal data. Finally, use of algorithms such as Sequential Minimal Optimization (SMO), Random Forest (RF), and Convolutional Neural Network (CNN) were used to experiment with the processed data. The experimental results showed that the data set obtained based on this method can be effectively applied to the training of machine learning-based anomaly detection models.

Enhancement of Heavy-Duty Engines Performance and Reliability Using Cylinder Pressure Information

Sustainability issues are becoming increasingly prominent in applications requiring the use of heavy-duty engines. Therefore, it is important to cut the emissions and costs of such engines to reduce the carbon footprint and keep the operating expenses under control. Even if for some applications a battery electric equipment is introduced, the diesel-equipped machinery is still popular thanks to the longer operating range. In this field, the open pit mines are a good example. In fact, the Total Cost of Ownership (TCO) of the mining equipment is highly impacted by fuel consumption (engine efficiency) and reliability (service interval and engine life). The present work is focused on efficiency enhancements achievable through the application of a combustion control strategy based on the in-cylinder pressure information. The benefits are mainly due to two factors. First, the negative effects of injectors aging can be compensated. Second, cylindrical online calibration of the control parameters enables the combustion system optimization. The article is divided into two parts. The first part describes the toolchain that is designed for the real-time application of the combustion control system, while the second part concerns the algorithm that would be implemented on the Engine Control Unit (ECU) to leverage the in-cylinder pressure information. The assessment of the potential benefits and feasibility of the combustion control algorithm is carried out in a Software in the Loop (SiL) environment, simulating both the developed control strategy and the engine behavior (Liebherr D98). Our goal is to validate the control algorithm through SiL simulations. The results of the validation process demonstrate the effectiveness of the control strategy: firstly, cylinder disparity on IMEP (+/−2.5% in reference conditions) is virtually canceled. Secondly, MFB50 is individually optimized, equalizing Pmax among the cylinders (+/−4% for the standard calibration) without exceeding the reliability threshold. In addition to this, BSFC is reduced by 1% thanks to the accurate cylinder-by-cylinder calibration. Finally, aging effects or fuel variations can be implicitly compensated, keeping optimal performance thorough the engine life.

Robust Nonlinear Control for the Fully Actuated Hexa-Rotor: Theory and Experiments

This letter addresses a fully-actuated Hexa-rotor’s control under exogenous position and attitude disturbances. For that aim, we propose a nonlinear and robust control based on a backstepping technique for position dynamics and a geometric control for attitude dynamics. We demonstrate that the closed-loop system is globally exponentially stable. To validate the reached stability, we present simulation results using MATLAB/Simulink and software in the loop simulations using the well-known PX4 firmware in a realistic scenario on a virtual environment in Gazebo. Finally, to ultimately demonstrate the effectiveness of our algorithm, we implement it on an own-developed fully-actuated Hexa-rotor platform. Our contributions can be summarized as 1) the design of a robust controller for the fully-actuated Hexa-rotor not presented in the literature, 2) the publication of the controller’s code for the PX4 autopilot software, and 3) drone’s construction and presentation of real flight experiments.

FPGA-Based Statechart Controller for MPPT of a Photovoltaic System

Conventional Maximum Power Point Tracking (MPPT) controllers in photovoltaic (PV) systems are seen to achieve tracking speeds in range of milliseconds. Power-electronic circuits in these systems many-a-time demand faster control actions in microseconds, as they operate at high frequencies, and also, a delay in control action would lead to a corresponding power-loss. Hence, an MPPT controller delivering such fast tracking speeds would improve overall system performance. In this work, an Field Programmable Gate Array (FPGA) based Statechart Controller is developed to perform MPPT control of the PV system. The developed Statechart Controller is tested using software-in-the-loop simulation(SILS) and results are presented. With inputs from a programmable logic controller emulating PV characteristic curves, the Statechart Controller is then deployed in a target FPGA. A comparison between performance with conventional MPPT controller and Statechart Controller is presented and results indicate that the latter is more effective in terms of tracking speeds, determinism, and modularity.

The cascade optimal control of steer by wire system using hardware in the loop simulations

This paper aims to further improve the performance of the control system on the steer by wire (SbW) of vehicle steering system, by presenting the development of optimal control system strategy for lateral motion and yaw motion which is arranged in a cascade so that the vehicle can always be maintained on the desired trajectory. The control system strategy to be developed is fuzzy logic control (FLC) as a lateral motion control and proportional integral derivative (PID) control as a yaw motion control, and to obtain an optimal control system, the modified-quantum particle swarm optimization (MQPSO) optimization method is used. The simulations are carried out using hardware in the loop simulations (HILS) which involve hardware, namely; motor stepper actuator and rotary encoder to determine and monitor the direction of the front wheels which are applied to the vehicle dynamics model in a real time. HILS test results show that vehicle movement can be maintained according to the desired trajectory (double lane change) with an average continues-root mean square (C-RMS) error of 0.015366 for lateral motion and 0.014967 for yaw motion, the average C-RMS error is greater 23.75% for lateral motion and 28.18% for yaw motion against the results of the software in the loop simulations (SILS) test.

Software-in-the-loop simulation of the forerunner UAV system

The forerunner UAV means a camera equipped drone flying in front of the advancing first responder units to increase driver situational awareness with an aerial view of the traffic situation and notification about imminent dangers. This article presents the software-in-the-loop (SIL) simulation of the concept including UNREAL4-Carla as the virtual reality environment with a firetruck driven through a game controller, the Matlab simulation of the DJI M600 forerunner hexacopter with UDP communication between firetruck and M600 and the real-time AI processing of synthetic images to detect ground vehicles and pedestrians. The target of SIL development is threefold. First, to test M600 autopilot and AI-based object detection in close to realistic conditions before the real flights. Second, to make an exhaustive feasibility study of the whole forerunner concept with several simulated situations. Third, to generate the required large amount of image data for AI object detection tuning. After introducing all parts of the SIL simulation the article presents an illustrative example evaluating the tracking of the ground vehicle with the M600 and the inference system results.

A Research on the SILS System for Design and Analysis of Non-Communication Electronic Warfare Weapons based on the Engineering M&S Technique

We research and develop a SW-based virtual testing product that can be commonly used in the design/ development of non-communication EW systems before the production of physical test products. Through this study, we have developed M&S technology to improve the accuracy of EW weapon system analysis/design and to verify and predict the performance of EW equipment, and to develop proven engineering module models and model base systems. It proposes a technology to build an EW M&S framework that can flexibly link/integrate various engineering/engage-level EW heterogeneous M&S systems. Keywords: ì „ìžì „, 공학급 M&S, SILS Keywords: Electronic Warfare, Engineering M&S, Software In the Loop Simulation

Hardware in the Loop Simulation of Control Optimal of DC Motor Base on Modified Quantum-Behaved Particle Swarm Optimization

Proportional, Integral, Dervative (PID) controller is a simple and very reliable controller, but to determine the optimal control system parameters on the PID controller (Kp, Ki, and Kd) is not easy. This paper aims to determine the optimal parameters of the PID controller using Modified Quantum Behave Particle Swarm Optimization (MQPSO) to regulate the speed control of a DC motor. MQPSO is a method that has particle search behavior that is more detailed than its predecessor methods, namely Particle Swarm Optimization (PSO) and Quantum-Behaved Particle Swarm Optimization (QPSO). The test is done through Software In the Loop Simulation (SILS) by representing a DC motor in the transfer function, after the optimal control parameters are obtained then applied to the Hardware In the Loop Simulation (HILS) test using the actual DC motor. The test results show that the PID controller that has been optimized using MQPSO results in achieving DC motor response under steady conditions and is faster than the PID controller that is optimized using Ziegler-Nichols (ZN), PSO and QPSO. The completion time obtained by MQPSO is 41.0201 ms, which is also faster than using QPSO 42.8276 ms, PSO 43.7008 ms and ZN 61.8571ms.

Systematic Fuzz Testing Techniques on a Nanosatellite Flight Software for Agile Mission Development

The success of CubeSat space missions depends on the ability to perform properly in a harsh environment. A key component in space missions is the flight software, which manages all of the processes executed by the satellite on its onboard computer. Literature shows that CubeSat missions suffer high infant mortality, and many spacecraft failures are related to flight software errors, some of them resulting in complete mission loss. Extensive operation testing is the primary technique used by CubeSats developers to ensure flight software quality and avoid such failures. The “New Space” requirements pressure to add “agility” to the software development, which could limit the capacity to test. While advanced and beneficial software testing techniques are found in the software engineering field, CubeSat software solutions mostly rely on unit testing, software in the loop simulation, and hardware in the loop simulation. In this work, fuzz testing techniques were developed, implemented, and evaluated as a manner to expedite operational testing of CubeSats while maintaining their completeness. The impact of the tools was evaluated by using the three new 3U CubeSats under development at the University of Chile. We identified twelve bugs not covered by classic testing strategies in less than three days. These failures were reported, fixed, and characterized by the developers in eight sprint sessions. Our results indicate that fuzz testing improved the completeness of flight software testing through automation and with almost no development interruption. Although our approach has been tested on the SUCHAI flight software, it applies to systems that follow a similar architecture.

A Stereo Vision-Aided Receding Horizon Vehicle Dynamic Control System for Independent Drive Vehicles Steered by Wire

This paper proposes a stereo vision-aided receding horizon vehicle dynamic control system for independent drive vehicles steered by wire. First, we propose the receding horizon vehicle dynamic control (RHVDC) to track the desired slip angle and yaw rate of a dynamic vehicle. The RHVDC computes and updates control inputs at each sampling time to minimize a quadratic cost function over the finite future time horizon, allowing it to address the time-varying property of dynamic vehicles. Its stability is shown to be guaranteed with appropriate parameters. Second, unlike the conventional steering systems fixed with the driver’s steering wheels, the SBW system improves the controllability of vehicle dynamics and enables better tracking performance. Third, combining a stereo vision system with existing sensors allows state estimation of dynamic vehicles to be more accurate in noisy environments. The three strategies mentioned above ultimately maximize the tracking performance of dynamic vehicles through improvement in terms of theory, facilities, and recognition. Through the software-in-the-loop simulation (SILS) with CarSim, the proposed RHVDC system has the better tracking performance for controlling both the slip angle and the yaw rate compared with the existing ones. It is also observed that the performance enhancement of the proposed RHVDC system is more outstanding on slippery or more severe roads.

Development of an Unmanned Aerial System for Maritime Environmental Observation

We developed an octocopter-based unmanned aerial system (UAS) to monitor remote environments. The system contains various environmental monitoring sensors for measuring wind speed/direction, temperature, relative humidity, atmospheric pressure, fine dust, and multispectral and RGB data. The UAS consists of an unmanned aerial vehicle (UAV), a ground control station, and a server. We studied its electrical, mechanical, and software (SW) configurations. Specifically, we developed hardware (HW) and SW to control the yaw and gimbal pitch directions of the UAV conveying multispectral and RGB cameras. To prevent the obtained solar reflectance from affecting the multispectral and RGB data and to improve the quality of the obtained data, we maneuvered the yaw so that it would always deviate 135° from the solar azimuth angle, with the sun at its rear. Managing the yaw direction involves controlling the UAV based on a micro air vehicle link message-based robot operating system (ROS). To safely test the UAS performance before the maiden flight in an ocean area, we first evaluated PX4 and ROS-based SW through indoor software-in-the-loop simulation (SILS) via the Gazebo tool. Subsequently, we used an F450 UAV and an actual maritime UAV to sequentially perform pre-flight and flight experiments. This paper explains the system operation scenario, UAS component, and simulation and experimental results. The results reveal that the average yaw angle error during the mission, $\bar {\left |{ \theta _{y,des}-\theta _{y} }\right |}$ , is approximately 8°, and the average pitch angle of the gimbal during the mission, $\left |{ 50^{\circ }-\left |{ \bar {\theta _{c}} }\right | }\right |$ , is less than 5°.

Novel Offline Software-in-the-Loop Simulation Technique for Modular Single-Phase Flyback Current Source Grid-Tie Inverter System

This paper proposes a novel approach in the offline Software-in-the-Loop (SIL) simulation technique to speed up the firmware development cycle of power electronics and enhance the firmware maintenance of commercial products. In the conventional SIL simulation process, Model-in-the-Loop (MIL) is always performed prior to the execution of SIL because it allows users to automatically generate C code for testing in the subsequent SIL. Furthermore, the target device can be programmed with the compiled files only if the simulation tools support specific models of control chips. In light of this, the goal to use SIL to validate firmware in early power electronics product development becomes more complex and limited due to the limited selection of simulation tools. In this paper, non-preemptive scheduling (NPS) and common firmware architecture (CFA) are explored to illustrate the integration of the application layer for implementing the proposed offline SIL. Users can directly use circuit simulation software that supports Dynamic-Link Library (DLL) to simultaneously develop source codes and verify the offline SIL process of the product. To further illustrate the practical application of the power electronics product in the microcontroller (MCU) mock model and the power stage circuit model, a single 300W power module composed of three single-phase quasi-resonant (QR) flyback current source converters connected in parallel and cascaded with an H-bridge unfolder is used as an example to execute offline SIL in the SIMULINK. Finally, a system-level experiment was conducted to validate the firmware of 16 power modules assembled in a 4.8 kW fuel cell (FC) grid-tie inverter system, which was modulated through the power management unit (PMU) and the monitoring graphical user interface (GUI).

Virtual Controller Interface Device for Hardware-in-the-Loop Simulation of Traffic Signals

Microscopic traffic simulation has been widely used for the design and/or evaluation of a new signal control strategy prior to field implementation. One of the most popular simulation approaches is the Hardware-in-the-Loop Simulation (HILS), which employs a Controller Interface Device (CID) to connect a physical signal controller to the simulation software to improve the accuracy of simulation. This paper documents the development and performance evaluation of a Virtual Controller Interface Device (VCID) based HILS. Different from the traditional physical CIDs, VCID provides wireless communication between signal controllers and simulation software through the National Transportation Communications for ITS Protocol (NTCIP). Controlled simulation experiments were conducted to compare the performance of VCID-based HILS with the Emulator-in-the-Loop Simulation (EILS), Software-in-the-Loop Simulation (SILS), and the traditional HILS. Queue length, delay, and vehicle trajectories were employed as performance measures. Simulation results show that VCID is an accurate and reliable tool for traffic signal simulation. In addition, since VCID-based HILS enables real-time updating of signal controller parameters during the simulation through the Simple Network Management Protocol (SNMP), it can efficiently assess the adaptive signal control algorithms that are developed based on the real-time traffic flow data collected by Connected Vehicles (CV) or Intelligent Transportation Systems (ITS).

A Study on the Improved Capacitor Voltage Balancing Method for Modular Multilevel Converter Based on Hardware-In-the-Loop Simulation

In the power industry, hardware in-the-loop simulation (HILS) based on a real-time digital simulator (RTDS) is important technology for modular multilevel converter (MMC)-based high-voltage direct current (HVDC) power transmission. It is possible in real time to verify various fault situations that cannot be predicted by the software-in-the-loop simulation (SILS). This paper introduces the implementation methodology of sub-module (SM) capacitor voltage balancing for a MMC-HVDC physical control system based on field-programmable gate array (FPGA), which has the advantages of high-speed parallel operation and validates the reliability and accuracy of MMC-HVDC control when this control system is operated with RTDS. The characteristics of conventional capacitor voltage balancing methods, such as the nearest level control (NLC) with full sorting method, the NLC with reduced switching frequency method, and the tolerance band (TB) method, implemented on a physical control system based on this implementation methodology, are compared and analyzed. This paper proposes the improved capacitor voltage balancing method for MMC-HVDC transmission. Finally, the proposed capacitor voltage balancing method is compared with conventional methods to analyze performance in real-time to demonstrate that the proposed method is better than the conventional methods.

Hardware- and Software-in-the-Loop Simulation for Parameterizing the Model and Control of Synchronous Condensers

The rapid increase of converter-based generation in grids causes significant changes in system dynamic characteristics. These changes require verification and testing of the reliability, optimization, and functionality of power system elements and controllers, which become more important for guaranteeing a secure operation. This paper first introduces a hardware-in-the-loop setup of an automatic voltage regulator (AVR) control system and then proposes a software-in-the-loop (SiL) setup for the parameterization of an IEEE standard AVR/excitation system model and a power oscillation damping (POD) controller of synchronous condenser. The AVR hardware is interfaced with a simulated grid in real-time digital simulator (RTDS) using EMT simulation to evaluate its control functions. Parameter optimization for the POD and the AVR simulation model by SiL simulation is implemented in a closed loop between RTDS and MATLAB/Simulink interfaced through OPC to satisfy the optimization objectives. By the tests executed on the future Western Danish power system, parameter optimization of the POD and IEEE standard AVR model, and the function of AVR hardware are successfully implemented and verified.

Computational Simulation of Flight Behavior of Flying Wing UAV

Abstract — The aim of this work is to model and simulate a Flying Wing Aircraft and compare acquired flight data from two different simulations. The framework proposed constitutes of the development of a graphical model as well as the use of a mathematical model of the aircraft. In order to implement the Software-in-the-Loop (SIL), we used a commercial flight simulation environment, X-plane 10, which simulates the dynamics of the aircraft through the Blade Element Theory, and the software MATLAB/Simulink, which simulates and implement the control laws. We collected the flight data from the simulator, as well as the responses of the mathematical model based on equations of motion and the aerodynamic derivatives, which were computed via the Digital DATCOM software. Both analytical simulation and the SIL simulation were performed with the same flight conditions, validating the longitudinal dynamic of the computational model and allowing further studies of this type of aircraft in future projects.