Hardware-in-Loop (HIL) Simulation

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Hardware-in-the-loop implementation for an active heave compensated drawworks

Hardware-in-the-loop implementation for an active heave compensated drawworks

Abstract: This paper presents the setup and running of a hardware-in-loop (HIL) simulation for an active heave compensated (AHC) draw-works. A simulation model of the draw-works is executed on a PC to simulate the AHC draw-works with a physical PLC. The PLC (ET200S) is configured with a controller architecture that regulates the motor angular displacement and velocity through actuation of the servo valves. Furthermore, a graphical user interface is developed for operation of the AHC system. The HIL test allowed tuning of the physical controller in terms of heave stabilization and positioning. The conclusion after the testing is a PLC which is ready for operation without necessitating the use a physical prototype of the process.

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Harmonic-by-harmonic time delay compensation Method for PHIL simulation of low impedance power systems

Harmonic-by-harmonic time delay compensation Method for PHIL simulation of low impedance power systems

he first step towards the development of new testing procedures for power components was demonstrated with the development of hardware-in-the-loop simulation (HIL), which is able to merge the two traditional testing procedures (computer simulation and hardware testing) by interfacing the software simulation with the real hardware under test. Mainly controller devices are used as testing devices for HIL simulation due to the fact that they only need low power and voltage signals to be exchanged and consequently this procedure is also called controller-hardware- in-the-loop (C-HIL) simulation. Since just low level signals are exchanged between the software simulation and the hardware under test, this procedure is not valid for power components such as motors, generators or power converters that require higher levels of power to be exchanged. Hence, in order to achieve an improvement in cost, time, flexibility, risk, and accuracy of the testing methodology for these power components further development was required. The solution for HIL simulation with power components was achieved by the addition of a power interface between the software simulation and the hardware under test, as shown in Fig.1. The

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Hardware in the loop 
		simulation and digital control of double inverted pendulum

Hardware in the loop simulation and digital control of double inverted pendulum

All these results are proof of the versatility that HIL offers in the implementation and emulation of plants. Reason why, this alternative to control nonlinear systems like double inverted pendulum, whose physical mechanism is difficult to build, was chosen. Among the papers found with this system, publications from [6] and [7] can be highlighted, where they control the angular and spatial position of the bars and mobile, on which is supported, with a LQR controller. In the same way, classic control systems along with neural networks have been used for estimate the controller gains and achieve the stabilization of the system [8]. Another example is the work performed in [9], where concepts related to artificial intelligence were used for controlling a similar system, achieving a real-time control, with more robustness and stability than using conventional methods.

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A new control method for the power interface in power hardware-in-the-loop simulation to compensate for the time delay

A new control method for the power interface in power hardware-in-the-loop simulation to compensate for the time delay

ower hardware-in-the-loop (PHIL) simulation is an ex- tension of the widely known hardware-in-the-loop (HIL) simulation concept. However, in contrast with the most common procedure of HIL called controller hardware-in-the- loop (CHIL), where the hardware under test (HUT) is a con- troller that only exchanges control signals with the simulated system, PHIL allows the testing of power components by exchanging power with the simulated system through the power interface. The power interface electrically couples and converts the low voltage/power signals of the real time simu- lator (RTS) into high voltage/power signals going into the HUT. The HUT responds to the applied signal (current or voltage), and the measurement of this response is fed back (by the power interface or an external measurement unit) to the RTS closing the loop, and therefore creating a simulation system that ideally would match with the real one. This struc- ture of a PHIL simulation is shown in Fig. 1. However, stabil- ity and accuracy issues exist when an interface is used, this is due to the introduced error during the simulation and amplifi- cation stages, and also to additional components introduced to compensate for the time-delay or for a stability improvement [1-4].

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Hardware-In-The-Loop and Software-In-The-Loop Testing of the MOVE-II CubeSat

Hardware-In-The-Loop and Software-In-The-Loop Testing of the MOVE-II CubeSat

Although the connection between the ADCS interfaces and the Mainpanel carried only digital information, the connection between the solar cells and the EPS carries electrical power. The introduction of Section 2 already stated that our HIL environment will cover the whole electrical domain, so we need to provide realistic inputs and outputs to the EPS to test it in flight-like conditions and verify the satellite’s power budget. The inputs, i.e., the solar cells, are replaced by the Solar Array Simulator covered in Section 2.3.2. The outputs, i.e., all consumers of electrical power, are not replaced. The HIL environment includes them as processing hardware. The actuators on the Sidepanels and the Toppanels are one major power sink that are not part of the processing hardware. We connect them in a read-only configuration so they will consume a realistic amount of power but do not disturb the communication (see Section 2.3.1). This architecture ensures that the HIL environment resembles the electrical power situation onboard the satellite at high precision. Furthermore, the verification is simplified to starting the simulation and observing the state of charge of the battery.

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Analysis on Control System Design of Plant Simulator for Hardware-In-The-Loop Simulation Using MATLAB

Analysis on Control System Design of Plant Simulator for Hardware-In-The-Loop Simulation Using MATLAB

Traditional testing, referred to as static testing, is where functionality of a particular component is tested by providing known inputs and measuring the outputs. Today there is more pressure to get products to market faster and reduce design cycle times. This has led to a need for dynamic testing, where components are tested while in use with the entire system, either real or simulated. Because of cost and safety concerns, simulating the rest of the system with real-time hardware is preferred to testing individual components in the actual real system. Dynamic testing also encompasses a larger range of test conditions compared to static testing. Employing this strategy for dynamic testing is known as Hardware-in-the-Loop (HIL) simulation. HIL is an integrated part of the design cycle. Figure 2 below represents the design cycle of embedded control applications common to automotive, aerospace, and defense industries.

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Real-Time Hardware-in-the-Loop Simulation of Permanent Magnet Synchronous Motor Drives under Stator Faults

Real-Time Hardware-in-the-Loop Simulation of Permanent Magnet Synchronous Motor Drives under Stator Faults

Peak and rms fault current results are compared for different speeds ranging from 500 to 6500 r/min and two different load conditions as shown in Fig.8. In general, a good match between FEA, HIL and experimental results is shown, with a maximum error below 15% occurring at lower rotor speeds and lower load resistance. The main cause of error is the poor repeatability of the contactor resistance which varies from 2 to 2.5m (25% variation) at different contactor closures during the experiments. At lower speeds, the resistive component dominates the overall fault impedance compared with higher speeds, where the dominating contributor is inductance. Figures 9-10 show measured and simulated fault current waveforms in four different conditions at rotor speeds of 1500 and 5500 r/min under no load and at 0.69- load, respectively. Figures 11 -12 show comparisons in d- and q-axis current ripples in two different operating conditions at 5500 and 3500 r/min, respectively, confirming the good agreement between the proposed real-time modelling and the experimental measurements.

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Hardware-in-the-loop simulation of massive-payload manipulation on orbit

Hardware-in-the-loop simulation of massive-payload manipulation on orbit

Furthermore, the modified model-based teleopera- tion is verified using a hardware-in-the-loop simula- tion (HILS). Various HIL simulators for space robots were surveyed in  [9]. HIL simulators for space robots have been developed mainly to simulate the capture of space targets such as satellites  [10–12]. However most HIL simulators for space robots have used conventional serial robots to reproduce the movement of the space target. Serial robots do not generally move very quickly, and hence the response delay is relatively large. The large response delay of the motion table (the robot arm used to reproduce the movement of the space target) may cause instability in HILS  [13]. Hence, this work uses a parallel-robot-based HIL simulator  [14], applying delay time compensation [13] in order to validate the model- based teleoperation by simulating massive-payload manipulation.

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Tire Suspension Steering Hardware in the Loop Simulation

Tire Suspension Steering Hardware in the Loop Simulation

In automotive applications, one of the most common applications of HIL simulations is testing and evaluating a vehicle’s Electronic Control Unit (ECU). In this case, a real ECU is tested by giving it virtual signals generated from a computer running a vehicle model. It can then be tested and analyzed under various driving conditions [5]. Dangerous driving conditions can be tested safely and repeatably. Due to these advantages, there are a number of commercially available products specialized in HIL simulations of ECUs; e.g., products from AVL, dSPACE, and ETAS. There are numerous HIL systems to test various functions of the ECU; e.g., HIL of Anti-lock Brake Systems (ABS) [6, 7], HIL of Electronic Power Steering (EPS) [8], HIL for testing of velocity/distance controller for driver safety system [9], HIL system of throttle body for testing of engine throttle controller [10], and HIL system to test diesel hybrid electric vehicle [11].

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An advanced hardware in the loop battery simulation platform for the experimental testing of battery management system

An advanced hardware in the loop battery simulation platform for the experimental testing of battery management system

Hardware-in-the-loop (HIL) simulation has been intensively used in many fields such as control development and verification, product and component assessment, and system performance validation [1-6]. It enables the testing of actual components of a system in conjunction with a virtual computer- based simulation in a real-time environment. When performing HIL simulation, the physical plant or system is replaced by a accurately equivalent model-based real-time simulator, which is equipped with physical inputs and outputs (I/O) ports for interfacing with the control system and other HW. Hence, HIL simulator can accurately reproduce the plant dynamics and its behaviours providing comprehensive closed-loop testing without the need for testing on real systems. This means of testing avoids complex processes in HW setup and configuration, time and cost constraints, and helps lower the risks of accident to people and equipment. Consequently, exploitation of HIL simulation in battery testing system is an efficient way, which is not only to emulate a battery pack based on any battery model, but also to provide an ideal testing environment for the BMS evaluation. As comparing to the BMS tests performed on a physical battery system, tests conducted on a HIL simulator are more cost and time saving, less complicated in setting-up the HW test bench and more secure to carry-out the experiments in cases of the testing condition is beyond the normal operating bounds, especially it is useful at the early stages of the development process or during complex fault insertion test scenarios.

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The use of real time digital simulation and hardware in the loop to de-risk novel control algorithms

The use of real time digital simulation and hardware in the loop to de-risk novel control algorithms

With RTDS and HIL it is a relatively easy and low cost to model multiple power and propulsion system topologies. Unlike a SITF, in all likelihood dedicated to a single topology, RTDS can be used to investigate multiple topologies during project concept design stages. Any investment in RTDS hardware can be reused, being reprogrammed for the different topologies. Whilst different sets of HIL hardware are likely to be required, the cost of the control hardware and software is generally a small fraction of the cost of the equipment it controls, particularly if no or minimal development is required. It is possible to envisage an RTDS being used to investigate the performance of multiple topologies, helping in the down select.

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Implementation and Hardware-In-The-Loop Simulation of a Magnetic Detumbling and Pointing Control Based on Three-Axis Magnetometer Data

Implementation and Hardware-In-The-Loop Simulation of a Magnetic Detumbling and Pointing Control Based on Three-Axis Magnetometer Data

Attitude dynamics is simulated using Simulink fixed step ode8 integrator. The integration time for the software is synchronized with that of the HiL simulations, which was selected to be 10 times faster than real time. This corresponds to an operating frequency of 10 Hz for the Helmholtz cage, therefore, to avoid loss of information, the sampling frequency of the OBC magnetometer is set to 100 Hz. It is worth noting that, since the attitude motion of the spacecraft is just simulated, the magnetometer will not read values of the geomagnetic field in ℱ , but in ℱ instead. Therefore, the coordinate transformation from B i to B b is performed in Simulink, after calculating the Euler angles

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The use of real time digital simulation and hardware in the loop to de-risk novel control algorithms

The use of real time digital simulation and hardware in the loop to de-risk novel control algorithms

With RTDS and HIL it is a relatively easy and low cost to model multiple power and propulsion system topologies. Unlike a SITF, in all likelihood dedicated to a single topology, RTDS can be used to investigate multiple topologies during project concept design stages. Any investment in RTDS hardware can be reused, being reprogrammed for the different topologies. Whilst different sets of HIL hardware are likely to be required, the cost of the control hardware and software is generally a small fraction of the cost of the equipment it controls, particularly if no or minimal development is required. It is possible to envisage an RTDS being used to investigate the performance of multiple topologies, helping in the down select.

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Systems level validation of a distributed frequency control algorithm

Systems level validation of a distributed frequency control algorithm

The validation and development of distributed control ap- proaches has been proven to be a difficult task to be carried out with accuracy and under realistic environments. In this case, a laboratory platform for improving the development and validation for distributed control concepts (mainly for power system use cases) has been accomplished. The platform consists of two main sections: firstly a hardware-in-the-loop (HIL) capability with real-time simulation and secondly a multi-agent system (MAS) platform with a realistic commu- nication network. With this implementation realistic testing of power components and its interactions under distributed control scenarios can be studied with more detail and more precise conclusions can be reported from the power system focus of the validation process. The MAS hardware setup with realistic communications allows for the same detail of testing as the power system side but with the focus on the distributed control algorithms (scalability, robustness, cyber-security, etc.) and the always important communication infrastructure. In Fig. 1 the structure of the distributed control platform is presented. The platform is mainly divided into two sections, the HIL section and the MAS capability.

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Hardware in the Loop Real-Time Simulation for Heating Systems: Model Validation and Dynamics Analysis

Hardware in the Loop Real-Time Simulation for Heating Systems: Model Validation and Dynamics Analysis

Abstract: Heating systems such as heat pump and combined heat and power cycle systems (CHP) are representing a key component in the future smart grid. Their capability to couple the electricity and heat sector promises a massive potential to the energy transition. Hence, these systems are continuously studied numerical and experimental to quantify their potential and develop optimal control methods. Although numerical simulations provide time and cost-effective solution for system development and optimization, they are exposed to several uncertainties. Hardware in the loop (HiL) system enables system validation and evaluation under different real-life dynamic constraints and boundary conditions. In this paper, a HiL system of heat pump testbed is presented. This system is used to present two case studies. In the first case, the conventional heat pump testbed operation method is compared to the HiL operation method. Energetic and dynamic analyses are performed to quantify the added value of the HiL and its necessity for dynamics analysis. The second case, the HiL testbed is used to validate the heat pump operation in a single family house participating in a local energy market. It enables not only the dynamics of the heat pump and the space heating circuit to be validated but also the building room temperature. The energetic analysis indicated a deviation of 2% and 5% for heat generation and electricity consumption of the heat pump, respectively. The model dynamics emphasized the model capability to present the dynamics of a real system with a temporal distortion of 3%

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Myoelectric control algorithm for robot-assisted therapy: a hardware-in-the-loop simulation study

Myoelectric control algorithm for robot-assisted therapy: a hardware-in-the-loop simulation study

The aim of the present study is to develop a myoelectric control (MEC) algorithm, based on the algorithm proposed by Hayashi et al. [19], but that does not require addi- tional sensors and uses the maximum voluntary contraction (MVC) as a simple cali- bration process. The sEMG signal processing algorithm can detect the orientation and approximate the intensity of movement intention proportionally to the maximum MVC tests. The proposed MEC algorithm was implemented in a computational model of the lower limb rehabilitation system, Nukawa. Such a mechatronic system is a product of requirements presented by an interdisciplinary group, formed by physiotherapist and engineers, and has its antecedents in [25]. The mechanical design, presented in Fig.  1, consists of two limbs, each one composed by a three-link mechanism and a Computed Torque Control (CTC). The implementation of the CTC algorithm was conducted in a first stage as a hardware-in-the-loop (HIL), using the Nukawa simulation model without having to use the actual robot since Nukawa is not yet fully operational [26].

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Model Based Development Using Hardware in the Loop Simulation for Servo Press Machine

Model Based Development Using Hardware in the Loop Simulation for Servo Press Machine

This paper presents a proposal of MBD using a Hard-ware-In-the-Loop Simulation (HILS) verification system, which can accommodate phenomena in the electrical, mechanical, and control fields and resolve difficulties described above, which are encountered during the development of a servo control system for industrial machine. The proposed HILS verification system consists of an actual servo amplifier, an actual controller, and a real-time simulator with a machine model, motor models, and electric circuit models installed. One can optimize the control method and parameters for various operating conditions. After the proposed method was applied to a press machine driven by a 75 kW servo motor, its effectiveness was confirmed.

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Scheduling the sequential hardware in the loop simulator

Scheduling the sequential hardware in the loop simulator

The seq hils is a cycle precise simulator, which can simulate synchronous designs. The simulation itself is performed on a FPGA. In order to sim- ulate large designs on the FPGA, time-multiplexing of hardware is imple- mented by the simulator. The design is split into cells, where similar cells are mapped onto a single hypercell in the FPGA. The FPGA sequentially evaluates cells on the hypercells and propagates values of changed output throughout the design until the system stabilizes. Currently, a round robin arbiter schedules unstable cells for evaluation. When the system is stable, a single cycle is simulated, and the simulator advances to the next cycle. In the next sections the design will be described more thoroughly. In the simulator design, three levels of detail can be distinguished; we will describe them in a top-down order: from duv -level to signal-level. But first we start with defining the timing involved in the simulation process.

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A Meta-model Based Modeling Method for Geographic Information Model in CTCS Hardware-in-the-loop Simulation System

A Meta-model Based Modeling Method for Geographic Information Model in CTCS Hardware-in-the-loop Simulation System

To verify the geographic information model and related modeling method, real data of the Wuhan- Guangzhou railway line which we just use five stations and four inter-sections has been used to instantiate the model. And a set of real train control equipments (TCC, CI, RBC, ATP, etc.) as well as a series of real equipment software have been embedded into the simulation platform. The simulating results of a lot of typical application scenes show that the geographic information model can indeed provide effective support for running of real equipments and software. Since running real

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COMPLETE MONITORING OF GROUND CONTROL SYSTEM FOR HIGH SPEED UAV

COMPLETE MONITORING OF GROUND CONTROL SYSTEM FOR HIGH SPEED UAV

Ground control system (GCS) was developed as tools to analyze a special purpose high speed UAV that capable of flying up to a minimum speed of 300 km/h, and this speed will continue to be improved for the next project. Using Hardware in the Loop Simulation (HILS) method between XPlane flight simulator and Labview as programming tools, all of attitude conditions, position in Google map and health monitoring of UAV can be monitored. Including setting the PID control and way points for auto pilot system can also be set easily. Making it easier for the pilot or the researchers to directly analyzing the current condition of the UAV maneuvers. Since all parameters are displayed in a user friendly views. In Hardware in the Loop Simulation (HILS), data communication is done using UDP / User Datagram Protocol to ensure that the data transfer will not interfere with monitoring / analysis conducted by the researchers, because this GCS has been extremes tested using F22 Raptor fighter up to speed of 514 m/s (about Mach 1.5) in the simulation. And more than that, the real data communication has also been carried out using the data telemetry system TX-RX for the high speed UAV is being developed. With these results, developed a universal GCS that capable of being used for the purposes of any kind UAV research, ranging from a low speed of 80 km/h to 400 km/h at this time. This GCS can display all the parameters that required by the researcher according to the parameters provided by XPlane for the UAV development.

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