Hardware-in-the-loop simulation of DC motor as an instructional media for control system design and testing

Instructional media in control systems typically requires a real plant as an element to be controlled. However, this real plant, which is costly to be implemented, can be replaced by a virtual plant implemented in a computer and modelled in such a way that it resembles the behavior of a real plant. This kind of set-up is widely termed as hardware-in-the-loop (HIL) simulation. HIL simulation is an alternative way to reduce the development cost. A virtual plant is easy to adjust to represent various plants or processes that are widely used in industry. This paper proposes a simple HIL simulation set-up designed as instructional media for design and testing a simple control system. The experimental result on DC motor control shows that HIL simulation dynamical response is similar to the real hardware response with a small average error on measured transient response, represented in 0.5 seconds difference in settling time and 7.43 % difference in overshoot. This result shows the efficacy of our HIL simulation set-up.

Smith predictor compensation and fuzzy incremental control for delay of space docking hardware-in-the-loop simulation system

Hardware-in-the-loop (HIL) simulation for space manipulator docking is an important means to simulate real space docking on the ground. The HIL simulation system in this paper utilizes the contact force measured by force sensor to calculate the dynamics of the mechanisms, and the docking process is simulated by the parallel robot. The measurement delay of force sensor and dynamic response delay of the parallel robot are inevitable, which not only affect the accuracy of simulation but also lead to the instability of the HIL simulation system. The traditional first-order phase compensation is the most commonly used force sensor compensator; but when the force changes with a high frequency, its compensation effect becomes bad, which will lead to the divergence of the HIL simulation system. Most control methods of the parallel robot are based on the model of the parallel robot, but the forces of the parallel robot are complex during the docking process, and the system parameters, motion frequency, and dynamic response characteristics are time-varying; thus, it is difficult to design the controller based on the model. In this paper, the Smith predictor compensation (SPC) method and fuzzy incremental control (FIC) method are utilized to decrease the delays of the force sensor and parallel robot, respectively. The effectiveness of the Smith predictor compensation and fuzzy incremental control method in reducing the delay of the HIL system and in improving the stability of the system is verified by simulation and experiment; compared with the traditional first-order phase compensation and proportional-integral-differential control methods, the advantages of the proposed methods are illustrated. The research in this paper provides an important technical means for accurately simulating the real docking process.

An Original Distributed Simulation Method Applied to the Advanced Nuclear Power Plant Control Technology Hardware-in-the-Loop Simulation Verification Platform

Hardware-in-the-loop (HIL) simulation technology, where the part of a system to be verified adopts real objects, is one of the important methods for the research of advanced nuclear power plant (NPP) instrumentation and control (I&C) technology. With the development of advanced NPP I&C technology, especially the multi-module NPP technology, the HIL simulation technology is facing the challenge of communication signals booming and model extension to deal with the requirement of modules increasing and thermal-electricity generation. Driven by the above requirement of research and engineering, it is necessary to develop a novel HIL simulation technology that has well flexible scalability and avoids the high computational burden of the distributed control system (DCS). In this paper, an original distributed simulation method applied to the transformation extension of the NPP I&C HIL simulation verification platform is proposed. The initial opinion of the method is deploying a third-party system utilized for numerical simulation and form a close loop with DCS by network communication. With the support of third-party equipment represented by the real-time target machine, the functions of the system can be flexibly expanded through the MODBUS series protocol, and algorithms with high sampling frequency requirements can be deployed. The method has the characteristics of economical communication consumption, standardized and reliable communication protocol, and flexible downloading models and algorithms mean. Aside from this, due to the relative independence from DCS, the distribute simulation method is promising to be an original platform for verifying the technology advanced control or fault diagnosis in addition to DCS computing servers.

HIL Simulation of a Tram Regenerative Braking System

Regenerative braking systems are an efficient way to increase the energy efficiency of electric rail vehicles. During the development phase, testing of a regenerative braking system in an electric vehicle is costly and potentially dangerous. For this reason, Hardware-In-the-Loop (HIL) simulation is a useful technique to conduct the system’s testing in real time where the physical parts of the system are replaced by simulation models. This paper presents a HIL simulation of a tram regenerative braking system performed on a scaled model. First, offline simulations are performed using a measured speed profile in order to validate the tram, supercapacitor, and power grid model, as well as the energy control algorithm. The results are then verified in the real-time HIL simulation in which the tram and power grid are emulated using a three-phase converter and LiFePO4 batteries. The energy flow control algorithm controls a three-phase converter which enables the control of energy flow within the regenerative braking system. The results validate the simulated regenerative braking system, making it applicable for implementation in a tram vehicle.

Test-Driven Design of Modulation Approaches for Grid-Tied Inverters

The paper presents an approach to evaluate modulation techniques in a Grid-Tied two-level Inverter using Test-Driven Design (TDD). It presents a set of tests that collect and calculate performance, harmonic, and power metrics of the inverter, based on IEEE Standards. The results are obtained by a Hardware-In-the-Loop (HIL) simulation and the TDD is applied with the pytest framework and Python language. The results of TDD procedure offer a structure to analyze different characteristics of the modulation approaches considering the Half-Bridge converter and the Space Vector, Sinusoidal and Carrier-Based algorithms.

Novel Human-in-the-Loop (HIL) Simulation Method to Study Synthetic Agents and Standardize Human–Machine Teams (HMT)

This work presents a multi-year study conducted at the University of Toledo, aimed at improving human–machine teaming (HMT) methods and technologies. With the advent of artificial intelligence (AI) in 21st-century machines, collaboration between humans and machines has become highly complicated for real-time applications. The penetration of intelligent and synthetic assistants (IA/SA) in virtually every field has opened up a path to the area of HMT. When it comes to crucial tasks such as patient treatment/care, industrial production, and defense, the use of non-standardized HMT technologies may pose a risk to human lives and cost billions of taxpayer dollars. A thorough literature survey revealed that there are not many established standards or benchmarks for HMT. In this paper, we propose a method to design an HMT based on a generalized architecture. This design includes the development of an intelligent collaborative system and the human team. Followed by the identification of processes and metrics to test and validate the proposed model, we present a novel human-in-the-loop (HIL) simulation method. The effectiveness of this method is demonstrated using two controlled HMT scenarios: Emergency care provider (ECP) training and patient treatment by an experienced medic. Both scenarios include humans processing visual data and performing actions that represent real-world applications while responding to a Voice-Based Synthetic Assistant (VBSA) as a collaborator that keeps track of actions. The impact of various machines, humans, and HMT parameters is presented from the perspective of performance, rules, roles, and operational limitations. The proposed HIL method was found to assist in standardization studies in the pursuit of HMT benchmarking for critical applications. Finally, we present guidelines for designing and benchmarking HMTs based on the case studies’ results analysis.