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®: Dynamic System Simulation for MATLAB®
Published in Perelroyzen Evgeni, Digital Integrated Circuits, 2018
Despite the extensive functional potential of Simulink Block Libraries, Simulink is, nevertheless, just a MATLAB component and can operate only under its control. To overcome the inseparability of a Simulink-generated model and the development environment, Simulink incorporates the tool called Real-Time Workshop (RTW). This tool provides for the creation of Simulink model–based software (in our context, test benches) intended for the real-time control of target-specific hardware (in our context, ATE [automated test equipment]). RTW’s major functional features are: The ability to generate program code from any Simulink model (the only limitation is induced by MATLAB Fcn Block and S-function Block) that should be preliminarily converted into MEX-files (Figure 1.89) [5] Use of an expandable library of device driversAn automatic and fully customized software development processUnification of components controlled by various operating systemsProgram code generation for any standard (conforming to the ANSI requirements) C-Language compiler
From Virtual to Real—A Progressive Simulation-Based Design Framework
Published in Gabriel A. Wainer, Pieter J. Mosterman, Discrete-Event Modeling and Simulation, 2018
Using simulation to support software design is adopted by several projects and tools for designing embedded software. The Ptolemy project [23,24] provides a component-based framework to express various computational models related to the embedded systems. It supports modeling of interactions between sets of components that are represented by different computational models. Simulink® [25] is a commercial tool that provides an extensive graphical interface to MATLAB® [26] for interactive modeling and functional simulation. It promotes a paradigm of Simulation and Model-Based Design [27] for designing and testing embedded control and signal processing software. Both Ptolemy and Simulink support implementation of embedded software using code generation from simulation models. However, a systematic process that progressively transitions a design from virtual to real is not well studied. For large-scale distributed real-time systems that have complex software, hardware, and physical operating environments, there is a need for systematic transitions from simulation models to real system implementation and measurement.
Wireless Hardware-in-the-loop Simulator
Published in Tran Duc Chung, Rosdiazli Ibrahim, Vijanth Sagayan Asirvadam, Nordin Saad, Sabo Miya Hassan, TM, 2017
Tran Duc Chung, Rosdiazli Ibrahim, Vijanth Sagayan Asirvadam, Nordin Saad, Sabo Miya Hassan
The architecture of WH-HILS is presented in Figure 9.1. In the figure, the simulator essentially consists of a WirelessHART gateway (LTP5903CEN-WHR), several wireless nodes (DC9003-A), and a computer. The gateway with an embedded access point serves as the network and security manager, and as the source of network information. This gateway communicates with other nodes in burst mode in which, if a device is busy, the received message will be placed in queue and the communication can be continued. The nodes function as wireless field devices installed at process plants. In addition, each of them can serve as a relay for routing messages to other nodes in a multi-hop network. The controller and process plant functionalities can be developed and integrated into the computer using MATLAB®. By using Real-time Sync block in Simulink, the simulation is synchronized with the computer’s clock, thus it can be run in real-time. For interfacing with the gateway, a Python program is used. This interface is natively supported by MATLAB®2015 and later versions and is described in detail in the following section. Currently, the supported Python versions are 2.7, 3.3, and 3.4 [182].
Adaptive differential evolution tuned hybrid fuzzy PD-PI controller for automatic generation control of power systems
Published in International Journal of Ambient Energy, 2022
Jagan Mohana Rao Chintu, Rabindra Kumar Sahu, Sidhartha Panda
The new contributions of the current work are: Hybrid fuzzy PD-PI controller is suggested first time in AGC.An adaptive DE technique is employed where Crossover Constant (Cr) and Scaling Factor (F) are varied during the search process.The advantages of proposed ADE technique-based hybrid fuzzy PD-PI controller is demonstrated over other recent approaches for the similar test systems.Stability analysis is done under varied conditions using gain and phase margins (PM).Robustness of suggested hybrid fuzzy PD-PI controller is investigated by considering the random load pattern.For experimental validation of the proposed approach, the Matlab/Simulink results are compared with Hardware-in-the-Loop (HiL) real-time simulation results.
A proof-of-concept field experiment on cooperative lane change maneuvers using a prototype connected automated vehicle testing platform
Published in Journal of Intelligent Transportation Systems, 2021
Kelli Raboy, Jiaqi Ma, Edward Leslie, Fang Zhou
Simulink is a graphical programing tool developed by MathWorks that acts as a companion to their MATLAB computation software. Simulink’s visual nature enables rapid prototyping of algorithms or logic while making it easy to visualize relationships between functions and data flow. Simulink acts as the framework for much of the software running on the MAB, both the control algorithm and various vehicle interfaces. In cases where using Simulink alone would have made specific software components challenging to create, the research team implemented the logic in standard C code and integrated that code directly with the rest of the Simulink code. The Simulink Coder toolbox was used to compile the Simulink model down to C code before using a cross-compiler to create the binary that could run on the MAB.
Assessment of emergency sourcing strategy of a supply chain through dynamic simulation approach
Published in Journal of Industrial and Production Engineering, 2020
Vempiliyath A. Thomas, Biswajit Mahanty
The model discussed above is integrated numerically in Matlab Simulink®. Simulink is a graphical program platform for modeling, simulation, and analysis of dynamical systems. Since it facilitates integration with other Matlab environments, we get more flexibility in modeling and analysis through scripting, adding customizable blocks and using different control theory techniques. Hence a more detailed analysis of SD model is possible through Simulink platform with the help of above-mentioned options. The differential equations used in the model are represented using the Laplace transform in the Simulink model.