Real-Time Implementation Examples
For implementations in many real-time simulation and testing areas, pairing Simulink Real-Time with one or more additional products can ease implementation development. This category provides links to examples that demonstrate implementations for various market segments. For more examples that use Speedgoat Target Machines, see Speedgoat Application Examples. To explore the wide range of product capabilities and find the solution that is right for your application or industry, see these solution areas:
Control Systems — For open-loop or feedback control systems, you can develop a real-time application that helps you test and simulate your system. For more information about control systems, see MATLAB and Simulink for Control Systems.
Robotics and Autonomous — From perception to motion, real-time applications can be part of your robotics to design, simulate, and verify every aspect of your autonomous systems. For more information, see MATLAB and Simulink for Robotics and Autonomous Systems.
Image Processing and Computer Vision — Real-time application can implement image processing and computer vision systems that respond to image and video data, apply algorithms, and help you explore implementation tradeoffs. For more information, see MATLAB for Image Processing and Computer Vision.
Power Electronics — For control of IGBTs, power MOSFETs, and other solid-state power electronics, you can design a real-time digital controller with simulation that helps ensure stability, improves power quality, optimizes dynamic performance, and handles fault conditions. For more information, see Electrification.
Signal Processing — From analyzing signals and exploring algorithms to evaluating design implementation tradeoffs, a real-time signal processing systems eases your simulation and test processes. For more information, see MATLAB and Simulink for Signal Processing.
FPGA Solutions — Real-time simulation and testing helps you generate processor-optimized C/C++ code for your target embedded processors and verify your algorithm running in an HDL simulator or on an FPGA or SoC device. For more information, see MATLAB for FPGA, ASIC, and SoC Development.