Embed is model-based design software for developing algorithms for complex embedded systems. It offers thousands of pre-built models that cover a wide range of engineering disciplines, with search to identify a model that matches your design requirements, and broad target support.
The Embed library of motor models and motor control algorithms, for both sensored and sensorless applications, provides the starting point to accelerate embedded motor control projects for any type of electric motor, including AC induction, BLDC, PMSM, brushed DC, or stepper motors.
Embed provides hundreds of digital power models to quickly convert analog designs to digital designs and develop compensator algorithms. The library includes blocks and examples for simulation and code generation of power supply, digital power components, and controls to shorten embedded software development.
With Embed, users can easily model and simulate end-to-end, physical layer data communication systems providing determination of energy and bit required for a given bit error rate for a comprehensive set of modulation, encoding, and channel configuration.
Embed is commonly used in IoT, satellite communications, RF systems, home automation, academia, aerospace and automotive industries as a platform for visualizing the key aspects of communication systems, digital waveforms, and their associated signal processing concepts.
For plant emulation, Embed offers an efficient way to create real-time digital twins for commissioning, tuning, and operator training. Use open platform communications (OPC) to verify plant behavior and connect to PLC networks including human-machine interfaces (HMI). Reduce product variability, increase process uptime, and maximize asset utilization.
Embed can be utilized to develop firmware for energy efficient, low-cost microcontrollers, supporting Kafka, MQTT, JSON, and other technologies. With Embed, you can be confident your IoT embedded system is production-ready.
Use image processing to manipulate and analyze digital assets for a variety of applications including industrial inspection and control, facial and gesture recognition, surveillance and security, traffic monitoring, autonomous driving, medical image analysis.
Use Embed to test and build a variety of deep neural network (DNN) algorithms on the PC and then generate code to implement the inference engine on an embedded target. Embed’s supported algorithms include: Caffe, Darknet, TensorFlow, DLDT, ONNX, and Torch.
Altair Embed can simulate, analyze, and automatically generate efficient code that can be downloaded, executed, and debugged on over 1,200 microprocessors, including STM32, TI C2000 and MSP430, Arduino, Raspberry Pi, and many more.
Step by Step instructions to install the Texas Instruments Code Composer Studio and Uniflash software on your computer.
Quick Start
This webinar, hosted by IEEE, focuses on Motor Control using Embed
To assist Kappa Electronics’ customer with controlling the motor for a new drone design, Altair’s solidThinking Embed was used for high speed simulation of.
Customer StoriesAltair Embed is an intuitive graphical environment for model-based embedded development. Diagrams are automatically converted to highly-optimized and compact.
