This demo highlights the model-based design (MBD) workflow for a low-cost segway robot. The mechanical and electrical parts of the robot are modeled using Simscape and the parameters of the models are adjusted to experimental values using Simulink design optimization. Based on the digital twin representation, control algorithms for high and low-level control are implemented, which can be simulated in Simscape or directly deployed to the hardware using automatic code generation.
- Physical modeling of a motor with Simscape electrical
- App based parameter optimization of Simscape model
- Hardware connectivity with Arduino and Raspberry Pi (Sensors and Motor)
- Built-in and custom drivers for hardware
- Automatic code generation and deployment
- Tuning PID Controller using App
- Design of LQR controller for balancing
- High-level state machine control with Stateflow
- Raspberry-Websocket for interactive control of the robot
Only the most relevant content is desribed here
- Sigi_Controls_Gitlab.prj -> Project file
- Cache, Code -> used by project for cache and autogenerated code
- Demo -> Contains project video and dashboard for use with live demo
- Models -> contains the Simulink model highlighting the workflow
- Scripts -> MBD educational material on how to configurate/callibrate a new robot
- Sources -> hardware drivers
- Specs -> Documentation of the hardware