Develop embedded software, optimize the operation, and predict
Engineers in the automated material handling industry use Model-Based Design from equipment design to operation.
With MATLAB® and Simulink®, you can:
- Develop advanced autonomous and control algorithms by systematic use of digital models throughout the development process
- Improve software quality with automatic generation of real-time code (IEC 61131-3 or C/C++)
- Optimize and verify machine software in simulation by virtual commissioning
- Develop and deploy condition monitoring and predictive maintenance software to embedded, cloud, and edge systems
Control and Autonomous Design
Model-Based Design is a mathematical and visual approach for developing complex autonomous and control systems, enabling you to use digital models from design, analysis, and simulation to automatic code generation and verification. You can use Model-Based Design in automated material handling applications like pick-and-place, motion control, autonomous algorithm with AI, and vibration suppression for a robot arm, AGV, stacker crane, and more. Through virtual prototyping, you can also analyze system performance before the manufactured hardware is available for testing.
- Politecnico di Torino Graduate Student Demonstrates Value of Physical Modeling and Dynamic Simulation to Industry Partner Comau
- Ricoh Develops a Detailed Model for Robot Actuator Design
- Mitsubishi Heavy Industries Develops Robotic Arm for Removing Nuclear Fuel Debris
- Implementation Verification of Picking System for Industrial Robot Using ROS and MATLAB
Automatic Code Generation
You can generate code like C, C++, CUDA®, Verilog®, VHDL®, and Structured Text, from digital models. Production code generation is available for PLCs and industrial controllers working with Ladder, Structured Text, and C. Simulink PLC Coder™ helps you reduce hand-coding and human errors by automatic code generation of IEC 61131-3 Ladder Diagrams and Structured Text. It also supports widely used third-party integrated development environments (IDEs).
Simulink PLC Coder generates test benches that help you verify the Structured Text and Ladder Diagrams using PLCs and simulation tools. It also provides code generation reports with static code metrics and bidirectional traceability between model and code. The field of automated material handling uses numerous PLCs globally. With Simulink PLC Coder, you can select the deployment target and deploy the software to various PLCs.
Using MATLAB and Simulink for virtual commissioning of machines can save you time because it allows for early verification and validation of machine software with digital models using desktop and real-time simulation before you test with real hardware. Virtual commissioning lets you improve software quality, test in various scenarios, and offer component interaction before testing with real hardware. With virtual commissioning, you can also tune the control parameters before final commissioning with real hardware (e.g., stacker crane, OHT vehicle) to avoid vibration and sway suppression control.
With predictive maintenance, you can maintain operational industrial assets such as pick-and-place robots, conveyors, and stacker cranes using digital models (e.g., digital twin). These digital models use sensor data and other relevant information to detect anomalies, monitor the health of components, and estimate remaining useful life (RUL).
You can use MATLAB, Simulink, and Predictive Maintenance Toolbox™ to develop and deploy condition monitoring and predictive maintenance software to cloud systems and edge devices.
Using MATLAB and Simulink for Material Handling Equipment
“With Simulink and HDL Coder we eliminated programming errors and automated delay balancing, pipelining, and other tedious and error-prone tasks. As a result, we were able to easily and quickly implement change requests from our customers and reduce time-to-market.”Ronald van der Meer, 3T