Developing mechatronic systems requires integrating physical subsystems with control systems and embedded software. Engineers use Model-Based Design to model, simulate, and verify multidisciplinary mechatronic systems from initial development to production.
With MATLAB®, Simulink®, and Simscape™, you can:
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Use Simscape to develop system or component level models to represent the physical portions of the system in the electrical, mechanical, or fluid domains. Import designs from existing CAD files to visualize 3D physical components and SPICE subcircuits to incorporate manufacturer specific behavior. Optimize system performance and detect integration errors early in development via simulation. Repurpose simulation models for virtual commissioning or operational digital twins.
Linearize nonlinear physical models to develop closed-loop control systems with linear control techniques, like Bode plots or root locus, or use advanced control strategies, like model predictive control or robust control. Leverage prebuilt functions and interactive tools to automatically tune and optimize controllers to meet the performance requirements and stability constraints of your system. Analyze key performance and stability characteristics in the time and frequency domains such as overshoot, rise time, phase margin, and gain margin.
Develop and verify state machines for supervisory control and error handling. Use graphical animation to analyze and debug supervisory logic while it is executing to identify potential design errors.
Refine your algorithms with rapid control prototyping (RCP) to prepare for your production environment. Use hardware-in-the-loop (HIL) simulations of your plant and environment model to reduce physical prototypes. Run real-time simulations on Speedgoat hardware and analyze the results in MATLAB to improve the performance of your mechatronic system.
Eliminate manual coding errors by automatically generating optimized C, C++, IEC 61131-3 (Structured Text and Ladder Diagram), CUDA®, Verilog®, or VHDL code directly from MATLAB and Simulink. Leverage floating and fixed-point design tools to investigate performance tradeoffs. Integrate the generated hardware independent code into your PLC platform’s integrated development environment (IDE) for deployment on your real-time hardware and for online debugging.
Author, import, and manage requirements in your model to maintain traceability across designs, tests, and generated code. Prove that designs meet requirements, automatically generate test cases for model coverage, and improve the quality of designs throughout the development process using formal test methods. Check model and code compliance using formal methods and static analysis. Find bugs and prove the absence of critical run-time errors with static code analysis. Produce reports and artifacts necessary to certify to industry standards such as IEC 61508, ISO 26262, and DO-178.
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