Model-Based Design for Space Control Systems
Model-Based Design for Space Control Systems
Imagine that your team is developing the power system of a satellite. The system incorporates a combination of physical elements (e.g., battery, solar panels), control logic, and external conditions (e.g., temperature, radiation). Before you begin the design, you want to address some key questions—for example:
• How do we size the batteries?
• What if the requirements change?
• How can we optimize the design to ensure the desired performance?
• How can we test the design thoroughly while minimizing risk?
Whether you’re developing controls for a flight system, an industrial robot, a wind turbine, a production machine, an autonomous vehicle, an excavator, or an electric servo drive, if your team is manually writing code and using document-based requirements capture, the only way to answer these questions will be through trial and error or testing on a physical prototype. And if a single requirement changes, the entire system will have to be recoded and rebuilt, delaying the project by days, or even weeks.
Using Model-Based Design with MATLAB® and Simulink®, instead of handwritten code and documents, you create a system model—a model incorporating the physical model, the control algorithms, and the environment. You can simulate the model at any point to get an instant view of system behavior and to test out multiple what-if scenarios and tradeoff analyses without risk, without delay, and without reliance on costly hardware.
This white paper introduces Model-Based Design and provides tips and best practices for getting started. Using real-world examples, it shows how teams across industries have adopted Model-Based Design to reduce development time, minimize component integration issues, and deliver higherquality products.
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By Mathworks
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