Hi Krishnan,
I see you are working on optimizing a Simulink model for unpowered flight to demonstrate dynamic soaring phenomen and you are looking to increase the range by adjusting the control surfaces.
To create a function that maximizes the distance traveled, you’ll need to set up an optimization problem. Here’s a high-level approach:
- Objective Function: This is the function you want to maximize or minimize. In your case, it’s the distance traveled by the aircraft. You’ll need to create a function that calculates this distance based on the aircraft’s flight path.
- Design Variables: These are the variables you’ll be changing in order to optimize the objective function. In your case, these could be the angles or positions of the control surfaces.
- Constraints: These are the limits within which the design variables can change. For example, the angles of the control surfaces likely have a minimum and maximum value.
- Optimization Algorithm: This is the method by which you’ll iteratively adjust the design variables to find the optimal solution. There are many algorithms to choose from, such as gradient descent, genetic algorithms, or even machine learning-based methods.
For further assistance, check the following reference to know about:
- Simulink Optimization Blockset documentation: https://www.mathworks.com/products/sl-design-optimization.html
Hope this gives help you to create the function.
