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It contains the properties needed for modeling the quadrotor, the initial conditions for the simulation, and the equilibrium values used for control. This is a file containing a struct of parameters. The function returns the updated A matrix. The last section uses the current states (or trajectory states when following a trajectory) as equilibrium. The 2nd uses the current R as equilibrium and works the best for this simulation. The 1st section allows you to use a static A matrix based off all true equilibrium values.

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Inside the code are 3 sections which can be used, 2 of which should always be commented out.

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This function is used by the controller to update the A state-space matrix based of the current states. Handles are used with each plotting object so as to not replot but rather update the objects information. The inputs are the current position and attitude of the quadcopter. This function animates the quadcopter simulation. This was done to model the Lie Group kinematics more accurately. This rotation matrix is shaped into a column vector with 9 elements and is reshaped inside of the animation and controller back into a 3x3 rotation matrix. This is because all 9 parameters of the SO(3) rotation matrix are used as states.

Note that the Lie Group dynamics function has 18 states and outputs rather than 12. The inputs are the 4 motor commands and the outputs are all of the current states used in the feedback loop and in the animation. This s-function models the plant in Simulink. Note that the A of the current time step is not updated as MPC predicts into the future as this is much more computationally expensive. This function calls getA() to update the A state-space matrix at every time step. The output of this function is 4 throttle commands, 1 for each motor of the quadcopter. It takes in the reference commands, current states, and curret time then uses MPC to calculate the desired control effort. This function is called in Simulink in the controller block. The reference commands are easily adjustable to fly different paths if desired. The Simulink can be opened within MATLAB and all you should have to do is click run to see the simulation. Both of these directories contain similar code files and 1 simulink (.slx) file each. This repo contains 2 directories: Lie_Group and Euler_Angles.

QUADCOPTER SIMULINK MODEL DOWNLOAD HOW TO

Here is a link to the download: How to Use This with automatically set it up for you. After downloading the toolbox, open MATLAB, navigate to the directory with the toolbox download, and double-click the toolbox download inside of MATLAB. This repo uses some of the functions from Peter Corke's Robotics Toolbox for MATLAB.

To open the simulink files, you must be using MATLAB 2018a or newer. It is used to solve the optimization in the MPC controller.

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CVXGEN is an online code generator for convex optimization. This repo uses code gererated from CVXGEN with an academic use only license. It can be seen that, since the Lie Group representation works on the manifold when controlling heading, it always spins the shortest distance to get to the desired heading and has no angle wrapping issues. Both simulations have been tested and tuned (at least a decent amount) to fly an hourglass/figure-8 waypoint path. One simulation uses Euler angles (roll,pitch,yaw) to represent attitude while the other uses the Lie Group SO(3) representation. This repo has 2 functional MATLAB simulations of a quadcopter using an MPC controller.

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