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The Project involves 3 typical convex optimization problems in control and the SDP (Semi-definite Programming) form or in other words the LMI (Linear Matrix Inequalities) form of each problem is achieved analytically and then the SDP optimization problems are solved in MATLAB using MATLAB CVX toolbox.

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3 Typical Convex Optimization Problems In Control And How To Solve Them Analytically And Finally Implement In MATLAB

This was a solution to homework 2 of my convex optimization university course. The Project involves 3 typical convex optimization problems in control and the SDP (Semi-definite Programming) form or in other words the LMI (Linear Matrix Inequalities) form of each problem is achieved analytically and then the SDP optimization problems are solved in MATLAB using MATLAB CVX toolbox. Note that you need to download the CVX toolbox from its distributer and MATLAB doesn't have it pre-installed. The problems and their analytic and programming solution are all thoroughly explained in the report file.

The m file that you need to run is the Convex_Ex2.m file and the sf_sys.m file is just a matlab function needed for simulation in the main file.

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The Project involves 3 typical convex optimization problems in control and the SDP (Semi-definite Programming) form or in other words the LMI (Linear Matrix Inequalities) form of each problem is achieved analytically and then the SDP optimization problems are solved in MATLAB using MATLAB CVX toolbox.

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