CAGE User's Guide

Creating an Optimization from Your Own Algorithm

The CAGE optimization feature allows you to use your own optimization algorithms as alternatives to the library routines foptcon and NBI.

Using an example, this tutorial illustrates how to take an existing optimization algorithm and implement it as an optimization function for use in CAGE optimization.

The problem to be solved is the worked example problem:

Maximize torque (TQ) over the free variables (SPK, AFR) over a specified set of (N, L) points. These points are defined in the data set New_Dataset, which can be found in the CAGE session optimworkedexample.cag.

The torque model to be used is that in /mbctraining/Holliday.mat.

Process Overview

1. Start with your own algorithm. We provide an example.
2. Create a CAGE optimization function.
3. Define the attributes of your optimization in the CAGE optimization function.
4. Add your algorithm to the CAGE optimization function.
5. Register your completed optimization function with CAGE.
6. Verify the optimization.

The steps of this tutorial lead you through a series of examples illustrating how to construct the code to incorporate your own algorithm into an optimization in CAGE.

Before you begin you must create a working directory.

1. Create a new folder (for example, C:\Optimization_Work). We recommend that you place this directory outside your MATLAB folders to avoid interfering with toolbox files.
2. Copy the following six files from the mbctraining directory into your new working folder:

• currtutoptim.m
  mbcOStemplate.m
  mbcOStutoptimfunc.m
  mbcOStutoptimfunc_s1.m
  optimtut.mat
  optimtuteg.mat
  

3. Make sure your new working directory is on the MATLAB path.
1. Select File -> Set Path.
2. Click Add Folder and browse to your working directory.
3. Click OK.
4. Click Save.

Step 1: Examine the Algorithm

1. Open currtutoptim.m from the mbctraining directory. currtutoptim.m is an optimization algorithm that solves the worked example problem in the MATLAB workspace. You should see the following code in the MATLAB editor.

   

2. Verify that this algorithm solves the worked example problem by typing the following commands at the MATLAB prompt:

• load optimtuteg.mat;
  bestX = currtutoptim(x0, data)
  

The workspace output should resemble

• BestX =      
         23.768        12.78
         18.179        12.78
         14.261        12.78
         12.014        12.78
         11.439        12.78
         12.535        12.78
         27.477        12.78
         21.887        12.78
         17.969        12.78
         15.722        12.78
         15.147        12.78
         16.243        12.78
         31.185        12.78
         25.595        12.78
         21.677        12.78
          19.43        12.78
         18.855        12.78
         19.951        12.78
         34.893        12.78
         29.303        12.78
         25.385        12.78
         23.138        12.78
         22.563        12.78
         23.659        12.78
         38.601        12.78
         33.012        12.78
         29.093        12.78
         26.847        12.78
         26.271        12.78
         27.368        12.78
         42.309        12.78
          36.72        12.78
         32.802        12.78
         30.555        12.78
         29.979        12.78
         31.075        12.78
  

The matrix bestX contains the optimal SPK and AFR values that maximize the MBC model torque (exported from Holliday.mat) at the speed and load points defined in the matrix data.

currtutoptim.m is the example optimization algorithm that you want to transfer to the CAGE optimization feature.

This tutorial shows how to make currtutoptim.m available for use in the CAGE optimization feature.

Using the Worked Example Optimization

Step 2: Create a CAGE Optimization Function