Merge branch 'test_ex_singletrack'

Author: lucasrm25

Presentation.pdf

@@ -36,7 +36,7 @@ and it is trained (hyperparameter optimization) by maximizing the log Likelihood
 ### Results
 
 
-| NMPC controller with unmodelled dynamics        | Adaptive NMPC controller (with trained Gaussian Process)         |
+| NMPC controller with unmodelled dynamics        | Learning-Based NMPC controller (with trained Gaussian Process)         |
 | ------------- |-------------|
 | <img src="./simresults/trackAnimVideo-16-Jan-2020-without-GP.gif" alt="drawing" width="400"/>      | <img src="./simresults/trackAnimVideo-16-Jan-2020-with-GP-optimized.gif" alt="drawing" width="400"/>    |
 

README.md

@@ -354,7 +354,7 @@ function optimizeHyperParams(obj, method)
 
         function logL = loglikelihood(obj, outdim, M, var_f, var_n)
         %------------------------------------------------------------------
-        % calculate the log likelihood: log(p(Y|X,theta)),
+        % calculate the negative log likelihood: -log(p(Y|X,theta)),
         %      where theta are the hyperparameters and (X,Y) the training data
         %------------------------------------------------------------------         
             Y = obj.Y(:,outdim);