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 # Distributed Minimax Adaptive Control
 
 ## Description
-This code explains the implementation of distributed minimax adaptive control algorithm
+This code explains the implementation of distributed minimax adaptive control algorithm designed for controlling uncertain networks
 
 ## Associated Paper
-V. Renganathan, Anders Rantzer and Olle Kjellqvist, `Distributed Minimax Adaptive Control for Uncertain Networks`, Submitted to ACC-LCSS 2024. 
+V. Renganathan, Anders Rantzer and Olle Kjellqvist, `Distributed Minimax Adaptive Control for Uncertain Networks`, Submitted to European Control Conference 2024. 
 
 ## Dependencies
 Please download and include the source files of package that converts MATLAB to tikz into the path. 
@@ -13,11 +13,10 @@ The package can be found in https://www.mathworks.com/matlabcentral/fileexchange
 ## Steps to run the simulation
 The main file to be run in MATLAB is the `DistributedMinimaxAdaptiveControl.m` file. Please follow the following steps in running the file.
 
-- In line 31, set the `dataPrepFlag` to 1 if new network data has to be generated. Set it to 0, if you want to preload the already generated network dynamics data.
-- In line 77, set the number of models to be prepared using the variable `numModels`
-- In line 205, set the index of the true dynamics model using the variable `modelNum`
-- In line 213, set the `disturbFlag`. Choose 0: none, 1: white noise, 2: sinusoid, 3: constant step
-- 
+- Set the `dataPrepFlag` to 1 if new network data has to be generated. Set it to 0, if you want to preload the already generated network dynamics data.
+- Set the number of models to be prepared using the variable `numModels`
+- Set the index of the true dynamics model using the variable `modelNum`
+- Set the `disturbFlag`. Choose 0: none, 1: white noise, 2: sinusoid, 3: constant step
 
 ## License
 MIT License: