write readme of mpc

mpc/README.md

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+# Model Predictive Control Tool
+This program is about template, function of linear model predictive control
+
+# Documentation of this function
+Linear model predicitive control should have state equation.
+So if you want to use this function, you should model the plant as state equation.
+Therefore, the parameters of this class are as following
+
+Parameters :
+
+- A : numpy.ndarray
+     - system matrix
+- B : numpy.ndarray
+    - input matrix
+- Q : numpy.ndarray
+    - evaluation function weight
+- R : numpy.ndarray
+    - evaluation function weight
+- pre_step : int
+    - prediction step
+- dt_input_upper : numpy.ndarray
+    - constraints of input dt
+- dt_input_lower : numpy.ndarray
+    - constraints of input dt
+- input_upper : numpy.ndarray
+    - constraints of input
+- input_lower : numpy.ndarray
+    - constraints of input
+
+We have two function, mpc_func_with_cvxopt.py and mpc_func_with_scipy.py
+Both function have same variable and member function. however the solver is different. 
+Plese choose the right method for your environment
+
+## Example
+# Problem Formulation and Expected results
+
+- updating soon!!
+
+# Usage
+
+- for example
+
+```
+$ python main_example.py
+```
+
+- for comparing two methods
+
+```
+$ python test_compare_methods.py
+```
+
+# Requirement
+
+- python3.5 or more
+- numpy
+- matplotlib
+- cvxopt
+- scipy1.2.0 or more
+
+# Reference
+I`m sorry that main references are written in Japanese
+
+- モデル予測制御―制約のもとでの最適制御 著：Jan M. Maciejowski　訳：足立修一　東京電機大学出版局