12345qiupeng
/
mpc_python_learn
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

fixed equations spacing in notebook, updated gitignore

master
mcarfagno 2020-04-07 16:51:12 +01:00
parent b3593ab100
commit 31ca324a26
3 changed files with 9 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
.gitignore vendored
View File

@ -1,2 +1,3 @@
*.pyc
/notebook/.ipynb_checkpoints
.ipynb_checkpoints

8
notebook/.ipynb_checkpoints/MPC_cvxpy-checkpoint.ipynb
View File

@ -827,14 +827,14 @@
"\\begin{aligned}\n",
"\\min_{} \\quad & \\sum^{t+T-1}_{j=t} x^T_{j|t}Qx_{j|t} + u^T_{j|t}Ru_{j|t}\\\\\n",
"\\textrm{s.t.} \\quad & x(0) = x0\\\\\n",
" & x_{j+1|t} = Ax_{j|t}+Bu_{j|t}) \\quad \\textrm{for} t<j<t+T-1 \\\\\n",
" & x_{j+1|t} = Ax_{j|t}+Bu_{j|t}) \\quad \\textrm{for} \\quad t<j<t+T-1 \\\\\n",
"\\end{aligned}\n",
"\\end{equation}\n",
"$\n",
"\n",
"Other linear constrains may be applied,for instance on the control variable:\n",
"\n",
"$ U_{MIN} < u_{j|t} < U_{MAX} \\quad \\textrm{for} t<j<t+T-1 $\n",
"$ U_{MIN} < u_{j|t} < U_{MAX} \\quad \\textrm{for} \\quad t<j<t+T-1 $\n",
"\n",
"The objective fuction accounts for quadratic error on deviation from 0 of the state and the control inputs sequences. Q and R are the **weight matrices** and are used to tune the response.\n",
"\n",
@ -861,14 +861,14 @@
"\\begin{aligned}\n",
"\\min_{} \\quad & \\sum^{t+T}_{j=t} C(x_{j|t},{j|t})\\\\\n",
"\\textrm{s.t.} \\quad & x(0) = x0\\\\\n",
" & x_{j+1|t} = f(x_{j|t},u_{j|t}) \\quad \\textrm{for} t<j<t+T-1 \\\\\n",
" & x_{j+1|t} = f(x_{j|t},u_{j|t}) \\quad \\textrm{for} \\quad t<j<t+T-1 \\\\\n",
"\\end{aligned}\n",
"\\end{equation}\n",
"$\n",
"\n",
"Other nonlinear constrains may be applied:\n",
"\n",
"$ g(x_{j|t},{j|t})<0$ for $t<j<t+T-1 $"
"$ g(x_{j|t},{j|t})<0 \\quad \\textrm{for} \\quad t<j<t+T-1 $"
]
},
{

8
notebook/MPC_cvxpy.ipynb
View File

@ -827,14 +827,14 @@
"\\begin{aligned}\n",
"\\min_{} \\quad & \\sum^{t+T-1}_{j=t} x^T_{j|t}Qx_{j|t} + u^T_{j|t}Ru_{j|t}\\\\\n",
"\\textrm{s.t.} \\quad & x(0) = x0\\\\\n",
" & x_{j+1|t} = Ax_{j|t}+Bu_{j|t}) \\quad \\textrm{for} t<j<t+T-1 \\\\\n",
" & x_{j+1|t} = Ax_{j|t}+Bu_{j|t}) \\quad \\textrm{for} \\quad t<j<t+T-1 \\\\\n",
"\\end{aligned}\n",
"\\end{equation}\n",
"$\n",
"\n",
"Other linear constrains may be applied,for instance on the control variable:\n",
"\n",
"$ U_{MIN} < u_{j|t} < U_{MAX} \\quad \\textrm{for} t<j<t+T-1 $\n",
"$ U_{MIN} < u_{j|t} < U_{MAX} \\quad \\textrm{for} \\quad t<j<t+T-1 $\n",
"\n",
"The objective fuction accounts for quadratic error on deviation from 0 of the state and the control inputs sequences. Q and R are the **weight matrices** and are used to tune the response.\n",
"\n",
@ -861,14 +861,14 @@
"\\begin{aligned}\n",
"\\min_{} \\quad & \\sum^{t+T}_{j=t} C(x_{j|t},{j|t})\\\\\n",
"\\textrm{s.t.} \\quad & x(0) = x0\\\\\n",
" & x_{j+1|t} = f(x_{j|t},u_{j|t}) \\quad \\textrm{for} t<j<t+T-1 \\\\\n",
" & x_{j+1|t} = f(x_{j|t},u_{j|t}) \\quad \\textrm{for} \\quad t<j<t+T-1 \\\\\n",
"\\end{aligned}\n",
"\\end{equation}\n",
"$\n",
"\n",
"Other nonlinear constrains may be applied:\n",
"\n",
"$ g(x_{j|t},{j|t})<0$ for $t<j<t+T-1 $"
"$ g(x_{j|t},{j|t})<0 \\quad \\textrm{for} \\quad t<j<t+T-1 $"
]
},
{