jaeandersson

/*
 *    This file is part of CasADi.
 *
 *    CasADi -- A symbolic framework for dynamic optimization.
 *    Copyright (C) 2010 by Joel Andersson, Moritz Diehl, K.U.Leuven. All rights reserved.
 *
 *    CasADi is free software; you can redistribute it and/or
 *    modify it under the terms of the GNU Lesser General Public
 *    License as published by the Free Software Foundation; either
 *    version 3 of the License, or (at your option) any later version.

jaeandersson

#include <iostream>
#include <fstream>
#include <ctime>
#include <iomanip>
#include <symbolic/casadi.hpp>
#include <symbolic/stl_vector_tools.hpp>

using namespace CasADi;
using namespace std;

jaeandersson

classdef Circle < Shape
  methods
    function self = Circle(varargin)
      self@Shape('_swigCreate',uint64(0),false);
      if nargin==3 && ischar(varargin{1}) && strcmp(varargin{1},'_swigCreate')
        self.swigCPtr = varargin{2};
        self.swigOwn = varargin{3};
      else
        % How to get working on C side? Commented out, replaed by hack below
        %self.swigCPtr = example_wrap('new_Circle',varargin{:});

jaeandersson

import numpy as NP
import casadi as C
def qpsolve(H,g,lbx,ubx,A=NP.zeros((0,0)),lba=NP.zeros(0),uba=NP.zeros(0)):
    # Convert to CasADi types
    H = C.DMatrix(H)
    g = C.DMatrix(g)
    lbx = C.DMatrix(lbx)
    ubx = C.DMatrix(ubx)
    A = C.DMatrix(A)
    A = A.reshape((A.size1(),H.size1())) # Make sure matching dimensions

jaeandersson

from pylab import *

# End time
T = 10.

# Number of control intervals
N = 20

# Number of Runge-Kutta 4 steps per interval and step size
NK = 20

jaeandersson

from casadi import *
from numpy import *
import matplotlib.pyplot as plt

N = 20      # Control discretization
T = 10.0    # End time

# Declare variables (use scalar graph)
u  = SX.sym("u")    # control
x  = SX.sym("x",2)  # states

jaeandersson

from casadi import *
from numpy import *
import matplotlib.pyplot as plt

N = 20      # Control discretization
T = 10.0    # End time

# Declare variables (use scalar graph)
u  = SX.sym("u")    # control
x  = SX.sym("x",2)  # states

jaeandersson

#import casadi
import numpy
from casadi import *

# Initial and final position
px0 = 0.0;  py0 = 1.5
pxF = 20.0; pyF = 0.0

# Time horizon and discretization
T = 3.0

jaeandersson

from casadi import *
from casadi.tools import *

import numpy
from numpy import cos,sin, vstack, hstack, multiply

class Quadcopter:
  """
   
   Quadcopter model

jaeandersson

import numpy as NP
from casadi import *

# Choose collocation points
d = 4  # Degree
tau_root = collocationPoints(d,"legendre")

# Calculate coefficients
C = DMatrix.nan(d+1,d+1)  # For the collocation equation
D = DMatrix.nan(d+1)      # For the continuity equation