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README.md

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Steps to Install acados:

clone the repo in the home/user directory and cd into the capracontrol directory.

1. Initialize acados submodule:

git submodule update --recursive --init

2. Move to the acados directory and build it:

cd ~/dtmpc/src/mpc/acados
mkdir -p build
cd build
cmake -DACADOS_WITH_QPOASES=ON ..
make install -j4
cd ~/dtmpc/

3. Install the acados_template interface python libary.

sudo apt install python3-pip
cd ~/dtmpc/src/mpc/acados/
pip install -e interfaces/acados_template
cd ~/dtmpc/

3.5 Do this step if you use acados on non-standard computer architecture (such as a rasperry pi)

cd ~/dtmpc/
sudo apt  install cargo  
cd ~/dtmpc/src/mpc/acados/
git clone https://github.com/acados/tera_renderer.git
cd tera_renderer
cargo build --verbose --release
cd target/release/
cd ~/dtmpc/src/mpc/acados/
cp tera_renderer/target/release/t_renderer bin/
cd ~/dtmpc/

4. set environment variables and run the python simulation:

Very important note. You must source each time you run the simulation. Each time you start up there is no need to build and install the code. Just run these lines and the libary is setup.

source setup_acados.sh

5. check if the installation is correct.

source setup_acados.sh
cd ~/dtmpc
python3 src/mpc/acados/examples/acados_python/getting_started/minimal_example_ocp.py

If you a graph with states and control input over time to reach a set point then it works.

Error codes for NLP solver:

  1. ACADOS_SUCCESS,
  2. ACADOS_FAILURE,
  3. ACADOS_MAXITER,
  4. ACADOS_MINSTEP,
  5. ACADOS_QP_FAILURE,
  6. ACADOS_READY,

Error codes for QP Solver:

  1. SUCCESS, // found solution satisfying accuracy tolerance
  2. MAX_ITER, // maximum iteration number reached
  3. MIN_STEP, // minimum step length reached
  4. NAN_SOL, // NaN in solution detected
  5. INCONS_EQ, // unconsistent equality constraints