A Python port of PiMPC.

Clone this repository

git clone https://github.com/shaoanlu/PiMPC-python.git

And install in edit mode

pip install -e .

Refer to examples:

• examples/afti16_example.py (linear AFTI-16 aircraft model)
• examples/unicycle_nmpc_example.py (nonlinear unicycle with time-varying linearization)

Create a model, configure with Modelsetup(), and solve with Model.solve().

model = Model()
model.setup(A, B, Np, kwargs...)
results = model.solve(x0, u0, yref, uref, w, verbose=False)

Required Arguments:

• A: State matrix
• B: Input matrix
• Np: Prediction horizon

Optional Problem Arguments:

• C: Output matrix (default: I, meaning y = x)
• e: Affine term in dynamics (default: zeros)
• Wy: Output weight matrix (default: I)
• Wu: Input weight matrix (default: I)
• Wdu: Input increment weight matrix (default: I)
• Wf: Terminal cost weight matrix (default: Wy)
• xmin, xmax: State constraints (default: ±Inf)
• umin, umax: Input constraints (default: ±Inf)
• dumin, dumax: Input increment constraints (default: ±Inf)

Solver Settings:

• rho: ADMM penalty parameter (default: 1.0)
• tol: Convergence tolerance (default: 1e-4)
• eta: Acceleration restart factor (default: 0.999)
• maxiter: Maximum iterations (default: 100)
• precond: Use preconditioning (default: false)
• accel: Use Nesterov acceleration (default: false)
• device: Compute device, cpu or gpu (default: cpu)

System Model:

x_{k+1} = A * x_k + B * u_k + e + w
y_k = C * x_k

where:

• e: Constant affine term (defined in setup!)
• w: Known/measured disturbance (provided at solve time)

Arguments:

• x0: Current state (nx)
• u0: Previous input (nu)
• yref: Output reference (ny)
• uref: Input reference (nu)
• w: Known disturbance (nx), use zeros(nx) if none

pytest tests/test_pimpc.py
# ================================================= test session starts # ==================================================
# platform linux -- Python 3.10.14, pytest-9.0.2, pluggy-1.6.0
# rootdir: /mnt/c/Users/shaoa/Documents/GitHub/PiMPC-python
# configfile: pyproject.toml
# collected 6 items
# 
# tests/test_pimpc.py ......                                                                                       # [100%]
# 
# ================================================== 6 passed in 0.43s # ===================================================