def __init__(self, dt: float): self.dt = dt self.models: Dict[str, XModModel] = {} self.connections: List[tuple] = [] # (from_model, from_port, to_model, to_port)
At its core, is the joint simulation of independent sub-simulators. xMOD excels in this area by offering several unique technical capabilities: xMOD™ | Co-simulation sofware editor and HiL plateform
Are you using co-simulation in your current workflow? Let us know in the comments how it has saved your project timeline. xmod co-simulation
xMOD Co-Simulation: Bridging Domains for Modern System Engineering
XMOD solutions (often integrated with MATLAB/Simulink environments) provide a streamlined workflow for this exact problem. Instead of manually flashing a microcontroller and reading serial data, XMOD automates the handshake between the PC and the target. def __init__(self, dt: float): self
def get_state(self): return {} # stateless
This is a compact where each xmod component could run in a separate process, use different solvers, or be wrapped from C/FMI. def step(self, t: float, dt: float, inputs: Dict[str, np
def step(self, t: float, dt: float, inputs: Dict[str, np.ndarray]) -> XModStep: x_meas = inputs.get("x_measured", np.array([0.0]))[0] F_cmd = self.Kp * (self.x_ref - x_meas) return XModStep( outputs="F_cmd": np.array([F_cmd]), new_time=t + dt )