Fixed-step Simulation

The selected interval determines how often the simulator evaluates the system and updates its variables. A smaller step can provide a more detailed representation of changes but requires more calculations, while a larger step can reduce computational demand and introduce greater numerical error or stability concerns. Testing multiple step sizes helps engineers identify an acceptable balance between fidelity and execution speed.

Uniform intervals make the timing of input reads, equation evaluations, and state updates predictable from one run to another. This consistency supports controlled comparisons when engineers change a model, controller, or step size. It also matters when a simulation must execute on a real-time processor, because predictable timing helps the computational process remain aligned with the intended system timeline.

During each cycle, the simulator first reads the relevant inputs, then evaluates the governing equations or component models, and finally updates system variables. Depending on the model, those variables may represent position, velocity, temperature, or voltage. Repeating this sequence at each predetermined interval produces a time-based record that engineers can inspect or use for controller evaluation.

Engineers can run the same model with different predetermined intervals and compare the resulting behavior. Noticeable changes between runs may indicate numerical error or sensitivity to the selected step size, while similar results provide evidence that the chosen interval is adequate for the intended analysis. The final choice must also consider computational cost and whether execution speed is important.

This approach is useful when a controller or physical hardware must interact with a model under predictable timing. In controller testing, it provides a repeatable time sequence for evaluating system responses. In hardware-in-the-loop experiments, fixed execution intervals support interaction with real-time processors, allowing engineers to examine a design under modeled dynamic conditions before deployment.

Simulation results can show how modeled quantities such as position, velocity, temperature, or voltage evolve over time. Repeating the analysis with alternative step sizes adds information about numerical error and stability rather than only system behavior. Engineers can use these comparisons to judge model fidelity, computational demands, and readiness for controller testing or implementation on a real-time processor.