7.7 Sampling, Computational Delay, and Model Fidelity

Core idea¶

Sampling, Computational Delay, and Model Fidelity must be treated as a system-level decision rather than an isolated technique. For an active suspension under full preview, finite-horizon MPC, reactive feedback, and noisy estimation, state what is fixed, what is optimized, what information is available, and what equations define feasibility.

The relevant quantities are $p$, controller and estimator $c$, information architecture $a_I$, and $\mathcal I_t$. The chapter-level formulation is

For this section, trace how the choice changes sensors, the active constraints, and the implementable engineering design. A method is useful only when its assumptions are explicit and its result answers the same system question as the baseline.

Engineering interpretation¶

Ask three questions:

1. Which physical, informational, computational, or economic resource changed?

2. Which objective component or active constraint made the change valuable?

3. Does the conclusion survive model, disturbance, initialization, uncertainty, and implementation checks?

A practical action is to restrict information. Record units and assumptions before optimization, report component objectives and margins afterward, and verify the result using an independent calculation or higher-fidelity model.

Activity 7.7: quantify sampling, computational delay, and model fidelity¶