CAD.4:4.2 - Evaluate feasibility before ranking attractive scores

For each candidate, establish the connected error behavior, physical constraints and continuation under its own admitted conditions. Include initialization, transitions, planned modes and fallback behavior. A candidate with a missing load-bearing condition is unresolved, not numerically inferior.

Then evaluate the behavior the task actually values: tracking envelope, settling, progress, resource consumption, disturbance rejection or cost. Use the same demand and perturbation class across candidates. An average objective cannot compensate for violating a hard constraint.

Boundedness and convergence are distinct. For example, if the nominal law makes z_k\to z_* and v_k\to v_*, the linear error equation has forcing g_k=Hz_k+Gv_k+w_k. With a contractive F, g_k\to0 implies e_k\to0: the contribution of any fixed finite past decays, and the remaining tail is bounded by its shrinking forcing divided by 1-q. If Hz_*+Gv_*\neq0, even zero disturbance can leave a steady bias. A bounded command domain alone establishes neither nominal progress nor zero error.

When the performance claim requires optimality, robust stability or task completion beyond these arguments, supply the corresponding result for the actual connected model. Do not infer it from the presence of MPC, a Lyapunov function for one component, or an optimizer’s successful return.