Admissibility-Preserving Control for Strict-Feedback Nonlinear Systems with Asymmetric Actuator Constraints

What the math gives to ML

The paper offers a constructive dynamic realization that preserves asymmetric actuator limits by embedding the constraint directly into the vector field instead of applying post-hoc clipping. Its transferable mechanism is a bounded state whose vector field points strictly inward at both actuator boundaries, together with computable interior equilibria determined by command amplitude and realization gains. This can be implemented as a recurrent output layer for policies, world models, or neural controllers, providing hard magnitude constraints and smoother temporal behavior than clipping. The main falsifiable signature is forward invariance of the action interval and agreement between measured steady-state actions and the paper's equilibrium equations.