Adaptive Constraint Processor (ACP) based on Artsybashev's Method (AAM-V1): A Deterministic Semantic Validation Layer for AI Integration in Cyber-Physical Systems

This work introduces the Adaptive Constraint Processor (ACP), a deterministic semantic validation layer designed to bridge the gap between probabilistic AI systems and deterministic physical environments. ACP operates as a Decision Arbitration Layer, enforcing physical consistency through:- multi-path analytical redundancy,- reverse validation,- sigma-normalized error detection,- explicit state classification (STABLE, DRIFT, DOUBT, SHOCK). The system transforms contradictions into control signals, preventing unsafe propagation of inconsistent data in robotics, aerospace, medical systems, and industrial automation. A formal pipeline and machine-readable JSON interface are provided to support reproducibility and integration with modern software stacks (ROS2, PX4, embedded systems). Core principle:"Contradiction as a control signal" This work defines a hybrid stochastic-deterministic architecture for safe AI deployment in cyber-physical systems. Artsybashev, Andrey Alekseevich АРЦЫБАШЕВ, АНДРИЙ