Hybrid fiber–wireless access networks have gained prominence as pragmatic solutions to deployment inefficiencies concentrated in the access segment of broadband infrastructure. Existing research has largely treated hybridization decisions as static design choices made at planning time, based on fixed assumptions regarding cost, performance, and feasibility. However, real-world access networks operate under time-variant conditions, including fluctuating traffic demand, dynamic interference environments, evolving regulatory constraints, and phased infrastructure availability. This paper proposes an adaptive control and dynamic optimization framework for hybrid RF–PON access networks that extends static segment-level substitution models into a time-dependent decision space. By integrating control theory principles, multi-objective optimization, and access network architecture models, the paper demonstrates how hybrid networks can continuously adjust the degree and location of wireless substitution to optimize deployment efficiency and service performance. The proposed framework redefines hybrid access networks as adaptive systems rather than fixed architectures, enabling resilience and efficiency under real-world variability. The paper contributes a novel analytical foundation for intelligent access network control and provides direction for future implementation and empirical validation.