The Rule-based Dynamic Control Algorithm for Intelligent Multi-Parameter Management in Dendrobium Officinale Cultivation

The cultivation of Dendrobium officinale from Huoshan involves complex interactions among multiple environmental parameters, posing significant challenges to conventional single-parameter control strategies. To address this issue, this paper proposes a rule-based dynamic control algorithm which integrates multi-sensor data fusion with a hierarchical expert-rule mechanism, enabling the identification and prioritized handling of coupled environmental anomalies and solving coordinated multi-parameter regulation. The proposed algorithm effectively prevents conflicts between control actions and enhances system robustness under complex environmental scenarios. Experimental demonstrate that the proposed approach outperforms static threshold-based methods and conventional PID control in terms of cooperative control effectiveness, adaptability to complex conditions, and resource efficiency, while avoiding the high computational cost and low interpretability associated with complex AI-based models.