An Adaptive Extended State Observer-Based Active Disturbance Rejection Control Strategy for Precision Salinity Regulation in Salt-Tolerant Rice Breeding

Precise salinity regulation has emerged as a critical bottleneck in the breeding of salt-alkali-tolerant rice, primarily due to the strong nonlinearity and time-varying disturbances (e.g., evaporation and drainage) inherent in salt pool systems. To address these challenges, this paper proposes an intelligent regulation strategy integrating an adaptive extended state observer (AESO) with active disturbance rejection control (ADRC). The core idea involves treating all internal uncertainties and external disturbances as a “total disturbance”, which is estimated online via the AESO and actively compensated by the ADRC control law. Distinct from conventional fixed-gain observers, the proposed AESO adaptively tunes the observer gain by minimizing the estimation error covariance, thereby achieving an optimal trade-off between rapid estimation and noise suppression. Based on a water-salt balance model, a dual-valve coordination mechanism (using seawater and brackish water valves) is derived to meet dynamic salt requirements. The proposed AESO-ADRC strategy was validated through simulations and a 107-day field experiment conducted in Sanya, China, under three salinity targets. Results demonstrate that the system stabilizes actual salinity within ±300 mg/L of the setpoints across all scenarios, indicates the potential of the proposed method to address the limitations (e.g., poor anti-disturbance capability) found in traditional PID or fuzzy control methods. The controller exhibits strong robustness against persistent time-varying disturbances and ensures long-term stability. This study presents a high-precision, model-free, and disturbance-rejection control solution for salinity management, serving as a core module for future intelligent breeding platforms.