Real-Time Output Linearization in Adaptive Predictive Control for Variable Rate Control of Agricultural Sprayers

Precise flow rate control in agricultural sprayers is critical for variable-rate application, but is challenged by nonlinear dynamics, dead zones, and model variations due to operational changes and nozzle switching. This work aims to develop an efficient control strategy capable of handling these challenges while ensuring compliance with operational constraints. To this end, a generalized predictive controller (GPC) integrated with a dynamic output-linearization scheme is proposed. The dynamic linearization plays a key role to enable adaptive control under practical operating conditions, without requiring a detailed characterization of the hydraulic system. To support this framework, a simplified Kalman filter is employed, to estimate, in real time, the total equivalent fluidic resistance of the system. Experimental validation was conducted using an agricultural sprayer development system, demonstrating superior performance compared to traditional methods, with improved accuracy and adaptability in the presence of disturbances. The proposed output linearizing fuzzy GPC controller (L-FGPC) effectively handles nonlinearities and operational constraints, offering a practical solution for advanced agricultural spraying systems.