Development of Walrus Optimization Algorithm-Tuned Integral-Proportional Derivative Temperature Control for Cashew-Kernel Dryer

Abstract

Precise temperature control in cashew kernel drying is critical for achieving the required 5% final moisture content while preventing roasting, discoloration, and overall quality degradation; however, conventional PID controllers often struggle to maintain this precision due to the nonlinear and time-varying behaviour of batch drying systems. To overcome these limitations, this study develops a Walrus Optimization Algorithm (WaOA)-tuned Integral–Proportional Derivative (I-PD) controller specifically designed for cashew kernel dryers. The drying process was modelled using Fick’s equation, and WaOA was employed to optimally tune the controller parameters. The performance of the proposed controller was compared with MATLAB-tuned PID, MATLAB-tuned I-PD, and Ziegler–Nichols PID controllers in MATLAB R2021a SIMULINK using rise time, settling time, steady-state error, and maximum overshoot as evaluation metrics. The WaOA-tuned I-PD controller achieved a rise time of 0.0479 s, settling time of 0.1398 s, and overshoot of 0.6672, outperforming all comparative controllers in stability and transient response. These findings demonstrate the potential of bio-inspired optimization techniques for enhancing temperature regulation in agricultural drying systems.