An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system

Conventionally, researchers have favored the model-based control scheme for controlling gantry crane systems. However, this method necessitates a substantial investment of time and resources in order to develop an accurate mathematical model complex system. Recognizing challenge, current paper introduces novel data-driven that relies exclusively on input output data. Undertaking couple modifications conventional marine predators algorithm (MPA), random average (RAMPA) with tunable adaptive coefficient step size ( CF) has been proposed as enhanced alternative towards fine-tuning multiple-node hormone regulation neuroendocrine-PID (MnHR-NEPID) controller parameters multi-input–multi-output (MIMO) First modification involved location calculation within algorithm’s updating mechanism solve local optima issue. The second then introduced CF search capacity by enabling users’ resilience attaining offsetting level exploration exploitation phases. Effectiveness is evaluated based convergence curve statistical analysis fitness function, total norms error input, Wilcoxon’s rank test, response analysis, robustness under influence external disturbance. Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence through its superior performance against MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame (MFO), multi-verse (MVO), sine-cosine (SCA), salp-swarm (SSA), slime mould (SMA), flow direction (FDA), formally published safe experimentation dynamics (ASED)-based methods.