Controller design for underwater robotic vehicle based on improved whale optimization algorithm

This paper presents the impact of introducing a two-controller on linearized autonomous underwater vehicle (AUV) for vertical motion control. These controllers are presented to overcome sensor noise AUV control model that effect tolerance and stability depth Linear quadratic Gaussian (LQG) controller is cascaded with adapt system compared FOPID established by improved whale optimization algorithm (IWOA) identify which controlling method can make more harmonize tolerable. The developed based improving original WOA reshaping specific detail earn warranty new IWOA will have values update position lower than identified lower-bound (LB), upper-bound (UB). Furthermore, examined set test functions include (unimodal, multimodal fixed dimension functions). privileges applying reducing executing time obtaining semi-optimal objective function as other popular swarm-intelligence algorithms.