Evaluation of Moth-Flame Optimization, Genetic and Simulated Annealing tuned PID controller for Steering Control of Autonomous Underwater Vehicle

This paper describes an optimal bio-inspired PID controller for accurate steering management of the Autonomous Underwater Vehicle system (AUV). To achieve precise control performance, a PID controller is designed, and its gain parameters K
p
, K
i,
K
d
are tuned by applying Simulated Annealing (SA), Genetic Algorithm (GA) and Moth-Flame Optimization Algorithm (MFO). The experimental response corresponding to the unit step and square input waveform for these proposed nature-inspired optimization algorithms were obtained. The response characteristics like overshoot, rise time, settling time and performances index ITAE were calculated and compared. The experimental results show that MFO-PID is highly efficient, followed by GA and SA, respectively.