High fidelity modelling and GA optimized control of yaw dynamics of a custom built remotely operated unmanned underwater vehicle

Abstract

In this paper, a custom built, underactuated, inspection class micro Remotely Operated Unmanned Underwater Vehicle (ROV) is employed as a testbed to investigate control and modelling problems related to underwater vehicles in shallow waters and pools. Dynamic model for yaw is obtained via mathematical modelling and system identification techniques. To instil confidence in the identified model, residuals and cross-validation tests are carried out to obtain high fidelity vehicle model for subsequent stabilizing closed-loop control design. Following the modelling exercise, design, real-time implementation, and analysis of a GA optimized PI controller for yaw is carried out. The performance of the GA optimized controller is benchmarked against the experimental results of a multi-parameter root-locus tuned PI controller and simulated responses of a standard linear quadratic regulator (LQR) controller. In addition, the efficacy of the GA-PI controller is gauged employing recently developed marine predator algorithm (MPA). The need for a controller with optimized performance motivated the utilization of GA and MPA optimization techniques. The results from real-time pool experiments indicate substantially enhanced performance of GA optimized controller, outperforming other controllers by as much as 22% in performance indicators such as settling time and maximum overshoot. Furthermore, the GA optimized controller demonstrated far better robustness and disturbance rejection capabilities.