A new approach in system and tactic design optimization of an autonomous underwater vehicle by using Multidisciplinary Design Optimization

Optimal design of an Autonomous Underwater Vehicle (AUV) consists of various subsystems and disciplines such as guidance and control, payload, hydrodynamics, power and propulsion, sizing, structure, trajectory and performance. The designed vehicle is also employed in an operational environment with tactical parameters such as distance to target, uncertainty in estimation of target position and target velocity. Multidisciplinary Design Optimization (MDO) is the best way for finding both optimum and feasible designs. In this paper, a new optimization design framework is proposed in which Multidisciplinary Feasible (MDF) as MDO framework and Particle Swarm Optimization (PSO) as optimizer were combined together for optimal and feasible conceptual design of an AUV. Initially, we found an optimal system design by using MDF-PSO methodology in engineering space for any single tactical situation (locally tactical parameters). Then the optimal off-design AUVs in tactical subspaces were found by minimizing the difference between the locally optimized objective function and sub-optimal objective function. In this framework, we have shown that not only is the tactical situation affected by AUV design parameters, but an optimal AUV for each tactical regions are also found.