Optimal Shape Design of an Autonomous Underwater Vehicle Based on Gene Expression Programming
A novel strategy combining gene expression programming and crowding distance based multi-objective particle swarm algorithm is presented in this paper to optimize an underwater robot’s shape. The gene expression programming method is used to establish the surrogate model of resistance and surrounded volume of the robot. After that, the resistance and surrounded volume are set as two optimized factors and Pareto optimal solutions are then obtained by using multi-objective particle swarm optimization. Finally, results are compared with the hydrodynamic calculations. Result shows the efficiency of the method proposed in the paper in the optimal shape design of an underwater robot.
KeywordsAutonomous underwater vehicle Shape optimization Gene expression programming Multi-objective particle swarm optimization
This work is supported by the project of National Natural Science Foundation of China (No. 61603277; No. 51579053; No. 61633009), the 13th-Five-Year-Plan on Common Technology, key project (No. 41412050101), the Shanghai Aerospace Science and Technology Innovation Fund (SAST 2016017). Meanwhile, this work is also partially supported by the Youth 1000 program project (No. 1000231901), as well as by the Key Basic Research Project of Shanghai Science and Technology Innovation Plan (No. 15JC1403300). All these supports are highly appreciated.
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