K. Shinohara / Natural Science 2 (2010) 959-967

Copyright © 2010 SciRes. OPEN ACCESS

966

6. CONCLUSIONS

We developed a model by using the dynamics of an und-

erwater manipulator. An algorithm was constructed on

the basis of the manipulator dynamics. The results obta-

ined by this algorithm qualitatively agreed with the ex-

perimental results.

In this study, a swimmer model providing the optimal

motion is presented. The optimization method mainly co-

nsists of the probabilistic approach (a genetic algorithm,

simulated annealing, etc.) and the deterministic approach

(adjoint variable method, etc.). In case the motion is re-

stricted to be 2D, the optimizer can easily search for the

optimal value. If the 2D motion is extended to 3D mo-

tion in this study model, it may be difficult to search for

the optimal value. By using the deterministic approach

(the adjoint variable method), it is highly possible to

ensure that the optimizer searches for the local minimum

by increasing the number of parameters. The determinis-

tic approach also demands the stationary condition based

on the variational method. The adjoint equation derived

by the stationary condition has strong nonlinear charac-

teristics. This nonlinearity causes numerical instability.

In the future study, the 3D motion of a swimmer will be

simulated by using the probabilistic approach, which

does not need mathematical formulation.

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