Optimal performance of a dynamical pole vault process was modeled as a constrained nonlinear optimization problem. That is, given a vaulter`s anthropomorphic data and approach speed, the vaulter chose a specific take-off angle, pole stiffness and gripping height in order to yield the greatest jumping height compromised by feasible bar-crossing velocities. The optimization problem was solved by nesting a technique of searching an input-to-output mapping arising from the vaulting trajectory and a method of nonlinear sequential quadratic programming (SQP). It was suggested from the optimization results that the body`s weight has an important influence on the vaulting performance beside the vaulter`s height and approach speed; the less skilled vaulter should gradually adopt a longer pole to improve the performance.
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