First of all, we set a driving condition (i.e., target angle uE and travelling time TE), while the coefficients an are the
optimized parameters. By using the input function in Eq. (6), the trajectory profile is calculated from Eqs. (1)–(3). Next,
numerical integration of Eq. (9) using the calculated trajectory profile yields the displacement of the flexible manipulator
(i.e., the objective function F1 is obtained). The driving torque is obtained from inverse dynamics analysis of Eq. (8), and then
the objective function F2 is calculated. To simultaneously minimize the two objective functions, the coefficients an are tuned
by vector evaluated particle swarm optimization (VEPSO) [26], which is a multi-objective optimization method. Finally, this
optimization approach serves to generate the optimal trajectory. It should be noted that the residual vibration suppression
and energy conservation of the flexible manipulator can be attained by driving the joint angle along the obtained optimal
trajectory, that is, the proposed method is categorized as an open-loop control considering that the sensors measuring the
vibrations are not required.