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Motion planning and trajectory control are two basic challenges of unmanned vehicles. In motion planning problem, feasible trajectories are developed while nonlinear dynamic model and performance constraints of the vehicle under utility are considered. In this study, motion planning is performed via an enhanced particle swarm optimization algorithm. The resulting offline generated trajectories are tracked using a nonlinear trajectory control system methodology. The Lyapunov-based constrained backstepping approach and command filters are utilized in designing the trajectory control system. Command filters smoothen the input signals and provide their derivatives. Evaluation of the proposed integrated approach in several simulated scenarios has effectively demonstrated the potential of both algorithms in generating optimal contour matching trajectories as well as excellent tracking capability of the trajectory control system.

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In this paper, the dynamic stability analysis of a rolling airframe actuated by one pair ON-OFF actuator using linear theory is presented via developing a new closed form solution. The effect of discontinuous forcing term on rolling airframe stability is studied. In contrast to tricyclic motion with constant forcing term (constant non-homogeneous term) in which only the amplitude of nutation and precession is affected, it is found that ON-OFF control affects both amplitude and phase of nutation and precession motions. In the case of discontinuous control surface, there are two sources for resonance instability. Finally, through simulation results of closed form solutions, a comparison between airframe’ response to ideal and real ON-OFF command is achieved. The effect of ON-OFF control on angular motion is also evaluated.