Novel trajectory generation and adaptive evolutionary feedback controller for quadrotors

This paper presents a novel realistic trajectory generation method for quadrotor helicopters that minimizes the fifth derivative of location with respect to time (crackle) so that smooth trajectories are obtained in typical flight scenarios. The trajectories are implemented with higher order polynomials that grant smoothness in the motor thrust. In order to tune the parameters of the polynomials in the search space, a multi-objective optimization method called particle swarm optimization (PSO) is used. The proposed technique satisfies the constraints imposed by the configuration of the quadrotor helicopter. Other particular constraints can be introduced such as: obstacle avoidance, speed limitation, attitude constraints and actuator torque limitations due to the practical feasibility of the trajectories. Furthermore, a novel adaptive evolutionary feedback controller (EFC) is described and it is used to follow these trajectories. The solution to the control problem is also obtained using PSO. Several numerical results are presented to assess the performance of the proposed trajectory generation and control methods.