Adaptive Path Planning And Flight Control For Quadrotor UAV

As the key technologies of UAV autonomous flight system,path planning and flight control are the the foundation of UAV intellectualization development.In view of this,these two parts were studied while the quadrotor UAV was taken as the research object.Aiming at online/offline path planning,cuttlefish algorithm was used to search the global best path based on the path evaluation function.An adaptive cuttlefish algorithm with joint modification was proposed considering that the traditional cuttlefish algorithm might be trapped in local optimum and have low precision after long search.The regulatory mechanism mixed with chaos perturbation and mutation learning was proposed to strengthen local search so as to improve search precision.Adaptive weight mechanism was introduced to diminish search space and ensure search efficiency.The auto filter mechanism based on individual fitness was used to adjust population diversity and break away from local optimum.Validity of the proposed algorithm was firstly verified through tests of six benchmark functions.And the proposed algorithm was then applied to offline path planning,the simulation results verify the superiority of the proposed algorithm.Furthermore,as the environment becomes more complex,the improvement effects of path planning are more remarkable.And when the proposed algorithm was applied to online path planning,the global path planning issue was transformed to the planning of several segmental paths,and a heuristic method was used to select the segmental goal.Simulation results show that the proposed algorithm meets the real-time requirement and has high precision.Effectiveness of the proposed algorithm is further verified.Aiming at the flight control problem in case that the quadrotor UAV system exists disturbances and unavailable state variables,a novel sliding mode controller combined with extended state observer(ESO)and a novel reaching law was proposed after simplifying the dynamic model reasonably.The novel reaching law combined with saturation function and power term was introduced to weaken chattering of the sliding mode control(SMC),and so as to improve the robustness of the system.The nonlinear ESO based on a fal(?)function was introduced to estimate the uncertainty factors in time,with these uncertainties being compensated in the controller,which improved the adaptability of the system to the environment.Control laws for position and attitude system were then designed by using the novel SMC controller,and the stability of the controller system had been proved by Lyapunov method.The simulation results show that the ESO proposed above has good observing performance for disturbance,the novel SMC controller can effectively suppress chattering,and has high control accuracy and robustness.