Delivery drones have always faced challenges when it comes to reliably deliver packages. This paper introduces a novel concept of a hybrid drone called “MICOPTER” to alleviate this issue. Being able to fly in three modes of aircraft, helicopter, and gyrocopter, the proposed model of the multi-identity helicopter comprises a 2DOF tilting mechanism of rotors and a folding wing system leading to better performance and controllability. To scrutinize the idea, MICOPTER is compared to other types of Unmanned Aerial Vehicles (UAVs) in terms of different performance parameters. The performance goal of the MICOPTER is the realization of a predetermined standard delivery drone mission based on Amazon Prime Air. According to the relevant literature, the corresponding conceptual design equations are formulated and the traditional matching diagram method is utilized to attain the initial design point. Afterward, a multidisciplinary-feasible design matrix is provided as well as multi-objective optimization to strive for optimal feasible configurations while maximizing cruise velocity and range. Furthermore, the configuration and performance of some of the feasible design points on the final Pareto frontier are compared with the traditional design. Finally, by simulating a typical flight profile and using robust non-linear backstepping control, the controllability of the proposed configuration is investigated. The controller performance is assessed considering its stability and tracking 8-shape trajectory. Results indicate the MICOPTER capabilities as a novel configuration in both terms of design performance and controllability.
This paper presents an optimized robust trajectory control system for an autonomous tiltrotor bi-copter based on an incremental nonlinear dynamic inversion (INDI) strategy combined with a set of PID/PD controllers. The methodology includes a lower level, fast attitude control action using an incremental nonlinear dynamic inversion (INDI) strategy, which is driven by a higher level, slow trajectory control action that uses nonlinear dynamic inversion (NDI). The nonlinear dynamic model of the drone is derived, and the basis of the motion and the design of the attitude and position stabilizing controllers are discussed. To develop and test the suggested controller, a circle-shaped flight profile is simulated. The linear control providing inputs to the NDI and INDI controllers is tuned via a novel multi-objective optimization auto-tuning method using the non-dominated sorting genetic algorithm II (NSGA-II). The tracking and disturbance rejection optimization is achieved via the use of the integral of time multiplied by the absolute error (ITAE) and the integral of the square of the error (ISE) objective functions, which are optimized concurrently. The simulation results reveal that the proposed control design outperforms the traditional dynamic inversion controller design and demonstrate that the developed INDI + PID/PD controller possesses exceptional accuracy and performance, enabling the tiltrotor bi-copter to track the given trajectory. Furthermore, the paper shows that the proposed controller produces 40% lower overshoot and settling time as measured with respect to previous backstepping controllers reported in the literature. The robustness of the controller is validated through diverse tests where the aircraft is subjected to external (wind gust) disturbances.
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