Co-design Optimization of a Novel Multi-identity Drone Helicopter (MICOPTER)

Abstract

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.

Research on Attitude Detection and Flight Experiment of Coaxial Twin-Rotor UAV

“…The main noise sources and main random errors of the coaxial UAV are mainly analyzed. Aiming at the attitude calculation problem of the coaxial dual-rotor UAV, an optimized adaptive unscented Kalman filter algorithm and an extended Kalman filter algorithm are proposed to advance the model [32][33][34]. In contrast, the algorithm uses the gradient descent algorithm to reproduce and adjust the process noise covariance to optimize the state prediction and estimation, which effectively reduces the error of the state solution.…”

“…The error covariance is updated, and the measurement update equation uses the values of the observed variables to correct the state and covariance estimates. The Accord ratio matrix of the state transition matrix and the measurement matrix is shown in Equation (34).…”

Nature-Inspired Algorithms from Oceans to Space: A Comprehensive Review of Heuristic and Meta-Heuristic Optimization Algorithms and Their Potential Applications in Drones

“…The design of such drones involves multiple technical aspects, including the need to balance performance requirements such as range, speed, and payload capacity, while also ensuring safety and stability. Optimization algorithms enable the exploration of large design spaces and the identification of optimal solutions that satisfy multiple design objectives and constraints [431,432]. Of course, PSO has also been used to solve the optimal conceptual design of aircraft to find the best possible configuration [433].…”