Adaptive Controller Design for Biplane Quadrotor

Abstract

AbstractIf augmented with fixed-wing design, air vehicles with the capability to land and take off vertically, such as quadcopters, become promising candidates for missions needing longer hover endurance, faster travel times, and higher payload capacities. Therefore, a backstepping controller (BSC) design of a biplane quadrotor during payload delivery, like vaccines in a remote area, and an adaptive backstepping controller (ABC) to handle mass changes despite wind gusts during the mission. Furthermore, we compare BSC, Integral Terminal Sliding Mode (ITSMC), and ABC for payload delivery to demonstrate effective tracking of the desired trajectory through ABC. The ITSMC also tracks the desired trajectory with mass change but provides a sluggish response, and BSC produces a steady-state altitude error whenever a significant mass change happens. Hybrid development of drones like the biplane quadrotor facilitates improved efficiency and impact through innovative control configurations. A step-by-step process of development of a biplane quadrotor is offered [1]. While Sridharan et al. [2] developed a range and load approximation technique on a biplane tail-sitter quadrotor. Dawkins et al. developed a mathematical model and PID control of a micro quadrotor [3]. Task scheduling and a path planning problem are addressed by Mathew et al. for cooperating vehicles enabling autonomous shipment in metropolitan landmarks [4], while Liu et al. presented formation control of a swarm of tail-sitters [5]. A robust nonlinear control action is developed wherein the coordinate system and the controller structures don’t need to switch [6]. Wagter et al. developed a Linear-Quadratic Regulator (LQR) controller [7]. Mofid et al. addressed a sensor failure scenario where a PID-SMC controller is used for a known upper bounded disturbance, and an adaptive PID-SMC for an unknown disturbance [8]. Finally, Muthusamy et al. proposed a new fuzzy brain emotional learning control for a quadrotor UAV trajectory tracking for real-time payload uncertainties [9].