Performance of the UAVs for a particular application can be enhanced by hybrid design, where take‐off, hover, and landing happen like rotary‐wing UAVs, and flies like fixed‐wing UAVs. A backstepping controller and an adaptive backstepping controller are designed for trajectory tracking and payload delivery in a medical emergency or medical substance delivery like vaccine delivery in the presence of wind gust. Simulation results show that the backstepping controller effectively tracks the trajectory during the entire flight envelope, including take‐off, hovering, the transition phase, level flight mode, and landing. A comparison between Backstepping, Integral Terminal Sliding Mode (ITSMC) and Adaptive Backstepping controllers for payload delivery show that the adaptive backstepping controller effectively tracks the altitude and attitude. ITSMC is capable of tracking the desired trajectory for a change in the mass but has sluggish response. The backstepping controller generates a steady‐state error in altitude during the mass change in biplane quadrotor.

The application scope of unmanned aerial vehicles (UAVs) is increasing along with commensurate advancements in performance. The hybrid quadrotor vertical takeoff and landing (VTOL) UAV has the benefits of both rotary-wing aircraft and fixed-wing aircraft. However, the vehicle requires a robust controller for takeoff, landing, transition, and hovering modes because the aerodynamic parameters differ in those modes. We consider a nonlinear observer-based backstepping controller in the control design and provide stability analysis for handling parameter variations and external disturbances. We carry out simulations in MATLAB Simulink which show that the nonlinear observer contributes more to robustness and overall closed-loop stability, considering external disturbances in takeoff, hovering and landing phases. The backstepping controller is capable of decent trajectory-tracking during the transition from hovering to level flight and vice versa with nominal altitude drop.

A biplane quadrotor is a hybrid type of Unmanned Aerial Vehicle (UAV) that has advantages of both fixed-wing and rotary-wing UAVs. In this study, we design controllers using (i) Backstepping Control (BSC), (ii) Integral Terminal Sliding Mode Control (ITSMC), and (iii) Hybrid control (ITSMC + BSC), where the ITSMC controls attitude and BSC controls the altitude subsystems as per the mathematical model of biplane quadrotor. The performance of these controllers is evaluated based on the autonomous trajectory tracking containing all possible maneuvers and operation modes that the biplane quadrotor can perform. Performance analysis reveals that the BSC-based controller is susceptible to a steady-state error in altitude tracking when mass is changed. In contrast, the ITSMC and the “hybrid” controllers achieve smooth tracking in a finite time. Furthermore, the “hybrid” controller outperforms the other designs, reducing tracking error and faster convergence time.

A biplane quadrotor (hybrid vehicle) benefits from rotary-wing and fixed-wing structures. We design a dual observer-based autonomous trajectory tracking controller for the biplane quadrotor. Extended state observer (ESO) is designed for the state estimation, and based on this estimation, a Backstepping controller (BSC), Integral Terminal Sliding Mode Controller (ITSMC), and Hybrid Controller (HC) that is a combination of ITSMC + BSC are designed for the trajectory tracking. Further, a Nonlinear disturbance observer (DO) is designed and combined with ESO based controller to estimate external disturbances. In this simulation study, These ESO-based controllers with and without DO are applied for trajectory tracking, and results are evaluated. An ESO-based Adaptive Backstepping Controller (ABSC) and Adaptive Hybrid controller (AHC) with DO are designed, and performance is evaluated to handle the mass change during the flight despite wind gusts. Simulation results reveal the effectiveness of ESO-based HC with DO compared to ESO-based BSC and ITSMC with DO. Furthermore, an ESO-based AHC with DO is more efficient than an ESO-based ABSC with DO.

Payload delivery is one of the many Unmanned Aerial Vehicle (UAV) applications that save time, energy, and human resources. The present simulation study compares rotary‐wing quadrotors (RW‐Quadrotors) and tail‐sitter biplane quadrotors (Bi‐Quadrotors) under payload delivery conditions that help to choose the best UAV for the particular mission. A comparative study is performed based on (i) time taken to accomplish the given mission, (ii) trajectory tracking performance, (iii) motor speed throughout the entire flight envelope, and (iv) remains SoC (State of Charge) after the mission. Furthermore, a Backstepping Controller (BSC) and an Adaptive Backstepping Controller (ABSC) are developed for both UAVs to handle mass changes during flight while Genetic Algorithm (GA) is used for the gain optimization. MATLAB Simulink‐based numerical simulation reveals that the Bi‐Quadrotor has a lower average rotor speed than the RW‐Quadrotor. However, the Bi‐Quadrotor's SoC after the mission is higher than the RW‐Quadrotor, and it took less time to accomplish the mission. The ABSC designed for RW‐Quadrotor and Bi‐Quadrotor effectively handles mass change during the mission. However, the BSC controller increases energy consumption for the Bi‐Quadrotor in the presence of wind gusts.

Maglev transportation system is become a hot topic for researchers because of the distinctive advantages, such as frictionless motion, low power consumption, less noise, and being environmentally friendly. The maglev transportation system’s performance gets sufficiently influenced by the control method and the magnetic levitation system’s dynamic performance, which is a critical component of the maglev transportation system. The Magnetic Levitation System (MLS) is a group of unstable, nonlinear, uncertain, and electromagnetically coupled practical application. Control objective of this study is to design a position stabilizing control strategy for Magnetic Levitation system under extreme uncertain parametric conditions using a reference model governed by a reference stabilizer and nonlinear adaptive control structure. After successful tuning the reference stabilizer with and without time-varying payload disturbance, the tracking-error dynamics are obtained in the presence of both matched and mismatched types of parametric uncertainties. Next, the close-loop stability theorem is formulated for Lyapunov stability analysis to get the design constraints, parameter update laws, and adaptive control law. Numerical simulations performed for a high range of parametric violations check the control design’s efficacy. The performance robustness gets confirmed by comparing the results with the nonlinear control approach. The MLS gets performance recovery and settles within safe limits in few seconds using the proposed methodology. However, the nonlinear controller faces permanent failure in stabilizing the MLS.