Full Model-Free Control Architecture for Hybrid UAVs

Abstract

This paper discusses the development of a control architecture for hybrid Unmanned Aerial Vehicles (UAVs) based on model-free control (MFC) algorithms. Hybrid UAVs combine the beneficial features of fixed-wing UAVs with Vertical TakeOff and Landing (VTOL) capabilities to perform five different flight phases during typical missions, such as vertical takeoff, transitioning flight, forward flight, hovering and vertical landing. Based on model-free control principles, a novel control architecture that handles the hybrid UAV dynamics at any flight phase is presented. This unified controller allows autonomous flights without discontinuities of switching for the entire flight envelope with position tracking, velocity control and attitude stabilization. Simulation results show that the proposed control architecture provides an effective control performance for the entire flight envelope and excellent disturbance rejections during the critical flight phases, such as transitioning and hovering flights in windy conditions.

Model-free control algorithms for micro air vehicles with transitioning flight capabilities

“…Depending upon the mission complexity and its requirements, the MAV should fly at low and high air speeds, respectively corresponding to hovering and forward flight phase. Based on these mission requirements, and the modeling issue presented in the previous section involving this particular MAV class, we present a part of our previous work that deals with: (i) comparison between a model-based controller and our MFC architecture during the transition flight in a disturbed environment; 37 (ii) uncertain parameter analysis of fixed-wing MAVs in forward flight; 38 (iii) full MFC architecture for position tracking, velocity control and attitude stabilization of a hybrid MAV during its entire flight envelope; 39 Our intention is to analyze our control architecture through additional flight simulations and real-world flight tests in order to investigate its operational behavior, its limits and the interaction between each MFC control block. The new contributions of this paper, with respect to our previous works, are: The paper is organised as follows: in the next section, we present the manufacturing process and the particular aerodynamics of the hybrid MAV prototype named DarkO.…”

“…Initial condition analysis. The initial conditions for pitch angle and for forward speed during the hovering flight (h ic and V x ic ), follow a normal distribution law according to equations (38) and (39). The stability boundary presented in Figure 7, was empirically defined by evaluating all recovery trajectories from initial conditions to the desired setpoint.…”

“…Depending upon the mission complexity and its requirements, the MAV should fly at low and high air speeds, respectively corresponding to hovering and forward flight phase. Based on these mission requirements, and the modeling issue presented in the previous section involving this particular MAV class, we present a part of our previous work that deals with: comparison between a model-based controller and our MFC architecture during the transition flight in a disturbed environment; 37 uncertain parameter analysis of fixed-wing MAVs in forward flight; 38 full MFC architecture for position tracking, velocity control and attitude stabilization of a hybrid MAV during its entire flight envelope; 39 …”

“…full MFC architecture for position tracking, velocity control and attitude stabilization of a hybrid MAV during its entire flight envelope; 39…”

Cascaded model‐free predictive control for single‐phase boost power factor correction converters

“…32 This control technique facilitates the estimation and elimination of uncertainties, unmodeled dynamics and unknown disturbances in the system with only a few parameters to be determined. Therefore, it has been successfully utilized in UAV control, 33 magnetic levitation system, 34 electric drive system 35 and current control of PFC converter, 36 etc.…”