A flatness-based flight trajectory planning/replanning strategy is proposed for a quadrotor unmanned aerial vehicle (UAV). In the nominal situation (fault-free case), the objective is to drive the system from an initial position to a final one without hitting the actuator constraints while minimizing the total time of the mission or minimizing the total energy spent. When actuator faults occur, fault-tolerant control (FTC) is combined with trajectory replanning to change the reference trajectory in function of the remaining resources in the system. The approach employs differential flatness to express the control inputs to be applied in the function of the desired trajectories and formulates the trajectory planning/replanning problem as a constrained optimization problem.
During the past 30 years, various fault-tolerant control (FTC) methods have been developed to address actuator or component faults for various systems with or without tracking control objectives. However, very few FTC strategies establish a relation between the post-fault reference trajectory to track and the remaining resources in the system after fault occurrence. This is an open problem that is not well considered in the literature. The main contribution of this paper is in the design of a reconfigurable FTC and trajectory planning scheme with emphasis on online decision making using differential flatness. In the fault-free case and on the basis of the available actuator resources, the reference trajectories are synthesized so as to drive the system as fast as possible to its desired setpoint without violating system constraints. In the fault case, the proposed active FTC system (AFTCS) consists in synthesizing a reconfigurable feedback control along with a modified reference trajectories once an actuator fault has been diagnosed by a fault detection and diagnosis scheme, which uses a parameter-estimation-based unscented Kalman filter. Benefited with the integration of trajectory re-planning using the flatness concept and the compensation-based reconfigurable controller, both faults and saturation in actuators can be handled effectively with the proposed AFTCS design. Advantages and limitations of the proposed AFTCS are illustrated using an experimental quadrotor unmanned aerial vehicle testbed.The reference trajectories F are determined as function of the initial conditions of the system and the final desired conditions as well as the initial time t 0 and the final time t f . The initial and final conditions and the initial time t 0 are known, and the sole unknown is the final time t f . Generally speaking, it is required to attain the desired objectives as fast as possible while respecting system When complete loss of actuators are not considered (i.e., w i < 1 or i > 0), 1 is invertible and 1 u > u and 1 u > u. Thus, for the remaining trajectories F rem .t / to travel, there is no AFTCS AND TRAJECTORY DESIGN AGAINST ACTUATOR FAULTS AND SATURATION P x f .t / D Ax f .t / C B.I m m W /u F T C .t / D Ax f .t / C B.I m m W /.u nom .t / C u add .t // D Ax f .t / C Bu nom .t / BW u nom .t / C B.I m m W /u add .t / (32)
In this paper, an Active Fault-Tolerant Control (AFTC) technique is developed and applied to an unmanned quadrotor helicopter UAV (Unmanned Aerial Vehicle, known also as Qball-X4) with 6 degrees of freedom based on a Gain-Scheduled Proportional-Integral Derivative (GS-PID) control technique. For implementing such an AFTC system, a Fault-Detection and Diagnosis (FDD) block is essential and implemented to detect and identify the actuator fault. The FDD block is implemented based on the OptiTrack visual feedback for providing information needed by GS-PID to switch from one set of pre-tuned controller gains for normal (pre-fault) condition to another set of controller gains tuned for faulty (post-fault) conditions in the presence of an actuator fault in the Qball-X4 UAV. Finally, experimental testing results are presented to demonstrate the effectiveness of the proposed active fault-tolerant control strategy based on the GS-PID control technique.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.