Abbas Chamseddine

Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed

Abstract As the first part, this paper presents an overview on the existing works on fault detection and diagnosis (FDD) and fault-tolerant control (FTC) for unmanned rotorcraft systems. Considered faults include actuator and sensor faults for single and multi-rotor systems. As the second part, several FDD and FTC techniques developed recently at the Networked Autonomous Vehicles Lab of Concordia University are detailed along with experimental application to a unique and newly developed quadrotor helicopter testbed.

Flatness-Based Trajectory Planning/Replanning for a Quadrotor Unmanned Aerial Vehicle

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.

Experimental Test of a Two-Stage Kalman Filter for Actuator Fault Detection and Diagnosis of an Unmanned Quadrotor Helicopter

This paper addresses the problem of Faut Detection and Diagnosis (FDD) of a quadrotor helicopter system in the presence of actuator faults. To this end a Two-Stage Kalman Filter (TSKF) is used to simultaneously estimate and isolate possible faults in each actuator. The faults are modelled as losses in control effectiveness of rotors. Three fault scenarios are investigated: loss of control effectiveness in one single actuator, simultaneous loss of control effectiveness in all motors, and loss of control effectiveness in three motors with different magnitudes. The developed FDD algorithm is evaluated through experimental application to an unmanned quadrotor helicopter testbed available at the Department of Mechanical and Industrial Engineering of Concordia University, called Qball-X4. The obtained results show the effectiveness of the proposed FDD method.

Fault Tolerant Flight Control Techniques with Application to a Quadrotor UAV Testbed

Unmanned Aerial Vehicles (UAVs) are gaining more and more attention during the last few years due to their important contributions and cost-effective applications in several tasks such as surveillance, search and rescue missions, geographic studies, as well as various military and security applications. Due to the requirements of autonomous flight under different flight conditions without a pilot onboard, control of UAV flight is much more challenging compared with manned aerial vehicles since all operations have to be carried out by the automated flight control, navigation and guidance algorithms embedded on the onboard flight microcomputer/microcontroller or with limited interference by a ground pilot if needed.

Fault-Tolerant Fuzzy Gain-Scheduled PID for a Quadrotor Helicopter Testbed in the Presence of Actuator Faults

Abstract In the current study, an adaptive PID controller is proposed for fault-tolerant control of a quadrotor helicopter system in the presence of actuator faults. A fuzzy inference scheme is used to tune in real-time the controller gains. Tracking errors and change in tracking errors are used in this fuzzy scheduler to make the system act faster and more effectively in the event of fault occurrence. Two fault scenarios are investigated: the loss of control effectiveness in all actuators and the loss of control effectiveness in one single actuator. The proposed adaptive PID controller is compared with the conventional one through an experimental application to a quadrotor helicopter testbed at the Department of Mechanical and Industrial Engineering of Concordia University. The obtained results show the effectiveness of the proposed method.

Active Fault Tolerant Control of a quadrotor UAV based on gainscheduled PID control

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.

Trajectory planning and re-planning for fault tolerant formation flight control of quadrotor unmanned aerial vehicles

This paper proposes an approach for fault tolerant control of quadrotor UAVs in formation flight. The fault tolerance is achieved by changing the reference trajectories of the entire formation so that to allow the damaged UAV to follow the healthy ones. For this purpose, the virtual structure formation framework is adopted and differential flatness is employed to find the relation between the applied control inputs and the reference trajectories. Simulation results for three UAVs in formation are given to demonstrate the effectiveness of the proposed approach.

Trajectory Planning and Replanning Strategies Applied to a Quadrotor Unmanned Aerial Vehicle

This paper considers the problem of trajectory planning/re-planning for a quadrotor unmanned aerial vehicle (UAV) system. In the fault-free case, the objective is to find the profile of the trajectory to follow so that the system constraints are not violated. When actuator faults occur, trajectory re-planning changes the nominal trajectory so as to take into consideration the new control limitations induced by the occurred fault. Trajectory re-planning requires information about fault location and amplitude and thus unscented Kalman filter (UKF) is employed to detect the occurrence of the fault, isolate the location of the fault and identify the fault amplitude. The main objective is to design a trajectory planning/re-planning approach that can be implemented on real UAV systems with low computation capabilities. For this purpose, the reference trajectories are designed as second-order systems to be used with a flatness-based trajectory planning/re-planning method. The approach is successfully applied to a quadrotor UAV testbed at the Department of Mechanical and Industrial Engineering of Concordia University.

A Distributed Deployment Strategy for a Network of Cooperative Autonomous Vehicles

This brief presents a distributed deployment algorithm for a network of heterogeneous mobile agents to minimize a prescribed cost function. This function is concerned with the cost of serving the entire field by all agents, where the so called operation cost of different agents are not necessarily the same. The problem is investigated for the case where agents have different types of dynamics. Using a multiplicatively-weighted Voronoi diagram, the field is partitioned to smaller regions (one for each agent). A distributed coverage control law is then provided that guarantees the convergence of agents to the optimal configuration with respect to the above-mentioned cost function. The effectiveness of the proposed algorithm is demonstrated by simulations and experiments on a testbed with two types of unmanned vehicles (aerial and ground).

Model Reference Adaptive Fault Tolerant Control of a Quadrotor UAV

This paper presents some experimental results on actuator fault-tolerant control (FTC) for a quadrotor Unmanned Aerial Vehicle (UAV) system. The strategy is based on Model Reference Adaptive Control (MRAC) where three di erent MRAC techniques are implemented and compared with a Linear Quadratic Regulator (LQR) baseline controller, namely the MIT rule MRAC, the Conventional MRAC (C-MRAC) and the Modi ed MRAC (MMRAC). The main advantage of the MRAC strategy is that it does not require an explicit information about the fault location and/or amplitude and thus, a fault detection and diagnosis module is not needed to detect, isolate and identify the occurred faults. The performance of this MRAC-based FTC is tested in the presence of three types of actuator faults: loss of e ectiveness in the total thrust, loss of e ectiveness in one of the rotors and partial damage of one propeller.