This paper proposes a novel adaptive sliding-mode-based control allocation scheme for accommodating simultaneous actuator faults. The proposed control scheme includes two separate control modules with virtual control part and control allocation part, respectively. As a low-level control module, the control allocation/reallocation scheme is used to distribute/redistribute virtual control signals among the available actuators under fault-free or faulty conditions, respectively. In the case of simultaneous actuator faults, the control allocation and reallocation module may fail to meet the required virtual control signal, which will degrade the overall system stability. The proposed online adaptive scheme can seamlessly adjust the control gains for the high-level sliding mode control module and reconfigure the distribution of control signals to eliminate the effect of the virtual control error and maintain the stability of the closed-loop system. In addition, with the help of the boundary layer for constructing the adaptation law, the overestimation of control gains is avoided, and the adaptation ceases once the sliding variable is within the boundary layer. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of simultaneous actuator faults. The effectiveness of the proposed control scheme is demonstrated by experimental results based on a modified unmanned multirotor helicopter under both single and simultaneous actuator faults conditions with comparison to a conventional sliding mode controller and a linear quadratic regulator scheme.

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An Adaptive Fault-Tolerant Sliding Mode Control Allocation Scheme for Multirotor Helicopter Subject to Simultaneous Actuator Faults

A review of quadrotor: An underactuated mechanical system

The use of robots in our daily lives is increasing. Different types of robots perform different tasks that are too dangerous or too dull to be done by humans. These sophisticated machines are susceptible to different types of faults. These faults have to be detected and diagnosed in time to allow recovery and continuous operation. The field of Fault Detection and Diagnosis (FDD) has been studied for many years. This research has given birth to many approaches and techniques that are applicable to different types of physical machines. Yet the domain of robotics poses unique requirements that are very challenging for traditional FDD approaches. The study of FDD for robotics is relatively new, and only few surveys were presented. These surveys have focused on traditional FDD approaches and how these approaches may broadly apply to a generic type of robot. Yet robotic systems can be identified by fundamental characteristics, which pose different constraints and requirements from FDD. In this article, we aim to provide the reader with useful insights regarding the use of FDD approaches that best suit the different characteristics of robotic systems. We elaborate on the advantages these approaches have and the challenges they must face. To meet this aim, we use two perspectives: (1) we elaborate on FDD from the perspective of the different characteristics a robotic system may have and give examples of successful FDD approaches, and (2) we elaborate on FDD from the perspective of the different FDD approaches and analyze the advantages and disadvantages of each approach with respect to robotic systems. Finally, we describe research opportunities for robotic systems’ FDD. With these three contributions, readers from the FDD research communities are introduced to FDD for robotic systems, and the robotics research community is introduced to the field of FDD.

On Fault Detection and Diagnosis in Robotic Systems

This brief presents the systematic design and real-time experimental results of a fault detection, isolation, and accommodation algorithm for quadrotor actuator faults using nonlinear adaptive estimation techniques. The fault diagnosis architecture consists of a nonlinear fault detection estimator and a bank of nonlinear adaptive fault isolation estimators designed based on the functional structures of the faults under consideration. Adaptive thresholds for fault detection and isolation are systematically designed to enhance the robustness and fault sensitivity of the diagnostic algorithm. After fault isolation, the fault parameter estimate generated by the matched isolation estimator is used for accommodating the fault effect. Using an indoor quadrotor test environment, real-time experimental results are shown to illustrate the effectiveness of the algorithms.

Quadrotor Actuator Fault Diagnosis and Accommodation Using Nonlinear Adaptive Estimators

This paper presents a fault tolerant approach for a coaxial octorotor regarding rotor failures. A complete architecture including error detection, fault isolation and system recovery is presented. The diagnosis system is designed with a nonlinear observer to generate residuals and an inference model to evaluate them and isolate the faulty motor. Once the motor failure is diagnosed, a recovery algorithm is applied. It uses the built-in hardware redundancy of the octorotor and compensates the loss of the failing motor by controlling its dual to keep a stable flight that allows the multirotor to continue its mission. This architecture is validated on real flights.

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Fault diagnosis and fault-tolerant control strategy for rotor failure in an octorotor

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.

M. Hadi Amoozgar

Papers

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