A multi-rate hierarchical fault-tolerant adaptive model predictive control framework: Theory and design for quadrotors

Purpose – A simplified global positioning system (GPS) error model including models for a variety of abnormal operational conditions and failures is developed to provide simulation tools for the design, testing, and evaluation of autonomous flight fault tolerant control laws. The paper aims to discuss these issues. Design/methodology/approach – Analysis and experimental data are used to build simplified models for GPS position and velocity errors on all three channels. The GPS model is interfaced with West Virginia University unmanned aerial vehicles (UAV) simulation environment and its utility demonstrated through simulation for several autonomous flight scenarios including GPS abnormal operation. Findings – The proposed simplified GPS model achieves desirable levels of accuracy and realism for all components for the purpose of general UAV dynamic simulation and development of fault tolerant autonomous flight control laws. Research limitations/implications – The simplified GPS model allows investigating GPS malfunction effects on the performance of autonomous UAVs and designing trajectory tracking algorithms with advanced fault tolerant capabilities. Practical implications – The simplified GPS model has proved to be a flexible and useful tool for UAV simulation and design of autonomous flight control laws at normal and abnormal conditions. Originality/value – The outcomes of this research effort achieve a level of detail never attempted before in modeling GPS operation at normal and abnormal conditions for UAV simulation and autonomous flight control laws design using a simplified framework.

Loss of control accounts for over 25% of aircraft accidents worldwide. This study presents a fault tolerant flight control strategy for increasing aircraft safety. The work has been undertaken within the Action Group on fault tolerant control (FTC) of the European GARTEUR programme, which develops collaborative efforts in Europe to create new FTC technologies that could significantly advance the goals of the aviation safety. After the fault detection and confirmation by the in-flight dedicated systems, a compensation loop is activated to ensure safe recovery. The design of the FTC loop is achieved without any changes in the nominal (and certificated) flight control system (FCS). The FTC scheme design is formulated as an H∞ strong stabilisation problem. Fault compensability is subsequently discussed and formulated as a trim-deficiency analysis problem. The proposed technique is implemented on the SIMONA flight simulator and evaluated through a pilot experiment. The tested scenario corresponds to the landing approach of a large transport aircraft (B747-100/200). The faulty situation is related to trimmable horizontal stabiliser (THS) failures. Piloted flight simulator experiments show that fault tolerance can be achieved under the condition that there exists sufficient remaining control authority.

In More Electric Aircraft applications, Dual Three-Phase Permanent Magnet Synchronous Machines can potentially be employed in starter/generator systems due to their high-power density and fault tolerance capabilities. However, achieving robust sensorless control and fault-tolerant operation in these machines remains a significant challenge, particularly under open-circuit fault conditions and parameter variations. This thesis addresses these challenges by introducing a novel Model Reference Adaptive System sensorless control strategy and an adaptive Proportional-Integral-Resonant fault-tolerant control scheme, ensuring high reliability and superior performance in More Electric Aircraft applications. The proposed Model Reference Adaptive System sensorless control strategy effectively estimates rotor position and speed, replacing conventional mechanical sensors which may not be viable in some specific aerospace environments A Forgetting Factor Recursive Least Squares online parameter estimation method is integrated into the Model Reference Adaptive System framework, significantly enhancing estimation accuracy while reducing computational complexity. Unlike traditional recursive least squares approaches, the Forgetting Factor Recursive Least Squares algorithm eliminates matrix inversion computations, making it computationally efficient and well-suited for real-time applications. Additionally, a Proportional-Integral-Resonant-based fault-tolerant control strategy is developed to mitigate electromagnetic torque ripple under open-circuit fault conditions. By modifying the current reference in the faulted phase and incorporating resonant compensation, the proposed control strategy effectively suppresses second-harmonic current distortions, ensuring smooth operation despite fault conditions. The proposed control methodologies are validated through comprehensive simulations and real-time experimental studies using a laboratory-based Dual Three-Phase Permanent Magnet Synchronous Machine prototype. When a single open-circuit fault is present, the torque of the dual three-phase machine studied in this work is derated to approximately 57.6% of the rated value. Under such a single open-circuit fault with realistic per-phase current limiting, simulations show that the proposed Proportional-Integral-Resonant-based fault-tolerant controller reduces the worst-peak torque error by about a factor of two compared with a standard Proportional-Integral controller, and a similar improvement is observed experimentally at 900 rpm. These results indicate that, relative to a conventional Proportional-Integral scheme, the Proportional-Integral-Resonant-based method provides stronger torque-ripple suppression under practical single open-circuit fault conditions while maintaining stable sensorless operation. For the Model Reference Adaptive System estimator, the Forgetting Factor Recursive Least Squares-enhanced Model Reference Adaptive System converges within 1 ms in simulation, keeps the identified parameters within 0.1% of their nominal values, and removes the approximate 2° position bias that appears with a fixed-parameter Model Reference Adaptive System using conventional Recursive Least Squares. Experimental results further confirm that, after step changes in the d- or q-axis current commands, the estimated rotor flux and stator inductance quickly reconverge to their nominal values with only small rotor-position errors. Compared with a traditional Recursive Least Squares implementation, the proposed Forgetting Factor Recursive Least Squares algorithm therefore improves robustness to parameter variations while avoiding matrix inversion. The results confirm that the proposed Model Reference Adaptive System sensorless estimation for Proportional-Integral-Resonant-based fault-tolerant control and Forgetting Factor Recursive Least Squares online parameter estimation strategies provide enhanced system robustness, improved estimation accuracy, and superior torque performance in More Electric Aircraft applications.

Many traditional fault tolerant flight control systems augment a baseline controller with an algorithm to detect and then isolate faults. Often, this entails estimating a new system dynamics model and automatic synthesis of new controller parameters. An alternate approach to fault tolerant control can be utilized if the basel ine controller is a direct adaptive control system. For failure modes that do not require control reconfiguration, this baseline adaptive controller demonstrates fault tolerance. This paper details the general formulation of a direct adaptive controller based on dynamic inversion with neural network adaptation. The implementation of this controller on several vehicles is also presented. In order to show the broad applicability of this approach, these vehicles are chosen from a wide range of categories, namely a tailless fighter, a reusable launch vehicle technology demonstrator, a helicopter, a ducted fan, and an acrobatic airplane. Results for nominal and fault cases for these vehicles are provided. Through this summary of fault tolerance results for each vehicle, direct adaptive control is shown to be well -suited to providing both nominal and fault tolerant control for vehicles from a wide range of categories.

The paper deals with the design of an active fault-tolerant control scheme, which is based on the actuator and sensor fault estimator. Thus, the paper starts with the development of such a fault estimation scheme capable of estimating these faults simultaneously. It is assumed that the estimator should have a desired \(H_\infty \) performance. Subsequently, a new fault-tolerant control law is proposed, which is based on a parallel digital twin of the system. Thus, the goal is to control the system in such a way as to follow the states of the references digital twin irrespective of the faults. Finally, the effectiveness of the proposed approach is verified with the laboratory three-tank system. In particular, the performance of the system is tested against a set of simultaneous actuator and sensor faults, respectively.

Thruster fault-tolerant control for dynamic positioning of vessels

Robust fault tolerant tracking controller design for a VTOL aircraft

The future of low altitude urban airspace utilization is poised to be transformed by the increasing dominance of small Unmanned Aerial Vehicles (UAVs). Their application can essentially be categorized as a threefold problem: establishing the regulatory principles for UAV operation, identification of the infrastructure needed to monitor the UAVs and ensure they adhere to the rules, and laying out the minimum performance requirements of the platforms so that they are capable of meeting the flight standards. This work addresses the pressing challenge of enhancing the performance envelope of small UAVs. The primary aim of this research is to develop an innovative overactuated multirotor system that augments UAV maneuverability, fault tolerance and operational safety. A crucial aspect of this study is overcoming the inherent underactuation limitations in standard quadrotors. This challenge is addressed through active propeller tilting, investigated in-depth through extensive real-world flight tests and simulations. The developed quadrotor, aptly named QuadPlus, efficiently combines actuator redundancy and thrust vectoring via propeller rotation in a compact package, compared to its state-of-the-art counterparts. Furthermore, a cascade control methodology based on incremental control allocation is devised to ensure stable attitude and velocity tracking even in the presence of actuator saturation and external disturbances during flight operations. The study showcases the successful realization of the QuadPlus multirotor system with an impressive 12 degrees of freedom. The innovative design allows for independent bi-axial tilting of 115 ° and 180 ° about two perpendicular axes while keeping the mechanical complexity relatively low. Real-world flight tests demonstrate the efficacy of the control methodology, showcasing stable hover and trajectory tracking in a desired hyperplane with accurate attitude tracking. Different test cases demonstrating the capability of QuadPlus to achieve symmetric (20 ° roll and pitch) and asymmetric (20 ° roll, 10 ° pitch and vice versa) attitude with static hover are presented. It is also tested against Level 3 wind conditions of 4m/s and actuator saturation. The extensive bi-axial tilting capability of the system enables precise force production of up to 9N for contact-based tasks, presenting promising potential for inspection-related applications. The research also significantly contributes to ensuring fail-safe UAV operations. A centralized fault-tolerant control (FTC) framework based on nonlinear model predictive control (NMPC) is proposed to address potential propeller failures, effectively mitigating attitude deviations and enhancing overall system control. The FTC framework is validated through intensive simulations, proving its effectiveness in maintaining stable flight even in the presence of failures. The system is successfully tested against a single propeller failure while following an attitude of 30 ° each in roll and pitch. It is also successfully tested for failure recovery in aggressive flights following an 8-shaped trajectory with the attitude varying between ±30 ° for roll and pitch, and ±25 ° for yaw. The corresponding maximum deviations from the commanded trajectory are observed to be within acceptable limits. Additionally, the research introduces a novel approach for on-board state-of-health (SoH) diagnostics of the battery, a critical component of the multirotor system. The energy equilibrium approach enables better management of battery performance, ensuring safe and reliable UAV operations while avoiding rapid performance deterioration. Experimental work is performed to validate the model. However, further analysis onboard QuadPlus is presented as future work as part of realizing the fault tolerance capabilities. It is hypothesized that the integration of the SoH diagnostics into the flight controller will help keep the current drawn within the safe functional limits of the battery. In summary, this research substantially advances the field of UAV technology by presenting a groundbreaking solution to the challenges posed by low altitude urban airspace utilization. The innovative overactuated multirotor system, QuadPlus, coupled with the fault-tolerant control framework and on-board component diagnostics approach, holds immense potential for inspection-related applications and interactions with the physical environment.

Purpose The purpose of this paper is to propose an adaptive neural-sliding mode-based observer for the estimation and reconstruction of unknown faults and disturbances for time-varying nonlinear systems such as aircraft, to ensure preciseness in the diagnosis of fault magnitude as well as the shape without enhancement of system complexity and cost. Fault-tolerant control (FTC) strategy based on adaptive neural-sliding mode is also proposed in the existence of faults for ensuring the stability of the faulty system. Design/methodology/approach In this paper, three strategies are presented: adaptive radial basis functions neural network (ARBFNN), conventional radial basis functions neural network (CRBFNN) and integral-chain differentiator. For the purpose of enhancement of fault diagnosis and isolation, a new sliding mode-based concept is introduced for the weight updating parameters of radial basis functions neural network (RBFNN).The main objective of updating the weight parameters adaptively is to enhance the effectiveness of fault diagnosis and isolation without increasing the computational complexities of the system. Results depict the effectiveness of the proposed ARBFNN approach in fault detection (FD) and approximation compared to CRBFNN, integral-chain differentiator and schemes existing in literature. In the second step, the FTC strategy is presented separately for each observer in the presence of unknown faults and failures for ensuring the stability of the system, which is validated on Boeing 747 100/200 aircraft. Findings The proposed adaptive neural-sliding mode approach is investigated, which depicts more effectiveness in numerous situations such as faults, disturbances and uncertainties compared to algorithms used in literature. In this paper, both the fault approximation and isolation and the fault tolerance approaches are studied. Practical implications For the enhancement of safety level as well as for avoiding any kind of damage, timely FD and fault tolerance have always had a significant role; therefore, the algorithms proposed in this research ensure the tolerance of faults and failures, which plays a vital role in practical life for avoiding any kind of damage. Originality/value In this study, a new neural-sliding mode concept is adopted for the adaptive faults approximation and reconstruction, and then the FTC algorithms are studied for each observer separately, whereas in previous studies, only the fault detection and isolation (FDI) or the fault tolerance problems were studied. Results demonstrate the effectiveness of the proposed strategy compared to the approaches given in the literature.

Fuzzy adaptive sliding mode fault estimation and fixed-time fault-tolerant control for coupled spacecraft based on SE(3)

Adaptive fault-tolerant shape control for nonlinear Lipschitz stochastic distribution systems

S INCE some catastrophic faults or failures may be induced due to the aging or damage of actuators and sensors during the mission of a spacecraft, those faults would lead to performance degradation of the spacecraft attitude control system or even result in the specified aerospacemission failure. Therefore, fault tolerance of the spacecraft attitude control system is one of the key issues that needs to be addressed. With a view to tackle such a challenge, fault-tolerant control (FTC) has received considerable attention in order to enhance the spacecraft reliability and to guarantee the attitude control performance [1–5]. In [5], an adaptive FTC is developed for the flexible spacecraft attitude tracking system where the persistent bounded disturbances, unknown inertia parameter, and even two types of reaction wheel faults are successfully accommodated. Indeed, the aforementioned approaches offer many attractive conceptual features, but at the same time they are derived based on the availability of direct and exact measurements of both the angular velocity and the attitude orientation. It is important to note, however, that when it comes to practical implementation, the angular velocity measurements are not always available because of either cost limitations or implementation constraints. Motivated from such a practical consideration, it is therefore highly desirable to develop partial state feedback attitude control strategies with spacecraft angular velocity measurements eliminated. The issue has been addressed in the literature by using observer-based control [6,7], Lyapunov-based control [8,9], and variable structure control [10] under normal operation of spacecraft. In this work, we provide solutions to two different problems of the flexible spacecraft attitude control system. The first problem consists of developing a control law to perform a attitude stabilization maneuver without angular velocity magnitude. In contrast with the velocity-free control schemes available in the literature, the presented approach can guarantee the attitude control performance be greatly robust to external disturbances and unknown inertia parameters. The second problem solved is the casewhere both loss of control effectiveness and additive fault occur in actuators simultaneously, but the attitude still requires stabilization with high resolution. To the best knowledge of the authors, this study is the first attempt to deal with fault-tolerant attitude stabilization control for flexible spacecraft with the angular velocity magnitude eliminated. The Note is organized as follows. Section II presents the mathematical model and attitude control problems formation of a flexible spacecraft under normal and faulty actuator conditions. Section III presents the proposed fault-tolerant attitude stabilization controller without velocity magnitude in the presence of two types of actuator faults. Simulation results to demonstrate various features of the proposed scheme are given in Sec. IV followed by conclusions in Sec. V.

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

SUMMARYThis paper is concerned with the fault tolerant synchronization problem for a class of complex interconnected neural networks against sensor faults. As sensor faults may lead to performance degradation or even instability of the whole network, fault tolerant control laws are designed to guarantee the controlled synchronization of the complex interconnected neural networks. On the basis of Lyapunov stability theory and adaptive schemes, three kinds of fault tolerant control laws are designed on the basis of linear matrix inequality technique. One is the passive fault tolerant control law, the other two are adaptive fault tolerant control laws. The latter two methods use the adaptive adjusting mechanism of the coupling coefficients to ensure the synchronization of the networks in the presence of sensor faults. Simulation results are given to verify the effectiveness of the proposed methods. Copyright © 2013 John Wiley & Sons, Ltd.

Dynamic Sensor Allocation Framework for Fault Tolerant Flight Control