Fault-tolerant control under controller-driven sampling using virtual actuator strategy

We present a new output feedback fault tolerant control strategy for continuous-time linear systems. The strategy combines a digital nominal controller under controller-driven (varying) sampling with virtual-actuator (VA)-based controller reconfiguration to compensate for actuator faults. In the proposed scheme, the controller controls both the plant and the sampling period, and performs controller reconfiguration by engaging in the loop the VA adapted to the diagnosed fault. The VA also operates under controller-driven sampling. Two independent objectives are considered: (a) closed-loop stability with setpoint tracking and (b) controller reconfiguration under faults. Our main contribution is to extend an existing VA-based controller reconfiguration strategy to systems under controller-driven sampling in such a way that if objective (a) is possible under controller-driven sampling (without VA) and objective (b) is possible under uniform sampling (without controller-driven sampling), then closed-loop stability and setpoint tracking will be preserved under both healthy and faulty operation for all possible sampling rate evolutions that may be selected by the controller

Deep Learning-Based, Passive Fault Tolerant Control Facilitated by a Taxonomy of Cyber-Attack Effects

In the interest of improving the resilience of cyber-physical control systems to better operate in the presence of various cyber-attacks and/or faults, this dissertation presents a novel controller design based on deep-learning networks. This research lays out a controller design that does not rely on fault or cyber-attack detection. Being passive, the controller’s routine operating process is to take in data from the various components of the physical system, holistically assess the state of the physical system using deep-learning networks and decide the subsequent round of commands from the controller. This use of deep-learning methods in passive fault tolerant control (FTC) is unique in the research literature. The proposed controller is applied to both linear and nonlinear systems. Additionally, the application and testing are accomplished with both actuators and sensors being affected by attacks and /or faults

Fault tolerant control for wind turbine pitch actuators

This paper develops a fault detection and isolation (FDI) and active fault tolerant control (FTC) of pitch actuators in wind turbines (WTs). This is accomplished combining a disturbance compensator with a controller, both of which are formulated in the discrete-time domain. The disturbance compensator has a dual purpose: to reconstruct the actuator fault (which is used by the FDI technique) and to design the discrete-time controller to obtain an active FTC. That is, the actuator faults are reconstructed and then the control inputs are modified with the reconstructed fault signal to achieve a FTC in the presence of actuator faults with a comparable behavior to the fault-free case. The proposed techniques are validated using the aeroelastic wind turbine simulator FAST. This software is designed by the U.S. National Renewable Energy Laboratory and is widely used for studying wind turbine control systems.Peer ReviewedPostprint (published version

Active actuator fault-tolerant control of a wind turbine benchmark model

This paper describes the design of an active fault-tolerant control scheme that is applied to the actuator of a wind turbine benchmark. The methodology is based on adaptive filters obtained via the nonlinear geometric approach, which allows to obtain interesting decoupling property with respect to uncertainty affecting the wind turbine system. The controller accommodation scheme exploits the on-line estimate of the actuator fault signal generated by the adaptive filters. The nonlinearity of the wind turbine model is described by the mapping to the power conversion ratio from tip-speed ratio and blade pitch angles. This mapping represents the aerodynamic uncertainty, and usually is not known in analytical form, but in general represented by approximated two-dimensional maps (i.e. look-up tables). Therefore, this paper suggests a scheme to estimate this power conversion ratio in an analytical form by means of a two-dimensional polynomial, which is subsequently used for designing the active fault-tolerant control scheme. The wind turbine power generating unit of a grid is considered as a benchmark to show the design procedure, including the aspects of the nonlinear disturbance decoupling method, as well as the viability of the proposed approach. Extensive simulations of the benchmark process are practical tools for assessing experimentally the features of the developed actuator fault-tolerant control scheme, in the presence of modelling and measurement errors. Comparisons with different fault-tolerant schemes serve to highlight the advantages and drawbacks of the proposed methodology

Controle reconfigurável de processos sujeitos a falhas em atuadores : uma abordagem baseada no MPC em duas camadas

Orientadores: Flávio Vasconcelos da Silva, Thiago Vaz da CostaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia QuímicaResumo: Plantas industriais modernas estão suscetíveis a falhas em equipamentos de processo e em instrumentos e componentes da malha de controle. Tais eventos anormais podem acarretar danos a equipamentos, degradação do desempenho do processo e até cenários extremos como a parada da planta e acidentes graves. Em vista disso, o emprego de sistemas de controle tolerante a falhas visa a elevar o grau de confiabilidade e segurança do processo por meio do tratamento e mitigação de eventos anormais, evitando que evoluam para situações críticas. Nesse sentido, este trabalho tem como objetivo desenvolver uma técnica de controle reconfigurável tolerante a falhas para processos sujeitos a falhas em atuadores. A presente proposta é baseada em abordagens por atuadores virtuais e ocultação da falha. Essas técnicas consistem no recálculo das ações de controle e na ocultação da falha do ponto de vista do controlador nominal, permitindo que o mesmo seja mantido após a reconfiguração da malha de controle. Na presente proposta, o atuador virtual é baseado na estrutura do controlador preditivo em duas camadas. Uma camada consiste no cálculo de referências para as variáveis de entrada e para o desvio previsto entre o comportamento da planta nominal e com falha. A outra camada, por sua vez, é responsável por conduzir as variáveis de processo para as referências calculadas na etapa anterior. Ambas as camadas são baseadas em problemas de programação quadrática e levam em consideração as restrições do processo, como limites de atuadores e desvios permissíveis em relação ao comportamento nominal da planta. Essa técnica possibilita a consideração de cenários de falhas nos quais não há graus de liberdade suficientes para a manutenção de variáveis controladas em valores desejados. Assim, a estimativa de perturbações permite que novas referências atingíveis sejam calculadas, ainda que haja erros de identificação do modelo pós-falha do processo. Por fim, a estrutura de controle proposta foi aplicada em simulações utilizando um processo de tanques quádruplos, bem como em experimentos conduzidos em uma planta de neutralização de pHAbstract: Modern industrial plants are susceptible to faults in process equipment and in instruments and components of the control loop. Such abnormal events can lead to equipment damage, degradation of process performance and even extreme scenarios such as plant shutdown and serious accidents. Thus, the use of fault-tolerant control systems aims to increase process reliability and safety by treating and mitigating abnormal events, preventing them from evolving to critical situations. In this sense, this work aims to develop a reconfigurable fault tolerant control technique for processes subject to actuator faults. The present proposal is based on the virtual actuator and fault hiding approaches. These techniques consist of recomputing control actions and hiding the fault from the nominal controller perspective, allowing it to be maintained after the control loop reconfiguration. We propose a virtual actuator based on the two-layer model predictive control structure. One layer consists of calculating references for input variables and for the predicted deviation between the nominal and faulty plant behaviors. The other layer, in turn, is responsible for driving process variables to the references calculated in the previous step. Both layers are based on quadratic programming problems and take into account process constraints such as actuator limits and permissible deviations from the nominal plant behavior. This technique allows the consideration of fault scenarios in which there are not enough degrees of freedom for the maintenance of controlled variables in desired values. Thus, disturbance estimation allows the calculation of new achievable references, even though there are identification errors in the post-fault model. Finally, the proposed control structure has been applied to an experimental pH neutralization plant. Finally, the proposed control structure was applied in simulations to a quadruple-tank process as well as in experiments conducted in a pH neutralization plantMestradoSistemas de Processos Quimicos e InformaticaMestre em Engenharia Química130952/2015-0CNP

Wind Turbine Active Fault Tolerant Control Based on Backstepping Active Disturbance Rejection Control and a Neurofuzzy Detector

© 2023 The Author(s). Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Wind energy conversion systems have become an important part of renewable energy history due to their accessibility and cost-effectiveness. Offshore wind farms are seen as the future of wind energy, but they can be very expensive to maintain if faults occur. To achieve a reliable and consistent performance, modern wind turbines require advanced fault detection and diagnosis methods. The current research introduces a proposed active fault-tolerant control (AFTC) system that uses backstepping active disturbance rejection theory (BADRC) and an adaptive neurofuzzy system (ANFIS) detector in combination with principal component analysis (PCA) to compensate for system disturbances and maintain performance even when a generator actuator fault occurs. The simulation outcomes demonstrate that the suggested method successfully addresses the actuator generator torque failure problem by isolating the faulty actuator, providing a reliable and robust solution to prevent further damage. The neurofuzzy detector demonstrates outstanding performance in detecting false data in torque, achieving a precision of 90.20% for real data and 100%, for false data. With a recall of 100%, no false negatives were observed. The overall accuracy of 95.10% highlights the detector’s ability to reliably classify data as true or false. These findings underscore the robustness of the detector in detecting false data, ensuring the accuracy and reliability of the application presented. Overall, the study concludes that BADRC and ANFIS detection and isolation can improve the reliability of offshore wind farms and address the issue of actuator generator torque failure.Peer reviewe

Fault Diagnosis and Fault-Tolerant Control of Unmanned Aerial Vehicles

With the increasing demand for unmanned aerial vehicles (UAVs) in both military and civilian applications, critical safety issues need to be specially considered in order to make better and wider use of them. UAVs are usually employed to work in hazardous and complex environments, which may seriously threaten the safety and reliability of UAVs. Therefore, the safety and reliability of UAVs are becoming imperative for development of advanced intelligent control systems. The key challenge now is the lack of fully autonomous and reliable control techniques in face of different operation conditions and sophisticated environments. Further development of unmanned aerial vehicle (UAV) control systems is required to be reliable in the presence of system component faults and to be insensitive to model uncertainties and external environmental disturbances. This thesis research aims to design and develop novel control schemes for UAVs with consideration of all the factors that may threaten their safety and reliability. A novel adaptive sliding mode control (SMC) strategy is proposed to accommodate model uncertainties and actuator faults for an unmanned quadrotor helicopter. Compared with the existing adaptive SMC strategies in the literature, the proposed adaptive scheme can tolerate larger actuator faults without stimulating control chattering due to the use of adaptation parameters in both continuous and discontinuous control parts. Furthermore, a fuzzy logic-based boundary layer and a nonlinear disturbance observer are synthesized to further improve the capability of the designed control scheme for tolerating model uncertainties, actuator faults, and unknown external disturbances while preventing overestimation of the adaptive control parameters and suppressing the control chattering effect. Then, a cost-effective fault estimation scheme with a parallel bank of recurrent neural networks (RNNs) is proposed to accurately estimate actuator fault magnitude and an active fault-tolerant control (FTC) framework is established for a closed-loop quadrotor helicopter system. Finally, a reconfigurable control allocation approach is combined with adaptive SMC to achieve the capability of tolerating complete actuator failures with application to a modified octorotor helicopter. The significance of this proposed control scheme is that the stability of the closed-loop system is theoretically guaranteed in the presence of both single and simultaneous actuator faults

Optimal fault-tolerant flight control for aircraft with actuation impairments

Current trends towards greater complexity and automation are leaving modern technological systems increasingly vulnerable to faults. Without proper action, a minor error may lead to devastating consequences. In flight control, where the controllability and dynamic stability of the aircraft primarily rely on the control surfaces and engine thrust, faults in these effectors result in a higher extent of risk for these aspects. Moreover, the operation of automatic flight control would be suddenly disturbed. To address this problem, different methodologies of designing optimal flight controllers are presented in this thesis. For multiple-input multiple-output (MIMO) systems, the feedback optimal control is a prominent technique that solves a multi-objective cost function, which includes, for instance, tracking requirements and control energy minimisation. The first proposed method is based on a linear quadratic regulator (LQR) control law augmented with a fault-compensation scheme. This fault-tolerant system handles the situation in an adaptive way by solving the optimisation cost function and considering fault information, while assuming an effective fault detection system is available. The developed scheme was tested in a six-degrees-of-freedom nonlinear environment to validate the linear-based controller. Results showed that this fault tolerant control (FTC) strategy managed to handle high magnitudes of the actuator’s loss of effciency faults. Although the rise time of aircraft response became slower, overshoot and settling errors were minimised, and the stability of the aircraft was maintained. Another FTC approach has been developed utilising the features of controller robustness against the system parametric uncertainties, without the need for reconfiguration or adaptation. Two types of control laws were established under this scheme, the H∞ and µ-synthesis controllers. Both were tested in a nonlinear environment for three points in the flight envelope: ascending, cruising, and descending. The H∞ controller maintained the requirements in the intact case; while in fault, it yielded non-robust high-frequency control surface deflections. The µ-synthesis, on the other hand, managed to handle the constraints of the system and accommodate faults reaching 30% loss of effciency in actuation. The final approach is based on the control allocation technique. It considers the tracking requirements and the constraints of the actuators in the design process. To accommodate lock-in-place faults, a new control effort redistribution scheme was proposed using the fuzzy logic technique, assuming faults are provided by a fault detection system. The results of simulation testing on a Boeing 747 multi-effector model showed that the system managed to handle these faults and maintain good tracking and stability performance, with some acceptable degradation in particular fault scenarios. The limitations of the controller to handle a high degree of faults were also presented

Fault-tolerant load reduction control for large offshore wind turbines

Offshore wind turbines suffer from asymmetrical loading (blades, tower etc.), leading to enhanced structural fatigue. As well as asymmetrical loading different types of faults (pitch system faults etc.) can occur simultaneously, causing degradation of load mitigation performance and enhanced fatigue. Individual pitch control (IPC) provides an important method to achieve mitigation of rotor asymmetric loads, but this may be accompanied by a resulting enhancement of pitch movement leading to increased possibility of pitch system faults, which negative effects on IPC performance.This thesis focuses on combining the fault tolerant control (FTC) techniques with load reduction strategies by a more intelligent pitch control system (i.e. collective pitch control and IPC) for offshore wind turbines in a system level to reduce the operation & maintenance costs and improve the system reliability. The scenario of load mitigation is analogous to the FTC problem because the action of rotor/tower bending can be considered as a fault effect. The essential concept is to attempt to account for all the "fault effects" in the rotor and tower systems which can weaken the effect of bending moment reduction through the use of IPC.Motivated by the above, this thesis focuses on four aspects to fill the gap of the combination between FTC and IPC schemes. Firstly, a preview control system using model predictive control with future wind speed is proposed, which could be a possible alternative to using LiDAR technology when using preview control for load reduction. Secondly, a multivariable IPC controller for both blade and tower load mitigation considering the inherent couplings is investigated. Thirdly, appropriate control-based fault monitoring strategies including fault detection and fault estimation FE-based FTC scheme are proposed for several different pitch actuator/sensor faults. Furthermore, the combined analysis of an FE-based FTC strategy with the IPC system at a system level is provided and the robustness of the proposed strategy is verified