Single Actuator Faults Research Articles

Fault Estimation Method for Nonlinear Time-Delay System Based on Intermediate Observer-Application on Quadrotor Unmanned Aerial Vehicle.

In this paper, the problem of actuator and sensor faults of a quadrotor unmanned aerial vehicle (QUAV) system is studied. In the system fault model, time delay, nonlinear term, and disturbances of QUAV during the flight are considered. A fault estimation algorithm based on an intermediate observer is proposed. To deal with a single actuator fault, an intermediate variable is introduced, and the intermediate observer is designed for the system to estimate fault. For simultaneous actuator and sensor faults, the system is first augmented, and then two intermediate variables are introduced, and an intermediate observer is designed for the augmented system to estimate the system state, faults, and disturbances. The Lyapunov-Krasovskii functional is used to prove that the estimation error system is uniformly eventually bounded. The simulation results verify the feasibility and effectiveness of the proposed fault estimation method.

Virtual Actuator Design for Uncertain Metzler Systems

The paper presents the design conditions adequate in design of virtual actuators and utilizable by nominal static output control structures in fault-tolerant control for strictly Metzler systems. The positive stabilization with H∞ norm performance is also addressed for virtual actuator design for strictly Metzler systems with interval uncertainty matrix representations of single actuator faults. Taking into account disturbance conditions and changes of values of variables after the virtual actuator activation, the design conditions are outlined in the terms of linear matrix inequalities. The approach provides a way to obtain acceptable dynamics of the closed loop system after virtual actuator activation.

Novel Actuator Fault Diagnosis Framework for Multizone HVAC Systems Using 2-D Convolutional Neural Networks

Heating, ventilation, and air conditioning (HVAC) systems are used to condition the indoor environment in buildings. They can be subjected to malfunctioning since they are the most extensively operated buildings’ components that account alone for almost half of the total building energy usage. Therefore, fault diagnosis (FD) of the HVAC system is important to maintain the system’s reliability and efficiency and provide preventive maintenance. This article presents a supervised FD strategy for single actuator faults in HVAC systems given that actuators, such as dampers and valves, are mostly prone to faults resulting in thermal discomfort and energy inefficiency in buildings. The proposed approach is based on 2-D convolutional neural networks (CNNs) using an efficient 1-D-to-2-D data transformation performed on the time-series signals acquired from the HVAC system. The performance of the CNNs is ensured by an optimal tuning of its significant hyperparameters using the Bayesian optimization algorithm toward maximizing the classification accuracy. The proposed 1-D-to-2-D data transformation approach is computationally efficient and eliminates the use of advanced signals preprocessing. It is performed in two schemes: the static and dynamic schemes to analyze the correlation between the system’s variables and consider the temporal effects of the time-series signals without compromising the detection time. The proposed approach is developed and validated using simulation data collected from a three-zone HVAC system simulator using Transient System Simulation Tool (TRNSYS). It demonstrates improved performance compared to the 1-D CNN-based approach and the other standard data-driven approaches for actuator FD in HVAC systems. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article was motivated by the problem of actuator faults, such as dampers and valves in heating, ventilation, and air conditioning (HVAC) systems. They are at risk of malfunctioning or failure resulting in reduced system efficiency, potential interference with supervision schemes execution, and equipment deterioration. This article presents a novel approach for single actuator faults in HVAC systems using the recently evolving topology of convolutional neural networks that are known for their high accuracy and reliable performance compared to the standard approaches. It utilizes the building historical data that can be obtained from the building management systems and without the need for either expert knowledge or details about the HVAC system. In future research, we plan to address the problem of multiple actuator faults, as well as simultaneous sensor and actuator faults.

Robust State Estimation for Positive Real Infinite-Dimensional Systems With Actuator and Sensor Faults

In this article, we propose a novel framework on the state estimation for a class of positive real infinite-dimensional systems, which suffer from unknown actuator and sensor faults and uncertain exogenous disturbance. Four cases of fault occurrence are taken into account: single multiplicative actuator fault, single multiplicative sensor fault, simultaneous actuator and sensor faults, and single actuator fault with a dead-zone nonlinearity. We develop new adaptive laws for the estimation of fault parameters and embed the proposed laws into the infinite dimensional state observer design. Moreover, by considering the actuator fault with a dead-zone nonlinearity, an infinite dimensional observer associated with coupled parameter update laws is developed to help to complete the fault accommodation. This is achieved by reconfiguring the actuator input based on the estimated information of parameters in the actuator fault map with a dead-zone nonlinearity.

Actuator fault-tolerant control study of an underwater robot with four rotatable thrusters

This paper presents the mathematical design and implementation of an actuator fault-tolerant control system for an underwater robot having four rotatable thrusters where the rotatable action of the thrusters is unconventional to a conventional underwater robotic system. Initially, the dynamic model of the robot is presented. Later, a motion control scheme using a backstepping control technique is made to track a desired spatial trajectory. Two techniques of active fault tolerance control viz., Elimination of Column Method, and Weighted-Pseudo Inverse Method are implemented successfully for single actuator faults on an infinity-shaped trajectory, which is a critical aspect of this study as most of the previous literature reported only on set point control. The methods mentioned above are extended to multiple thrusters failure, but both of them could not handle more than a single thruster failure. Hence, an attempt is made to accommodate two thrusters' failure through the line of sight approach by considering the vehicle as under-actuated. The desired vehicle performance is achieved with this approach. Finally, oceanic currents are modeled to simulate the effectiveness of the methods discussed in the paper to prove the performance capabilities of the control system and fault accommodation schemes under realistic conditions.

Active Fault-Tolerant Control With Imperfect Fault Detection Information: Applications to UAVs

A major issue in active fault-tolerant control (FTC) is having to rely on uncertain information provided by the fault detection and identification (FDI) algorithm. To achieve a reliable FTC, the controller needs to be robust against FDI uncertainties, namely missed “small” faults and fault detection delays. In this article, the FDI system only needs to indicate which actuator is faulty after a predefined amount of time, but does not need to estimate the actuator fault value or its faulty position. The goal is to design a FTC, which is robust against potentially undetected “small” actuator faults and which guarantees boundedness of the unstable poles for all possible actuator fault types. An adapted μ analysis is developed to analyze the unstable system poles, due to the presence of a fault. It is integrated within a DK-iteration approach to synthesize a controller in a robust control framework with H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> -design objectives. The synthesis is shown on a fixed-wing UAV, where fault-tolerance against single-actuator faults is achieved. Real flight experiments of a UAV with aileron and flap faults show the validity of the approach.

Advanced Fault Tolerant Air-Fuel Ratio Control of Internal Combustion Gas Engine for Sensor and Actuator Faults

The reliability of a process machine can be significantly enhanced by introducing a fault-tolerant control system in it. Hardware redundancy is an important aspect to enhance fault tolerance capability and is studied in this paper. A novel modified triple modular redundancy (MTMR) approach is proposed for the sensors to avoid a shutdown in the case of simultaneous faults in more than one sensor, and dual redundancy is proposed for the actuators to avoid a single point of failure due to the single actuator fault. The performance of the control system is verified by simulation in MATLAB Simulink environment. The proposed MTMR fulfills the gap in conventional TMR by maintaining stability even in the case of simultaneous faults in two channels. Cost and benefit analysis (CBA) is carried out to determine the financial feasibility of the implementation of the proposed system. The results of the CBA demonstrate that the proposed system is financially feasible due to the positive net present value and small breakeven period.

Relaxed formulation of the design conditions for Takagi-Sugeno fuzzy virtual actuators

Abstract The H∞ norm approach to virtual actuators design, intended to Takagi-Sugeno fuzzy continuous-time systems, is presented in the paper. Using the second Ljapunov method, the design conditions are formulated in terms of linear matrix inequalities in adapted bounded real lemma structures. Related to the static output controller, and for systems under influence of single actuator faults, the design steps are revealed for a three-tank system plant.

Adaptive Observer Based Actuator Faults Estimation

An approach to fault estimation systems design, adjusted for linear continuous-time systems, is proposed in the paper. Based on LMI approach, the method exploits the state-space observer principle in an adaptive scheme intended for single actuator faults. A simulation example, subject to different type of failures, demonstrates the effectiveness of the proposed form of the fault estimation technique.

An enhanced approach to actuator fault estimation design for linear continuous-time systems

An enhanced approach to fault estimation systems design, adjusted for linear continuous-time systems, is proposed in the paper. Based on LMI principle the method exploits state-space observer principle in an adaptive fault estimation scheme for single actuator faults. A simulation example, subject to different type of failures, demonstrates the effectiveness of the proposed form of the fault estimation technique.

Fault diagnosis and isolation of a complex system using a neural network observer

In this work, we use the approach based on neural observer in order to introduce the diagnosis of a non-linear system. The synthesis of such a trained specific observer using the back-propagation algorithm leads to an estimation study then a determination of fault diagnosis and isolation of single actuator fault based on residual generation. The robustness of the proposed observer is tested through a physical example. Finally, a comparison of observers’ performances will be interesting for judging the effectiveness of this approach. So, the obtained results will be compared to the sliding mode observer and the classic Luenberger observer.

An Iterative LMI Method to Discrete-time Reliable State-feedback Controller Design with Mixed H2/H∞ Performance

This paper studies the reliable mixed H 2 /H ∞ , state-feedback control of discrete-time linear systems based on the iterative linear matrix inequality (ILMI) approach. The design goal is to find an internally stabilizing state-feedback controller such that the nominal mixed H 2 /H ∞ performance measure of a closed-loop transfer matrix is optimized. The designed controller satisfies the H ∞ robust stability constraint and the reliability constraint (in terms of stability and performance) under actuator faults. Besides the advantage of optimizing nominal performance, this new reliable design has the flexibility that it can be formulated to tolerate the actuator faults within certain admissible set of actuators, or to tolerate any single actuator fault. Either partial or complete actuator fault is allowed. Two examples are also given to illustrate the design method and benefits.