Active Fault Tolerant Control Research Articles

NONLINEAR FAULT TOLERANT CONTROL OF DUAL THREE-PHASE INDUCTION MACHINES BASED ELECTRIC VEHICLES

This paper proposes a robust fault-tolerant control (FTC) for the dual three-phase (DTP) induction machines under failures and which is controlled by a higher-order sliding mode control strategy. However, the DTP induction machine is increasingly used because of its advantages such as better reliability and supply division, both passive and active FTC laws have been designed and tested on DTP. The proposed method not only realizes the FTC and the fault elimination as well but also provides a possible solution for emulating a traction system using a direct continue machine (DCM) supplied by a four-quadrant chopper. Therefore, the emulation system is based on a controlled DCM, which imposes the same behavior of the mechanical power train of an electric vehicle to the DTP. Simulation results are given to verify the robustness and good performance of the proposed fault-tolerant control scheme.

A controller management scheme for active fault-tolerant tracking: Linear discrete-time systems

This paper proposes an active fault-tolerant control (FTC) approach based on the controller management and virtual actuator idea for linear discrete-time systems subject to unknown L2-bounded disturbances, input constraint, and time-varying additive actuator faults. The closed-loop faulty system, which includes the modified nominal controller, the fault and state estimator, and the virtual actuator, suppresses the effects of disturbances and faults, while ensuring input-constraint satisfaction. The management of the nominal controller is performed through an online optimization method – in the form of a standard quadratic programming problem – by manipulating the reference input and intervening in the nominal controller evolution. The proposed method proves the input-to-state stability (ISS) criterion of the overall closed-loop faulty system. The problem of minimizing the ultimate bound of the ISS criterion is formulated in terms of tractable linear matrix inequality (LMI) conditions that allow the fault and state estimation errors to converge to a small neighborhood of the origin. To illustrate the capabilities and advantages of the proposed control strategy, comparative simulation results are presented for a flexible joint robotic system, tracking control of a DC motor’s angular velocity, and the multivariable VTOL aircraft.

An active fault tolerance framework for uncertain nonlinear high-order fully-actuated systems

This paper presents a novel active fault tolerance framework for uncertain high-order fully-actuated systems (HOFASs). Starting from the uncertain faulty HOFAS model with nonlinear measurement, the advantages of this description are revealed via Lie Derivatives. A HOFAS adaptive observer and controller integration is established and further a closed-loop HOFAS dynamic data modeling structure is derived. This structure uncovers the dynamic characteristics including fault features, and naturally yields a fault detectability condition. Based on the fault information from the dynamic data model, an active fault tolerant control strategy for HOFASs is proposed, which enriches HOFAS control theory. The uniformly bounded stability of the HOFAS model is proved theoretically and illustrated experimentally.

Avoiding contingent incidents by quadrotors due to one or two propellers failure.

With the increasing impact of drones in our daily lives, safety issues have become a primary concern. In this study, a novel supervisor-based active fault-tolerant (FT) control system is presented for a rotary-wing quadrotor to maintain its pose in 3D space upon losing one or two propellers. Our approach allows the quadrotor to make controlled movements about a primary axis attached to the body-fixed frame. A multi-loop cascaded control architecture is designed to ensure robustness, stability, reference tracking, and safe landing. The altitude control is performed using a proportional-integral-derivative (PID) controller, whereas linear-quadratic-integral (LQI) and model-predictive-control (MPC) have been investigated for reduced attitude control and their performance is compared based on absolute and mean-squared error. The simulation results affirm that the quadrotor remains in a stable region, successfully performs the reference tracking, and ensures a safe landing while counteracting the effects of propeller(s) failures.

Design of hybrid fault-tolerant control system for air-fuel ratio control of internal combustion engines using artificial neural network and sliding mode control against sensor faults

This paper proposes a novel hybrid fault-tolerant control system (HFTCS) with dedicated non-linear controllers: artificial neural network (ANN) and sliding mode control (SMC) for active and passive parts, respectively. The proposed system can provide both desirable properties of stability to unexpected fast disturbances and post-fault optimal performance. In the active fault tolerant control system (AFTCS) part, the fault detection and isolation (FDI) unit is designed through the use of ANN for the estimation of faulty sensor values in the observer model. In the passive fault-tolerant system (PFTCS) part, the air-fuel ratio (AFR) controller is designed using a robust SMC that allows systems to manage faults in predefined limits without estimation. In the proposed system, SMC will form the passive part to react instantly to faults while ANN will optimize post-fault performance with active compensation. Moreover, Lyapunov stability analysis was also performed to make sure that the system remains stable in both normal and faulty conditions. The simulation results in the Matlab/Simulink environment show that the designed controller is robust to faults in normal and noisy measurements of the sensors. A comparison with the existing works also demonstrates the superior performance of the proposed hybrid algorithm.

Active Fault-Tolerant Control Applied to a Pressure Swing Adsorption Process for the Production of Bio-Hydrogen

Pressure swing adsorption (PSA) technology is used in various applications. PSA is a cost-effective process with the ability to produce high-purity bio-hydrogen (99.99%) with high recovery rates. In this article, a PSA process for the production of bio-hydrogen is proposed; it uses two columns packed with type 5A zeolite, and it has a four-step configuration (adsorption, depressurization, purge, and repressurization) for bio-hydrogen production and regeneration of the beds. The aim of this work is to design and use an active fault-tolerant control (FTC) controller to raise and maintain a stable purity of 0.9999 in molar fraction (99.99%), even with the occurrence of actuator faults. To validate the robustness and performance of the proposed discrete FTC, it has been compared with a discrete PID (proportional–integral–derivative) controller in the presence of actuator faults and trajectory changes. Both controllers achieve to maintain stable purity by reducing the effect of faults; however, the discrete PID controller is not robust to multiple faults since the desired purity is lost and fails to meet international standards to be used as bio-fuel. On the other hand, the FTC scheme reduces the effects of individual and multiple faults by striving to maintain a purity of 0.9999 in molar fraction and complying with international standards to be used as bio-fuel.

Diagnosis and fault tolerant control against actuator fault for a class of hybrid dynamic systems

Over the past few decades, there have been increasing research activities in fault diagnosis (FD) and fault-tolerant control (FTC) for switched hybrid systems. This paper addresses the problem of active-fault tolerant control (AFTC) for switched hybrid systems subject to actuator faults to enhance system security and keep system stability. The proposed FTC is designed by adding the state feedback control with integral action to an additive control law which requires accurate fault estimation to compensate for the fault effect. Thus, a data-based projection method (DPM) is extended (EDPM) based on inputs and outputs measures to estimate the fault without using mathematical models. The synthesis of the state feedback control with integral action is proposed for recovering the desired performances. It integrates a set of controllers corresponding to a set of partial models to design a set of switching control laws. Indeed, new linear matrix inequalities (LMIs) using Lyapunov stability analysis are proposed to find the optimal values of the control gains matrices and keeping system stability. A comparative study of the proposed FTC with existing work is given to show the effectiveness of the proposed technique.

An Integrated Design Approach for Fault-Tolerant Control of Switched LPV Systems With Actuator Faults

In this article, the active fault-tolerant control (FTC) issue is addressed for switched linear parameter varying (LPV) systems in the discrete-time domain. A general dwell-time property is considered in the system setup to govern the switching dynamics between subsystems, and the parameter variations within each subsystem are subjected to the polytopic uncertainties. The main innovation of the developed active FTC approach is to effectively cope with switched LPV models where both input and output matrices can be of parameter-dependent form. By virtue of a novel Lyapunov function approach depending on both dwell time and parameter variations, the joint task for fault detection, estimation, and compensation is fulfilled via an integrated design scheme. The input-to-state stability (ISS) conditions are obtained for the augmented faulty system satisfying a given ISS-gain performance requirement. The desired effect of active FTC is achieved in three critical steps: 1) construct a fault detection filter in terms of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_{\infty }$ </tex-math></inline-formula> norm; 2) design an observer-based estimator to estimate the system states and faults simultaneously; and 3) synthesize a fault-tolerant controller with the LPV structure using the estimated states and faults for fault compensation. Finally, an application example is utilized to illustrate the efficiency and availability of the proposed control approach.

Sliding-mode observer–based active fault-tolerance control for a two-degree-of-freedom helicopter system with sensor faults

In this paper, an active fault-tolerance controller is proposed for a two-degree-of-freedom (2-DOF) helicopter model with different types of sensor faults. The proposed controller is designed by combining an interval type-2 fuzzy logic control approach with a sliding-mode control technique. In addition, the controller is compensated by a sliding-mode observer used to estimate faults in real-time. For the proposed control scheme, the overall stability of the closed-loop system is proven using the Lyapunov stability theory. Finally, numerical simulations and experiments verify that the proposed scheme achieves superior control performance in the case of sensor failure.

Multirotor Motor Failure Detection with Piezo Sensor

Failure detection of Unmanned Aerial Vehicle (UAV) motors and propulsion systems is the most important step in the implementation of active fault-tolerant control systems. This will increase the reliability of unmanned systems and increase the level of safety, especially in civil and commercial applications. The following paper presents a method of motor failure detection in the multirotor UAV using piezo bars. The results of a real flight, in which the failure of the propulsion system caused the crash of a hybrid VTOL UAV, were presented and analyzed. The conclusions drawn from this flight led to the development of a lightweight, simple and reliable sensor that can detect a failure of the UAV propulsion system. The article presents the outcomes of laboratory tests concerning measurements made with a piezo sensor. An extensive analysis of the obtained results of vibrations recorded on a flying platform arm with a propulsion system is presented, and a methodology for using this type of data to detect failures is proposed. The article presents the possibility of using a piezoelectric sensor to record vibrations on the basis of which it is possible to detect a failure of the UAV propulsion system.

Active Fault-Tolerant Control Based on MPC and Reinforcement Learning for Quadcopter with Actuator Faults

In this paper, we propose an active fault-tolerant control (AFTC) method combining model predictive control (MPC) and reinforcement learning (RL) for the quadcopter with actuator faults. We take a data-based discriminant model as the fault detection and diagnosis (FDD) module indicating a system fault mode based on the state error. With the information of the fault mode and the state error, the RL controller generates auxiliary control signals to correct the system. To configure the MPC controller quickly, we propose an auxiliary signal-based method for estimation of fault parameters and prove its convergence. The AFTC framework reduces requirements for accurate modeling, and avoids the instability of the RL controller under a continuous operation. To validate the effectiveness of the proposed framework, two trajectory tracking simulations with single and multiple faults are carried out. The simulation results show satisfactory performance and verify that the proposed framework is real-time applicable.

Fault-Tolerant Control of Gas-Lifted Oil Well

The gas-lifted system has inherent ability to hide the effect of fault hence the system can inject gas into the annulus and oil will still be produced even in the presence of fault of significant value. This however affects the optimal operation of the system and could move the system towards the undesirable casing-heading instability. Faults of step decrease in the valves coefficients in addition to limitation on the valve affect the optimal flow of the liquids through the system. We detect and isolate these faults using generalised likelihood ratio test (GLRT) and Dedicated observer scheme (DOS) respectively. The states of the system are estimated using extended Kalman filter (EKF). Model predictive control based fault-tolerant control is then implemented on the system by using the robustness property of the zone control MPC and limiting the input bound in the optimiser. Both passive and active fault-tolerant control (FTC) were used to improve oil production or stabilise the system. Passive fault-tolerant control (FTC) provides more robustness but it does not change oil production noticeably enough. Reducing the upper control bound ensures stability but production could decline. Increasing the controller cost that prioritises the input target increases production but it is prone to casing-heading instability.

Fault Tolerant Control for Tilted Hexarotors Under a Rotor Failure

This paper addresses the active fault tolerant control problem for a tilted hexarotor under both actuator faults and failures, modelled respectively as partial or total losses of effectiveness. A disturbance observer based control approach is adopted in order to estimate faults and failures, and cope with them at the control level. An inner-outer loop tracking control law is then designed which, thanks to the actuation properties of the hexarotor, does not require any reconfiguration neither in response to a fault nor failure. The control scheme is tested in simulation, with parameters of a real hexarotor and realistic sensor noise.

Povećanje performansi aktivne kontrole otporne na greške u svemirskoj letelici korišćenjem neuronskih mreža

Actuator fault poses a challenge to the attitude control of spacecraft. Fault-tolerant control (active or passive) is often used to overcome this challenge. Active methods have better performance than passive methods and can manage a broader range of faults. However, their implementation is more difficult. One reason for this difficulty is the critical reaction time. The system may become unrecoverable if the actual reaction time becomes larger than the critical reaction time. This paper proposes using a feedforward neural network to reduce the actual reaction time in the active fault-tolerant control of spacecraft. Besides this improvement, using a feedforward neural network can increase the success percentage. Success percentage is the ratio of successful simulations to the total number of simulations. Simulation results show that for 200 simulations with random faults and initial conditions, the actual reaction time decreases by 73%, and the success percentage increases by 25%. Based on these results, the proposed controller is a good candidate for practical applications.

Neural network-based sensor fault estimation and active fault-tolerant control for uncertain nonlinear systems

In this work, we developed a novel active fault-tolerant control (FTC) design scheme for a class of nonlinear dynamic systems subjected simultaneously to modelling imperfections, parametric uncertainties and sensor faults. Modelling imperfections and parametric uncertainties are dealt with using an adaptive radial basis function neural network (RBFNN) that estimates the uncertain part of the system dynamics. For sensor fault estimation (FE), a nonlinear observer based on the estimated dynamics is designed. A scheme to estimate sensor faults in real-time using the nonlinear observer and an additional RBFNN is developed. The convergence properties of the RBFNN, used in the fault FE part, are improved by using a sliding surface function. For FTC design, a sliding surface is designed that incorporates the real-time sensor FE. The resulting sliding mode control (SMC) technique-based FTC law uses the estimated dynamics and real-time sensor FE. A double power-reaching law is adopted to design the switching part of the control law to improve the convergence and mitigate the chattering associated with the SMC. The FTC works well in the presence and absence of sensor faults without the requirement for controller reconfiguration. The stability of the proposed active FTC law is proved using the Lyapunov method. The developed scheme is implemented on a nonlinear simulation of an unmanned aerial vehicle (UAV). The results show good performance of the proposed unified FE and the FTC framework.

Active sensor fault tolerant control of bus voltage in standalone low voltage DC microgrid

Active sensor fault tolerant control of bus voltage in standalone low voltage DC microgrid

Wide-Speed Range Sensorless Control of Five-Phase PMSM Drive under Healthy and Open Phase Fault Conditions for Aerospace Applications

This paper presents a speed sensorless control of a five-phase PMSM in healthy operation and under the Open-Phase Fault on any phase of the machine. The solution is recommended for mission-critical applications requiring high reliability capacities, such as Aerospace applications. An adapted Active Fault Tolerant Control is proposed with the aim of obtaining electromechanical torque as close as possible to that normally developed by a machine working in healthy condition. In instances of a loss of power to one phase of the machine, a reconfiguration of the control law is performed to ensure the continuity of service and to maintain acceptable control performances without requiring a hardware rearrangement of the power architecture. The motor rotation speed and position, required for the Field Oriented Control (FOC) of the stator currents, are estimated using a Back-Electromotive Forces (Back-EMF) observer based on a mathematical model of the motor and implemented in the stator diphase reference frame. Different electrical models that describe the behavior of the five-phase machine in the normal and degraded operations are given. Experimental results on a 1.25 kW synchronous PM machine are shown to confirm the effectiveness of the motor control.

Active fault-tolerant control of cable-driven parallel robots

Active fault-tolerant control of cable-driven parallel robots

Observer‐based single‐network incremental adaptive dynamic programming for fault‐tolerant control of nonlinear systems with actuator faults

SummaryA model‐free incremental adaptive fault‐tolerant control (FTC) scheme is proposed for a class of nonlinear systems with actuator faults. To deal with actuator faults and guarantee the approximate optimal performance of the nominal nonlinear system without any prior knowledge of system dynamics, a single‐network incremental adaptive dynamic programming (SIADP) algorithm based on incremental neural network observer is developed to design an active fault‐tolerant control (AFTC) policy. An approximate linear time‐varying system is obtained by incremental nonlinear technique, in which the relevant matrix parameters are identified by recursive least square estimation. Then, a SIADP algorithm‐based fault‐tolerant controller is developed. Based on the redundancy characteristic and function of actuators, a grouping scheme of actuators is introduced. An incremental neural network observer is designed to approximate the actuator faults. The novel SIADP scheme is constructed with a simplified single critic neural network to shorten the learning time and decrease the computational burden in the control process, in which the norm of the weight estimations of critic neural network is updated. Moreover, based on the Lyapunov theorem, the uniformly ultimately bounded stability of the closed‐loop incremental system is proved. Finally, simulations are given to verify the effectiveness of the proposed FTC scheme.

Design of Active Fault-Tolerant Control System for Air-Fuel Ratio control of Internal Combustion engine using nonlinear regression-based observer model.

Internal Combustion (IC) engines are prevalent in the process sector, and maintaining sufficient Air-Fuel Ratio (AFR) regulation in their fuel system is crucial for enhanced engine performance, fuel economy, and environmental safety. Faults in the AFR system's sensors cause the engine to shut down, hence, fault tolerance is essential. In order to avoid engine shutdown, this paper offers a novel Active Fault-Tolerant Control System (AFTCS) for air-fuel ratio control of an Internal Combustion (IC) engine in a process plant. In the Fault Detection and Isolation (FDI) unit, the proposed AFTCS uses a nonlinear regression-based observer model for analytical redundancy. The suggested system was simulated in the MATLAB / Simulink environment. The proposed system was tested at two different speeds (300 r/min and 600 r/min) and the results show that the system's response is within the acceptable bound without compromising the stability. The findings also demonstrate the higher fault tolerance capability for sensor defects of the AFR control system, particularly for the MAP sensor (at 300 r/min) in terms of reduced oscillatory response in comparison to the current literature. Compared to the linear regression-based and Genetic Algorithm (GA) based model, the nonlinear regression-based model results in a more accurate estimation of the faulty sensors. The proposed model is also efficient in terms of computation power and response time.