Fault Compensation Research Articles

Adaptive Fault-Tolerant Control of Mobile Robots with Fractional-Order Exponential Super-Twisting Sliding Mode

Industrial mobile robots easily experience actuator loss of some effectiveness and additive bias faults due to the working scenarios, resulting in unexpected performance degradation. This article proposes a novel adaptive fault-tolerant control (FTC) strategy for nonholonomic mobile robot systems subject to simultaneous actuator lock-in-place (LIP) and partial loss-of-effectiveness (LOE) faults. First, a nominal fractional-order sliding mode controller based on the designed exponential super-twisting reaching law is investigated to reduce the reaching phase time and eliminate the chattering. To address the time-varying LIP faults and uncertainties, a novel barrier function (BF)-based gain is explored to assist the super-twisting law. An estimator is designed to estimate the lower bound of the time-varying partial LOE fault coefficients, thus without requiring the boundary information of faults that is commonly requested in traditional FTC schemes. Combined with the nominal controller clubbed with BF and estimator-based LOE fault compensation term, the fault-tolerant controller is finally constructed. The proposed FTC scheme achieves fast convergence and the sliding variables can be confined in a predetermined neighborhood of the sliding manifold under actuator faults. The results show that the proposed controller has superior tracking performance under faulty conditions compared with other state-of-the-art adaptive FTC approaches.

ADP-Based Fault-Tolerant Control for Multiagent Systems With Semi-Markovian Jump Parameters.

This article analyzes and validates an approach of integration of adaptive dynamic programming (ADP) and adaptive fault-tolerant control (FTC) technique to address the consensus control problem for semi-Markovian jump multiagent systems having actuator bias faults. A semi-Markovian process, a more versatile stochastic process, is employed to characterize the parameter variations that arise from the intricacies of the environment. The reliance on accurate knowledge of system dynamics is overcome through the utilization of an actor-critic neural network structure within the ADP algorithm. A data-driven FTC scheme is introduced, which enables online adjustment and automatic compensation of actuator bias faults. It has been demonstrated that the signals generated by the controlled system exhibit uniform boundedness. Additionally, the followers' states can achieve and maintain consensus with that of the leader. Ultimately, the simulation results are given to demonstrate the efficacy of the designed theoretical findings.

Coupled error super-twisted sliding mode active fault-tolerant control for robotic system with actuator fault.

This paper focuses on a robotic system with actuator fault and presents a sliding mode active fault-tolerant control method based on coupled position error. The actuator fault is first detected by a fault alerter with a predetermined threshold. After the fault is successfully detected, the fault is estimated by a fault observer. Coupling the position error with the weighted position error of different joints, a non-singular fast terminal sliding mode surface is constructed, and a super-twisted algorithm is introduced to design a coupled error super-twisted sliding mode controller (CESSMC). Furthermore, the fault estimation is incorporated with the CESSMC to accomplish the coupled error super-twisted sliding mode active fault-tolerant control. The stability and the finite-time convergence of the system are theoretically proved. Simulations and experiments are conducted to verify the effectiveness of the proposed method. The proposed method can achieve the position error convergence in finite time and reduce chattering in the control input. With the tight coupling between position error and weighted position error, the fault compensation effect and trajectory tracking accuracy can be improved.

Regenerative braking fault compensation control of distributed electric vehicle considering random wheel fault degree

Distributed drive electric vehicles can reduce range anxiety through regenerative braking. However, if the wheel motor torque output fails, it will form an additional yaw moment to the vehicle, causing instability, or deviation and threatening its safety. To solve this problem, the research object is an electric vehicle driven by a four-wheel hub motor. A braking force compensation distribution strategy for front and rear axles is proposed, which combines electronic hydraulic braking (EHB) system compensation control and deviation auxiliary control. Firstly, a fault detection module is established, and the motor’s output torque is estimated by designing a torque observer to obtain the fault degree information of the motor. Secondly, to fully use the motor’s regenerative braking force, the fault-free and faulty electro-hydraulic braking force distribution strategies are designed in the coordinated distribution layer of the electro-hydraulic braking system. The corresponding electro-hydraulic braking force compensation method is selected according to the fault degree of the regenerative braking function, the position of the faulty wheel, and the braking strength. Then, a deviation auxiliary controller is designed based on the model predictive control, and the intervention time of the auxiliary controller is determined according to the vehicle’s state. Finally, the control method is verified based on CarSim/Simulink co-simulation and hardware-in-the-loop (HIL) platform. The test results show that the designed control method can effectively compensate for the regenerative braking failure of random wheel and ensure the braking safety of the vehicle.

Command filter–based fixed-time fault estimation and compensation control for nonlinear systems with prescribed performance

Command filter–based fixed-time fault estimation and compensation control for nonlinear systems with prescribed performance

Current sensor unanticipated fault detection and compensation of 14.5-meter optical/infrared telescope drive system based on algebraic transformations

This paper discusses an unanticipated fault detection, isolation, and compensation (FDIC) strategy for the arc splicing permanent magnet synchronous motor (PMSM) operating under a promising 14.5-meter optical/infrared telescope drive system, specifically focusing on current sensors. The application is based on algebraic transformations that allow not only failure detection but also location and isolation. Besides, detection is performed merely by means of the measured current sensors and does not require additional knowledge or estimators; isolation utilizes information provided by detection to locate where the faults originated and release isolation signals; and compensation is carried out through the remaining currents that are not affected by the faults. It is noted from the results that the performance of FDIC in faulty mode is very acceptable and uncompromising in terms of fault detection, current symmetry, speed tracking, load torque and robustness remedial measures. Therefore, the proposed method can effectively ensure the stable operation of the drive system in the presence of faults.

Adaptive Fault-Tolerant Tracking Control for Discrete-Time Nonstrict-Feedback Nonlinear Systems With Stochastic Noises

This paper discusses the problem of fault-tolerant tracking control for discrete-time nonstrict-feedback nonlinear systems in the presence of stochastic noises and actuator faults. The system is characterized by a discrete-time nonstrict-feedback structure and multiplicative stochastic noise related to the states, which poses a challenge for the design and analysis of the fault-tolerant controller. Moreover, the considered actuator faults include multiplicative and additive faults without prior information. By integrating the properties of the backstepping framework and neural networks, and by introducing an adaptive fault compensation term, a novel fault-tolerant tracking control strategy is proposed. The effects of faults are compensated and the difficulties caused by the system structure are overcome, avoiding the algebraic loop problem and overcoming the causal contradiction. Given specific parameters, the designed fault-tolerant controller can ensure that the tracking error converges to an adjustable region regarding the origin and that all system signals are uniformly bounded concerning the mean-square sense. The simulation examples illustrate the effectiveness of the designed fault-tolerant control method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —As system complexity has been increasing, practical systems are often affected by faults when performing tracking control. Fault-tolerant control can provide acceptable robustness and improve system safety. On the one hand, many practical systems are nonlinear, difficult to model mathematically and accurately, and affected by stochastic noises. On the other hand, with digital control, the object is a discrete-time system. In practical applications, the upper bounds of the faults and the noises are often unknown. In this paper, a novel adaptive fault-tolerant control method is proposed for the more general uncertain discrete-time nonlinear systems, i.e., nonstrict-feedback nonlinear systems, with stochastic noises and actuator faults. Neural networks and an adaptive fault compensation term are integrated into the fault-tolerant controller. By adjusting the controller parameters properly, it is ensured that the tracking error converges to a small neighborhood of zero in the event of a fault occurring. In future research, sensor faults, input constraints, optimal control design, and applications in multi-agent systems will be considered.

Adaptive fixed-time fault-tolerant tracking control for rotary steerable drilling tool systems

In this paper, the problem of adaptive fixed-time fault-tolerant tracking control is investigated for rotary steerable drilling tool systems (RSDTSs). Markov jump system (MJS) is used to describe the RSDTS with varying parameters which are induced by the changing environment. By employing the smooth projection operator technique, adaptive laws are established to estimate the faults. Based on the fault compensation strategy, a new adaptive fixed-time fault-tolerant tracking control scheme is proposed to ensure that the RSDTS is globally stochastically practically fixed-time stable. In addition, to reduce the computational burden in the backstepping framework, the derivatives of the virtual control are directly derived using command filters. Finally, the experiment performed on the rotary steerable drilling tool systems prototype is exploited to demonstrate the feasibility and effectiveness of the proposed method.

Complex plane based adaptive method for protection of series compensated transmission line using phasor measurement unit data

Though differential relays are preferred for the protection of series-compensated transmission line (SCTL), they may mal-operate during current inversion, high resistance internal faults and current infeed/outfeed situations. Therefore, a new protection scheme for SCTL using Phasor Measurement Unit data, that adaptively manages the operating region in the current ratio complex plane according to the percentage compensation level, is presented. Boundaries of the operating region are determined adaptively based on the estimated impedance value of the series compensation. Usefulness of the technique is confirmed by generating cases covering wide range of fault parameters, compensation level, and load angle on an existing 400 kV Indian SCTL using PSCAD software as well as through Hardware in Loop simulation employing the Real Time Digital Simulator. Reported outcomes reveal the ability of the suggested algorithm in sensing all types of internal faults. Its performance remains unaffected during current/voltage inversion, operation of MOV and/or airgap during high fault current conditions, current infeed/outfeed situation, and external fault with current transformer saturation condition. Impact of the presence of noise in the acquired signals is also analyzed. The suggested technique is applicable for SCTLs having different voltage levels and power flow conditions. The proposed method has higher responsiveness during high resistance internal faults up to 500 Ω and better steadiness during external faults compared to numerous prevailing methods.

Current sensor fault-tolerant control based on modified Luenberger observers for safetycritical vector-controlled induction motor drives

Vector controlled drives require stator current information for use in current feedback and/or state variable estimators. That is why the detection and compensation of possible CS damage is so important. This article focuses on current sensor (CS) fault-tolerant control (FTC) in induction motor (IM) drive systems. In contrast to solutions known from the literature, two Modified Luenberger Observers (MLO) were applied, allowing for high-quality estimation of currents used in the detector and fault compensator. In a simple implementation of a detection algorithm based on residuals, an adaptive threshold coefficient was employed, enabling effective detection of various types of faults, regardless of whether the second current sensor was faulty or intact. The presented solution was evaluated during both motor and regenerative operation, with faults occurring in transient states, unlike solutions known in the literature.

Neural network adaptive switched fault-tolerant control of uncertain nonlinear systems with full state constraints

This paper studies the neural network adaptive fault-tolerant control (NNAFTC) for a class of uncertain nonlinear systems with full state constraints. It is the first time to introduce switched adaptive fault compensation strategy for the controller design process. On the one hand, the proposed method overcomes the limitation needed to be given a prescribed local restriction region of the traditional state constraint schemes, such as log-type, tan-type and integral-type. On the other hand, the full-state constraint and switched fault-tolerant problem is effectively solved even if the existence of actuator failures. Concomitantly, the novel switched tuning functions, the NN approximation technique and the integral barrier Lyapunov functions (IBLF) are combined to construct the backstepping controllers and adaptation laws. It can be proved that all the closed-loop states are restricted in the proper compact sets for any given initial values. Finally, A simulation is shown to demonstrate the validity and advantages of the presented control approach.

Torque fault compensation in electric vehicle switched reluctance motor drives: A jellyfish search optimization method

AbstractIn this paper, an enhanced indirect instantaneous‐torque‐control is proposed based on the torque sharing function approach of switched reluctance motor drives for electric vehicles by employing the jelly fish search. The major goal is to attain vehicle desires that include minimal torque ripple, maximum torque per ampere (MTPA), and huge performance and extend speed limit. First, a simplest analytic design is developed a determine more proficient turn‐on angle for the torque product. Second, an altered torque sharing function (TSF) is used for compensating the faults of torque tracking. The proposed technique is calculated to represent an accurate switched reluctance motor and its magnetized features. They have worked to create the machine model and execute the necessary transmits. The torque fault is evaluated and compensated inside the torque sharing function. The adapting TSF is compensates for the torque fault with receiving the phase because it is the minimal flux rate connecting variation. Finally, the jellyfish search technique is accepted to determine the optimal control parameters. The proposed strategies are done in MATLAB and its performance is contrasted with different existing strategies. According to the simulation result, the proposed strategy‐based accuracy is 94.2% at 50 iteration and 80% at 100th iteration which is higher than the existing methods. From this analyses, it proved that the proposed technique gives superior performance to existing one.

A Fault Detection and Compensation Strategy of the Resolver for Variable Leakage Flux Permanent Magnet Motor With Threshold Self-Regulation

A Fault Detection and Compensation Strategy of the Resolver for Variable Leakage Flux Permanent Magnet Motor With Threshold Self-Regulation

Voltage Error Estimation-Based Fault Diagnosis Method for Three- phase PWM-inverter in Grid-connected Photovoltaic Power System Without any Over-rating

Inverter is an essential component of a grid connected PV system. In fact, an open-switch fault in this power converter could result an important system malfunction and consequently leads to system disconnection. In this context, this paper focuses on the fault-tolerant control of PWM-inverter with redundancy leg for grid-connected PV system. In addition, a fast method of fault detection and compensation is used to maintain the continuous operation of the converter when there is a half-leg open-circuit fault (IGBT+ anti-parallel diode) on one of PWM-inverter legs. Therefore, it can detect this type of fault and compensate it in less than 50 μs by using a time criterion instead of voltage criterion. Also, the fuzzy logic technique is employed to control the active and reactive power injected into the network without exceeding the whole system power capacity limits. Note that, in this study, the active and reactive power references of the chosen operating point (the reactive-to-active power ratio: tgφ = Q/P = 0.19) are based on experimental tests. Simulation results show the feasibility and the effectiveness of the proposed fault diagnosis method in terms of fault detection and service continuity in presence of a half-leg open-circuit fault in PWM-inverter without any over-rating of the PV system components or instability.

Adaptive fault-tolerant control for attitude maneuvering under attitude constraints and finite sequential actuator faults

The problem of retargeting rigid body attitude with attitude constraints has been extensively investigated, whereas the challenge persists in maneuvering rigid-body attitude with multiple concurrent attitude constraints and finite sequential actuator faults. Finite sequential actuator faults, which can reduce controllability or destabilize the system, necessitate the implementation of fault-tolerant control strategies. Therefore, this paper aims to address the issue of redirecting spacecraft attitude subject to multiple attitude constraints and finite sequential actuator faults comprehensively. Firstly, we represent spacecraft attitude using unit quaternions and employ an artificial potential function to effectively handle multi-attitude constraints. The negative gradient direction guides the rigid-body spacecraft towards seamless convergence with the desired attitude. Our proposed unwinding strategy effectively avoids unwinding phenomena during large-angle spacecraft reorientation as well. Additionally, we design an adaptive compensation strategy for finite sequential actuator faults that enables real-time calculation of the fault compensation matrix under such actuator faults. Importantly, we propose an improved adaptive fault-tolerant back-stepping controller integrated with a potential function that effectively addresses both attitude constraints and finite sequential actuator faults simultaneously. Subsequently, stability analysis is conducted on the proposed controller to ensure its stability in practical applications rigorously. Finally, numerical simulations are performed meticulously to demonstrate the effectiveness and robustness of our proposed controller.

Fault-tolerant control for satellite autonomous rendezvous with quality characteristics and actuator uncertainties

An autonomous fault detection and fault-tolerant control solution combining Model Predictive Control (MPC) and Label Distributed Learning (LDL) is developed for the position tracking and attitude synchronization problems in autonomous satellite rendezvous and docking. The proposed algorithm can deal with center of mass (CM) variations and time-varying mass characteristics due to satellite fuel consumption, actuator saturation and fault, and external disturbances. Firstly, a six-degree-of-freedom (6-DOF) satellite translation-rotation coupling model was established to express the relative motion between the satellite and the target, taking the above factors into account. Subsequently, an on-board autonomous closed-loop fault-tolerant control algorithm using MPC is proposed, in which an LDL-based fault detection mechanism is embedded. The scheme specifies that propulsion faults are estimated by calculating the difference between the MPC's prediction of the satellite's future state and the measured change in the actual state. And the mapping matrix between the commanded force/torque and the actual force of the propulsion system is updated in real time to achieve autonomous fault detection and compensation on board the satellite. Among them, the LDL-based fault detection scheme is trained offline. It requires only simple matrix operations for on-orbit use, which is low-cost and suitable for resource-limited space environments. The additional creation of a time-varying disturbance observer allows the estimation and compensation of unmodelled errors and external disturbances. The stability of the proposed fault-tolerant control algorithm is rigorously demonstrated using Lyapunov analysis. Finally, numerical simulations show that the proposed method can successfully achieve autonomous satellite docking under different combinations of thruster faults.

Geometric Control and Structure-at-Infinity Control for Disturbance Rejection and Fault Compensation Regarding Buck Converter-Based LED Driver

Currently, various light-emitting diode (LED) lighting systems are being developed because LEDs are one of the most used lighting sources for work environments, buildings, homes, and public roads in terms of some of their applications. Similarly, they have low energy consumption, quick responses, and excellent optimal performance in their operation. However, these systems still need to precisely regulate lighting, maintain stable voltage and current in the presence of faults and disturbances, and have a wide range of operations in the event of trajectory changes or monitoring tasks regarding the desired voltage and current. This work presents the design and application of two types of robust controllers (structure-at-infinity control and geometric control) applied to an LED driver using a buck converter. The controllers aim to follow the desired trajectories, attenuate disturbances at the power supply input, and compensate for faults in the actuator (MOSFET) to keep the capacitor voltage and inductor current stable. When comparing the results obtained with the two controllers, it was observed that both present excellent performance in the presence of constant disturbances. However, in scenarios in which variable faults and path changes are implemented, the structure-at-infinity control method shows an overimpulse of output voltage and current ranging from 39 to 42 volts and from 0.3 to 0.45 A, with a margin of error of 1%, and it can generate a failure in the LED driver using a buck converter. On the other hand, when using geometric control, the results are satisfactory, achieving attenuating constant disturbances and variable faults, reaching the desired voltage (40 v to 35 v) and current (0.3 to 0.25 A) with a margin of error of 0.05%, guaranteeing a system without overvoltages or the accelerated degradation of the components due to magnetic conductivity.

Integrated sensor FTC using integral sliding mode control

In this paper, a sliding mode sensor fault tolerant control scheme which involves a first order sliding mode observer, fault compensation logic and an integral sliding mode controller, is proposed for a class of uncertain linear parameter-varying systems. The proposed scheme has the capability to retain near nominal fault-free performance in the face of a class of sensor faults/failures. In particular, the closed-loop stability of the sensor fault tolerant scheme involving the sliding mode observer and the sliding mode controller in the presence of faults and uncertainty, is rigorously analysed. Furthermore, the paper proposes an algorithm to simultaneously synthesize the design freedom associated with the observer gains and control law despite the lack of a separation principle in the closed loop system overall caused by the uncertainty. The proposed scheme is validated using a commercial aircraft model. Good simulation results show the efficacy of the scheme.

Adaptive Intelligent Minimum Parameter Singularity Free Sliding Mode Controller Design for Quadrotor

This paper presents a singularity free fast terminal sliding mode control (SFFTSMC) for position and attitude tracking of a quadrotor with unknown dynamics. The contribution of this work is threefold, namely: devising an SFFTSMC strategy using an auxiliary function to eliminate the singularity in the control law, a cost-saving minimum parameter update scheme using a fully connected recurrent neural network (FCRNN) to handle the unknown dynamics of quadrotor and development of an adaptive control law to compensate for the loss of effectiveness of the actuator and saturation effects, considered explicitly, without the requirement of any fault detection and diagnosis (FDD) unit. The proposed approach offers a direct singularity free control action in the presence of unknown dynamics, actuator faults, and saturation. Overall closed-loop stability is guaranteed in finite-time using Lyapunov stability theory and update laws for minimum parameters of FCRNN and fault compensator are derived using the same. Extensive simulations are presented for the trajectory tracking tasks using the proposed method and compared with the existing piece-wise fast terminal sliding mode controller (PFTSMC) and Radial basis function network (RBFN) based fault compensation approach. The proposed method is also validated in the Gazebo simulator via Pixhawk autopilot to demonstrate the feasibility in real-time. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This research is motivated by a cost-effective control scheme for quadrotors in cases of unknown/uncertain dynamics, external disturbances, actuator faults, and saturation. Precise quadrotor dynamics are difficult to obtain in real time. Also, there may be parametric uncertainties in quadrotor parameters like mass, inertia, and aerodynamic coefficients. External disturbances like wind gusts are always present in outdoor environments, and it may be the case that quadrotor motors lose their effectiveness due to defective motors or propeller damage while flying. To address these issues, first, it requires a precise control scheme to control the quadrotor while guaranteeing stability to ensure the safety of the quadrotor itself and people in the surrounding environment. Second, the approach should not be computationally heavy, which may sluggish the overall response of the quadrotor. Thus, we propose a control scheme to address these two issues simultaneously using a new fast terminal sliding mode control scheme augmented with FCRNN by updating minimum parameters instead of all the weight parameters of FCRNN. A compensator is introduced to mitigate the effect of unexpected actuator fault and saturation. The proposed approach can be helpful in various quadrotor applications, like pesticide spraying in agriculture, payload transportation, search and rescue, construction, etc., where unknown quadrotor dynamics and unknown payload situations occur.

Sensor fault detection and compensation with performance prescription for robotic manipulators

This paper focuses on sensor fault detection and compensation for robotic manipulators. The proposed method features a new adaptive observer and a new terminal sliding mode control law established on a second-order integral sliding surface. The method enables sensor fault detection without the need to know the bounds on fault value and/or its derivative. It also enables fast and fixed-time fault-tolerant control whose performance can be prescribed beforehand by defining funnel bounds on the tracking error. The ultimate boundedness of the estimation errors for the proposed observer and the fixed-time stability of the control system are shown using Lyapunov stability analysis. The effectiveness of the proposed method is verified using numerical simulations on two different robotic manipulators, and the results are compared with existing methods. Our results demonstrate performance gains obtained by the proposed method compared to the existing results.