Tolerant Control Research Articles

Alternative splicing drives the functional diversification of a bHLH transcription factor in the control of growth and drought tolerance in rice

Alternative splicing drives the functional diversification of a bHLH transcription factor in the control of growth and drought tolerance in rice

Online Full Range Copper Loss Minimization for Single-Phase Short-Circuit Fault Tolerant Control in Five-Phase PMSM

Online Full Range Copper Loss Minimization for Single-Phase Short-Circuit Fault Tolerant Control in Five-Phase PMSM

Fault tolerant control of permanent magnet synchronous motor based on hybrid control strategies DTC-SVM with second order sliding mode control using multi-variable filter

This paper describes direct torque control (DTC) of a permanent magnet synchronous machine (PMSM) powered by a two-level voltage inverter whose switching of switches is based on the Space Vector Modulation. To overcome the robustness of the control to the presence of a fault, we included an improvement of the direct torque control with Space vector modulation (DTC-SVM) by the use of the filters for the flux and the torque and compared to the direct torque control of the DTC-SVM, the PI controllers are replaced with sliding mode blocks, This control method allows giving a new structure DTC -SVM with sliding mode control. The analysis of the results shows good performances for the speed and a considerable reduction of the fluctuations at the level of the torque and the flux.

Adaptive Takagi–Sugeno (T–S) fuzzy observer based fault tolerant control for DC–DC converters with robustness against uncertainties

AbstractThis paper proposes a Takagi–Sugeno fuzzy system model based fault tolerant control scheme for DC–DC converters, which is robust against parameter uncertainties and achieves the output voltage of an ideal converter. The control involves estimating the duty cycle change in the form of a fault parameter required to track the output voltage, in the presence of several uncertain conditions including converter losses, variation in input voltage, and unknown and changing output load. An adaptive law is designed to estimate the fault parameter that guarantees state and parameter error convergence. The adaptive law is derived using the Lyapunov stability theorem and the required parameters are evaluated by solving a linear matrix inequalities optimization problem. The load resistance is estimated in parallel by using a Kalman filter and fed to the fault parameter estimation scheme. Furthermore, a fast and robust method to detect short and open circuit switch faults is also presented. The proposed technique offers a simple, yet effective method to regulate the output voltage under several faulty and uncertain conditions. The proposed technique is tested on a DC–DC boost converter simulation model and the demonstrated MATLAB/Simulink results show the effectiveness of the proposed algorithm.

Data-based deep reinforcement learning and active FTC for unmanned surface vehicles

In this study, we investigate the active fault tolerant control(AFTC) of unmanned surface vehicles (USV) under actuator faults and environmental disturbances using deep reinforcement learning(DRL). We realize the perception of the environment and continuous control through end-to-end learning based on neural networks(NN). The contents of AFTC include 1) actuator fault estimation(FE) based on long short-term memory(LSTM) and 2) a fault tolerant control(FTC) framework based on a deep deterministic policy gradient to enable the USV to learn autonomous decision making through training. We introduce mixed noise based on Gaussian noise and Ornstein–Uhlenbeck noise into the training, which increases the exploration space and improves the generalization ability of the USV. An experiential replay method based on quantum computing is designed to distinguish the importance of samples through preparation and depreciation operations, enabling a guided learning process. Finally, we verify the universality and effectiveness of the AFTC framework by tracking straight and sinusoidal trajectories.

Open-fault diagnosis and tolerant control of a dual inverter fed open-end winding interior permanent magnet synchronous motor

Open-fault diagnosis and tolerant control of a dual inverter fed open-end winding interior permanent magnet synchronous motor

Integral reinforcement learning–based adaptive fuzzy fault tolerant control of hypersonic flight vehicle

The fault tolerant control (FTC) of hypersonic flight vehicle (HFV) with actuator fault is proposed in this paper. The fault model considered in this paper is a general model which HFV may encounter in practice. For designing the FTC, the nonlinear model of HFV is represented by T-S fuzzy models, and policy iteration (PI) strategy is utilized to solve the design problem of T-S controller for the built T-S model of HFV without actuator fault. Then, based on the normal T-S controller, an adaptive fuzzy FTC controller is proposed, in which the feedback gain matrices can improve themselves according to the special fault. The stability of the proposed adaptive fuzzy FTC is proved by Lyapunov theory, and an integral reinforcement learning (IRL)–based solving algorithm is proposed. Simulations on three different kinds of actuator faults are proposed, and the simulation results show that, under three different faults, the designed adaptive FTC can ensure the reliable flight of HFV.

Disturbance observer–based finite‐time fault tolerant control of quadrotor unmanned aerial vehicles with command filtered and event‐triggered techniques

AbstractThis article primarily focuses on the finite‐time fault‐tolerant tracking control problem of quadrotor unmanned aerial vehicle (UAV) systems. Our main innovation points are: (1) A simple cubic form of Lyapunov function is applied to the design of the position ring controller of the quadrotor UAV; (2) The command filtering technology effectively solves the challenge of derivation of complex coupling matrixs in the controller design process; (3) An improved disturbance observer and a variable threshold event‐triggered mechanism are applied in the Quadrotor UAV system. In summary, the overall approach combines the backstepping method and finite‐time Lyapunov stability to prove the finite‐time stability of all the signals in the system. Finally, the effectiveness and rationality of the algorithm are verified through simulation experiments and its application on an actual simulation platform.

A Solanum lycopersicum polyamine oxidase contributes to the control of plant growth, xylem differentiation, and drought stress tolerance.

Polyamines are involved in several plant physiological processes. In Arabidopsis thaliana, five FAD-dependent polyamine oxidases (AtPAO1 to AtPAO5) contribute to polyamine homeostasis. AtPAO5 catalyzes the back-conversion of thermospermine (T-Spm) to spermidine and plays a role in plant development, xylem differentiation, and abiotic stress tolerance. In the present study, to verify whether T-Spm metabolism can be exploited as a new route to improve stress tolerance in crops and to investigate the underlying mechanisms, tomato (Solanum lycopersicum) AtPAO5 homologs were identified (SlPAO2, SlPAO3, and SlPAO4) and CRISPR/Cas9-mediated loss-of-function slpao3 mutants were obtained. Morphological, molecular, and physiological analyses showed that slpao3 mutants display increased T-Spm levels and exhibit changes in growth parameters, number and size of xylem elements, and expression levels of auxin- and gibberellin-related genes compared to wild-type plants. The slpao3 mutants are also characterized by improved tolerance to drought stress, which can be attributed to a diminished xylem hydraulic conductivity that limits water loss, as well as to a reduced vulnerability to embolism. Altogether, this study evidences conservation, though with some significant variations, of the T-Spm-mediated regulatory mechanisms controlling plant growth and differentiation across different plant species and highlights the T-Spm role in improving stress tolerance while not constraining growth.

Sliding mode observer-based fault diagnosis and continuous control set fault tolerant control for PMSM with demagnetization fault

A fault detection, estimation and fault tolerant control scheme for demagnetization fault in the permanent magnet synchronous motor systems is proposed in this paper. When demagnetization fault occurs, the system will deviate from the normal state severely. To facilitate the calculation, the demagnetization fault is converted to the dq coordinate system for processing and the resistance change is modeled as the system uncertainty, and the effect of the uncertainty on the system is analyzed. Then a fault detection observer is designed to detect the fault occurrence time, and a sliding mode observer based fault estimation algorithm is designed to estimate the fault and disturbance information. The observer parameters are determined by linear matrix inequality. When the fault information is obtained, a continuous control set fault tolerant control scheme is presented to minimize the impact of fault as far as possible. Finally, experimental results provide evidence of the feasibility of the suggested algorithm.

Adaptive sliding mode and RBF neural network based fault tolerant attitude control for spacecraft with unknown uncertainties and disturbances

Taking the external disturbance, model uncertainty, actuator failure, and actuator saturation into consideration, this paper investigates the nonlinear fault-tolerant attitude control problem for the spacecraft. First, to deal with the disturbance and uncertainty with unknown boundaries, an adaptive sliding mode control method is proposed to stabilize the state variables of the spacecraft attitude control system. Then the actuator failure and saturation are further considered, and the second spacecraft fault-tolerant attitude controller is derived based on adaptive sliding mode control and radial basis function (RBF) neural networks. The adaptive control gains reduction technique is applied in the design process, which can weaken the chattering phenomenon of the controller to some extent, and the stability of the attitude control system is analyzed through Lyapunov theory. In the proposed controller, model information and external disturbance are not required and only the system states are needed. Furthermore, the boundaries of the model uncertainty, external disturbance, actuator fault and saturation are assumed to be existing but unknown by the proposed controllers. These features make the proposed attitude controllers need few modeling information of the spacecraft, or maintain strong robustness even if the model or external environment occurs significant changes. Finally, numerical simulations demonstrate the great performance of the proposed fault-tolerant attitude control method.

Integral terminal sliding mode fault tolerant control of quadcopter UAV systems

The article presents an active fault-tolerant control scheme with an integral terminal sliding mode controller for the UAV systems. This scheme effectively addresses saturation issues, disturbances, and sensor and actuator faults. Initially, the quadcopter UAV's model is represented in state space form. Subsequently, an augmented system incorporating auxiliary states from sensor faults is developed. An adaptive sliding mode observer is proposed for estimating the actuator and sensor faults. The integral terminal sliding mode fault-tolerant control, designed for altitude and attitude regulation, relies on fault estimation data. In contrast, a cascade proportional-integral-derivative (PID) controller is employed for position control. Simulation results demonstrate the superiority of the proposed method over existing control algorithms.

Multiple model fault diagnosis and fault tolerant control for the launch vehicle’s attitude control system

Abstract For the launch vehicle attitude control problem, traditional methods can seldom accurately identify the fault types, making the control method lack of pertinence, which largely affects the effect of attitude control. This paper proposes an active fault tolerant control strategy, which mainly includes fault diagnosis and fault tolerant control. In the fault diagnosis part, a small deviation attitude dynamics model of the launch vehicle is established, Kalman filters with different structures are designed to detect and isolate faults through residual changes, and the fault quantity of the actuator is further estimated. In the fault tolerant control part, the following control scheme is adopted according to the above diagnostic information: when the sensor fault is detected, the sensor measurement data is reconstructed; when the actuator fault is identified, the control allocation matrix is reconstructed. Simulation results show that the proposed method can effectively diagnose sensor fault and actuator faults, and significantly improve attitude tracking accuracy and control adjustment time.

Asymptotic voltage restoration in islanded microgrids via an adaptive asynchronous event-triggered finite-time fault-tolerant control

As the actuators of distributed generators involved in Microgrids (MGs) may experience different faults, it is highly recommended to design an appropriate secondary Fault Tolerant (FT) controller to provide resilience and robustness with respect to these malicious events. Meanwhile, the reduction of communication network workload from controller-to-actuator may be helpful to mitigate actuators stress. By virtue of the above, this article aims at introducing a novel distributed adaptive FT-Event-Triggered Control (FT-ETC) scheme for secondary voltage regulation control in AC islanded MG able to compensate faulty actuators effects while reducing the waste of communication network resources. The proposed control scheme is derived with the aid of the backstepping method and the ETC theory, whose combination ensures resilience with respect to possible faulty signals, while no knowledge of global information is required. Adaptive mechanisms are derived by exploiting Lyapunov theory, while Zeno-freeness property is proven by contradiction. Compared with the existing state-of-the-art on FT-ETC in islanded MG, here the main novelty relies in achieving the asymptotic rather than the practical stability of the voltage tracking errors despite an unhealthy environment, while the remaining adaptive signals involved in the closed-loop systems are bounded in finite-time. Finally, an extensive simulation analysis, also involving real-time Hardware In-the-Loop (HIL) experiments, confirms the theoretical derivation.

Concurrent Learning Robust Adaptive Fault Tolerant Boundary Regulation of Hyperbolic Distributed Parameter Systems.

This article develops a robust adaptive boundary output regulation approach for a class of complex anticollocated hyperbolic partial differential equations subjected to multiplicative unknown faults in both the boundary sensor and actuator. The regulator design is based on the internal model principle, which amounts to stabilize a coupled cascade system, which consists of a finite-dimensional internal model driven by a hyperbolic distributed parameter system (DPS). To this end, a systematic sliding mode equipped with a backstepping approach is developed such that the robust state feedback control can be realized. Moreover, since the available information is a faulty boundary measurement at the right side point, state estimation is required. However, due to the presence of boundary unknown faults, we need to solve an issue of joint fault-state estimation. Restrictive persistent excitation conditions are usually required to guarantee the exact estimation of faults but are unrealistic in practice. To this end, a novel concurrent learning (CL) adaptive observer is proposed so that exponential convergence is obtained. It is the first time that the spirit of CL is introduced to the field of DPSs. Consequently, the observer-based adaptive boundary fault tolerant control scheme is developed, and rigorous theoretical analysis is given such that the exponential output regulation can be achieved. Finally, the effectiveness of the proposed methodology is demonstrated via comparative simulations.

A Simple Online Fault Location and Tolerant Control Strategy for Power Electronic Transformers With a Single IGBT Open-Circuit Fault

A Simple Online Fault Location and Tolerant Control Strategy for Power Electronic Transformers With a Single IGBT Open-Circuit Fault

Fuzzy-Approximation Adaptive Fault Tolerant Control for Nonlinear Constraint Systems With Actuator and Sensor Faults

Fuzzy-Approximation Adaptive Fault Tolerant Control for Nonlinear Constraint Systems With Actuator and Sensor Faults

DFIG in Wind Energy Applications with High Order Sliding Mode Observer-based Fault-Tolerant Control Scheme using Sea Gull Optimization

This paper describes a new method for maximizing power extraction from a wind energy conversion system (WECS) by using a doubly fed induction generator (DFIG) that operates below nominal wind speed. To maximize the collected power of a wind turbine (WTG) exposed to actuator failure, a fault-tolerant high-order sliding mode observer (HOSMO) and Seagull Optimization Algorithm with a model predictive controller (MPC) technique is proposed. Evaluate both the real state and the sensor error simultaneously using a higher-order sliding-mode observer. Active fault tolerant controllers are designed to regulate wind turbine rotor speed and power in the presence of actuator defects and uncertainty. With the growing interest in employing wind turbines (WTGs) as the primary generators of electrical energy, fault tolerance has been seen as essential to improving efficiency and reliability. This research focuses on optimal fault-tolerant pitch control, which is used to modify the pitch angle of wind turbine blades in the event of sensor, actuator, and system failures. A Seagull Optimization Algorithm (SOA) is proposed to tune controller parameters to improve the performance of WT. The proposed method has achieved 92% of power tracking performance when compared to existing method.

Coping with salinity stress: segmental group 7 chromosome introgressions from halophytic Thinopyrum species greatly enhance tolerance of recipient durum wheat.

Increased soil salinization, tightly related to global warming and drought and exacerbated by intensified irrigation supply, implies highly detrimental effects on staple food crops such as wheat. The situation is particularly alarming for durum wheat (DW), better adapted to arid/semi-arid environments yet more sensitive to salt stress than bread wheat (BW). To enhance DW salinity tolerance, we resorted to chromosomally engineered materials with introgressions from allied halophytic Thinopyrum species. "Primary" recombinant lines (RLs), having portions of their 7AL arms distally replaced by 7el1L Th. ponticum segments, and "secondary" RLs, harboring Th. elongatum 7EL insertions "nested" into 7el1L segments, in addition to near-isogenic lines lacking any alien segment (CLs), cv. Om Rabia (OR) as salt tolerant control, and BW introgression lines with either most of 7el1 or the complete 7E chromosome substitution as additional CLs, were subjected to moderate (100 mM) and intense (200 mM) salt (NaCl) stress at early growth stages. The applied stress altered cell cycle progression, determining a general increase of cells in G1 and a reduction in S phase. Assessment of morpho-physiological and biochemical traits overall showed that the presence of Thinopyrum spp. segments was associated with considerably increased salinity tolerance versus its absence. For relative water content, Na+ accumulation and K+ retention in roots and leaves, oxidative stress indicators (malondialdehyde and hydrogen peroxide) and antioxidant enzyme activities, the observed differences between stressed and unstressed RLs versus CLs was of similar magnitude in "primary" and "secondary" types, suggesting that tolerance factors might reside in defined 7el1L shared portion(s). Nonetheless, the incremental contribution of 7EL segments emerged in various instances, greatly mitigating the effects of salt stress on root and leaf growth and on the quantity of photosynthetic pigments, boosting accumulation of compatible solutes and minimizing the decrease of a powerful antioxidant like ascorbate. The seemingly synergistic effect of 7el1L + 7EL segments/genes made "secondary" RLs able to often exceed cv. OR and equal or better perform than BW lines. Thus, transfer of a suite of genes from halophytic germplasm by use of fine chromosome engineering strategies may well be the way forward to enhance salinity tolerance of glycophytes, even the sensitive DW.

Influence of pharmacogenomic polymorphisms on allopurinol-induced cutaneous adverse drug reactions in Thai patients

BackgroundAllopurinol has been causing substantial morbidity and mortality particularly in Asian population by producing cutaneous adverse drug reactions (cADRs). Nonetheless, there are no data describing whether other genetics are a valid marker for prediction of allopurinol-induced cADRs patients in addition to HLA-B*58:01 allele. The goal of this study was to identify suitable single nucleotide polymorphisms (SNPs) for allopurinol induced cADRs among Thai patients. Methods: We conducted a case-control association study after enrolling 57 Thai patients with allopurinol induced cADRs and 101 allopurinol-tolerant controls. The genetic biomarkers and associated SNPs located on chromosome 6p21 were examined by TaqMan® SNP genotyping assays in both the cases and the controls.ResultsOut of fifteen SNPs in nine genes, we found four combined SNPs (rs3099844 of HCP5, rs9263726 of PSORS1C1, rs9263733 of POLR2LP, and rs9263745 of CCHCR1) were significantly associated with allopurinol-induced cADRs compared to the tolerant controls (OR 73.2; 95% CI 24.2–266.8; P = 1.9 × 10− 24). The overall sensitivity, specificity, positive predictive value and negative predictive value of these combinations were 84%, 94%, 9%, and 100%, respectively. However, the variant alleles of these SNP combinations were detected in 89.5% (51/57) of the cases. Moreover, the HLA-B*58:01 allele was observed in 86.0% of patients with allopurinol-induced cADRs, but only in 4.0% of tolerant controls (OR: 137.2; 95% CI: 38.3–670.5 and p-value = 1.7 × 10− 27).ConclusionsThus, this research confirms the association between the specific HLA-B*58:01 allele and all phenotypes of allopurinol-induced cADRs in Thais. Furthermore, there was found the combined four SNPs (rs3099844, rs9263726, rs9263733, and rs9263745) could be used as alternative novel biomarkers for predicting cADRs in patients taking allopurinol.