Tolerant Control Research Articles

Sliding mode control‐based distributed fault tolerant tracking control for multiple unmanned aerial vehicles with input constraints and actuator faults

AbstractIn this article, the distributed tracking control problem is studied for the formation flight systems of unmanned aerial vehicles (UAVs) in presence of input constraints and actuator faults. Different from the traditional approximation technique, such as radial basis function neural networks and fuzzy logic systems, the novel broad learning system approximation technique is introduced in this study to identify the unknown lumped disturbances including external disturbances, input constraints and additive actuator faults. Combining dynamic surface control technique with the fractional order sliding mode control, a distributed fault tolerant tracking control strategy is developed for the formation flight systems of UAVs. Besides, the adverse effect of multiplicative actuator faults is compensated by the Nussbaum function, such that the satisfactory cooperative tracking control performance of the formation flight systems is obtained. Finally, a simulation experiment is given to demonstrate the superiority of the proposed control scheme compared with other existing results.

Realistic Optimal Tolerant Solution of the Quadratic Interval Equation and Determining the Optimal Control Decision on the Example of Plant Fertilization

In scientific journals, it is increasingly common to find articles presenting methods for solving problems not based on idealistic mathematical models containing perfectly accurate coefficient values that cannot be obtained in practice, but on models in which coefficient values are affected by uncertainty and are expressed in the form of intervals, fuzzy numbers, etc. However, solving tasks with interval coefficients is not fully mastered, and a number of such problems cannot be solved by currently known methods. There is undeniably a research gap here. The article presents a method for solving problems governed by the quadratic interval equation and shows how to find the tolerant optimal control value of such a system. This makes it possible to solve problems that could not be solved before. The paper introduces a new concept of the degree of robustness of the control to the set of all possible multidimensional states of the system resulting from its uncertainties. The method presented in the article was applied to an example of determining the optimal value of nitrogen fertilization of a sugar beet plantation, the vegetation of which is under uncertainty. It would be unrealistic to assume precise knowledge of crop characteristics here. The proposed method allows to determine the value of fertilization, which gives a chance to obtain the desired yield for the maximum number of field conditions that can occur during the growing season.

LTT and HLA testing as diagnostic tools in Spanish vancomycin-induced DRESS cases: A case-control study.

Drug reaction with eosinophilia and systemic symptoms (DRESS) is a severe T-cell-mediated off-target adverse reaction. DRESS cases caused by vancomycin have often been reported. The HLA-A*32:01 allele has been associated with genetic susceptibility to vancomycin-induced DRESS in US citizens of European descent. We have analyzed the association of the HLA-A*32:01 allele in 14 Spanish DRESS cases in which vancomycin was suspected as the culprit drug, and the lymphocyte transformation test (LTT) as an in vitro assay to evaluate vancomycin sensitization. The results were compared to vancomycin-tolerant control donors. LTT was performed in 12 DRESS cases with PBMCs from resolution samples available and in a group of 12 tolerant donors. ROC curves determined that LTT is a suitable tool to identify patients sensitized to vancomycin (AUC = 0.9646; p < 0.0001). When a stimulation index >3 was regarded as a positive result, contingency tables determined 91% sensitivity, 91.67% specificity, 91% positive predictive value, and 91.67% negative predictive value (p = 0.0001, Fisher's exact test). The HLA A*32:01 allele was determined by an allele-specific PCR assay in 14 cases and 25 tolerant controls. Among the DRESS cases, five carriers were identified (35.7%), while it was detected in only one (4%) of the tolerant donors, [odds ratio (OR) = 13.33; 95% CI: 1.364-130.3; p = 0.016]. The strength of the association increased when only cases with positive LTT to vancomycin were considered (OR = 24.0; 95% CI: 2.28-252.6; p = 4.0 × 10-3). Our results confirm the association of the risk allele HLA-A*32:01 with vancomycin-induced DRESS in Spanish cases, and support LTT as a reliable tool to determine vancomycin sensitization.

A QTL approach in faba bean highlights the conservation of genetic control of frost tolerance among legume species.

Frost is a major abiotic stress of winter type faba beans (Vica faba L.) and has adverse effects on crop yield. Climate change, far from reducing the incidence of frost events, is making these phenomena more and more common, severe, and prolonged. Despite the important interaction that the environment has in the tolerance of faba bean to frost, this trait seems to have good levels of heritability. Several QTLs for frost tolerance have already been reported, however, a more robust identification is needed to more precisely identify the genomic regions involved in faba bean tolerance to sub-zero temperatures. Several pea (Pisum sativum L.) and barrel medic (Medicago truncatula L.) frost tolerance QTLs appear to be conserved between these two species, furthering the hypothesis that the genetic control of frost tolerance in legume species might be more generally conserved. In this work, the QTL mapping in two faba bean recombinant inbred line (RIL) populations connected by a common winter-type parent has led to the identification of five genomic regions involved in the control of frost tolerance on linkage groups I, III, IV, and V. Among them, a major and robust QTL of great interest for marker-assisted selection was identified on the lower part of the long-arm of LGI. The synteny between the faba bean frost tolerance QTLs and those previously identified in other legume species such as barrel medic, pea or soybean highlighted at least partial conservation of the genetic control of frost tolerance among different faba bean genetic pools and legume species. Four novel RILs showing high and stable levels of tolerance and the ability to recover from freezing temperatures by accumulating frost tolerance QTLs are now available for breeding programs.

Associations of HLA and drug-metabolizing enzyme genes in co-trimoxazole-induced severe cutaneous adverse reactions

Co-trimoxazole is mainly used as a first-line drug for treatment and prophylaxis against Pneumocystis jiroveci pneumonia. This drug, however, has been reported as the most common causative drug for severe cutaneous adverse reactions (SCARs). This study aimed to extensively elucidate the associations between genetic polymorphisms of HLA class I and genes involved in bioactivation and detoxification of co-trimoxazole on co-trimoxazole-induced SCARS in a large sample size and well-defined Thai SCARs patients. A total of 67 patients with co-trimoxazole-induced SCARs, consisting of 51 SJS/TEN patients and 16 DRESS patients, and 91 co-trimoxazole tolerant controls were enrolled in the study. The results clearly demonstrated that the HLA-B∗13:01 allele was significantly associated with co-trimoxazole-induced SCARs, especially with DRESS (OR = 8.44, 95% CI = 2.66–26.77, P = 2.94 × 10−4, Pc = 0.0126). Moreover, the HLA-C∗08:01 allele was significantly associated with co-trimoxazole-induced SJS/TEN in the HIV/AIDS patients with an OR of 8.51 (95% CI = 2.18–33.14, P = 8.60 × 10−4, Pc = 0.0241). None of the genes involved in the bioactivation and detoxification of co-trimoxazole investigated in this study play any major role in the development of all phenotypes of SCARs.

Fault Detection and Fault Tolerant Control for Anti-lock Braking Systems )ABS) Speed Sensors by Using Neural Networks

This paper proposed neural networks to continuously provide alternative constructed signals for vehicle and wheel speed sensors utilized for the Anti-Lock Braking System (ABS), which serves as the fault tolerant control method. These alternative constructed signals are used for two purposes. The first is to generate residual signals, and the second is to be adopted instead of isolated faulty signals. The residual signal is generated by extracting the difference between the alternative constructed signals and the corresponding actual signals. These residual signals serve as an indication of fault occurrence and to express that fault severity. Whenever a fault occurrence is detected and diagnosed in one of the sensor’s signals, the faulty signal is isolated and replaced by the corresponding constructed signal to maintain the system's normal behavior under a faulty condition. The range of data covered under the proposed estimating neural networks is huge, continuous in time, and not sampled. In this work, the range of the data lies between [50 to 120 km/h] when the braking is started. That cannot be performed by any available method. These models' training process is based on the Levenberg-Marquardt (LM) algorithm, implemented and tested by MATLAB/Simulink. The results show that these models can accurately map the measured data into the desired output through the best-fit functions. The fast response of the trained models makes them suitable for real-time alternative signals for fault-tolerant purposes for speed sensors during hard or panic braking.

Fault estimation and fault tolerant control for interval type-2 Takagi–Sugeno fuzzy systems via membership-function-dependent approach

This paper investigates the fault estimation (FE)-based fault tolerant control (FTC) technique to achieve the desired control performance for the nonlinear systems suffering from uncertainties, external disturbance and actuator faults using the interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy model. In this work, an IT2 fuzzy observer is built to simultaneously estimate both the system states and actuator faults, upon which a fault tolerant controller is proposed to guarantee the asymptotical stability of the closed-loop system with a prescribed H_{infty } performance level. Considering the bidirectional robustness interactions between the observer and FTC system, an integrated design technique is developed to address observer and FTC units together in one step to realize the required robustness within the whole closed-loop FTC system. By utilizing Lyapunov stability theory combined with the matrix inequality convexification techniques, a membership-function-dependent (MFD) FTC strategy is proposed where the information of membership functions is taken into account in the analysis for relaxation of the stability conditions. Additionally, to offer greater design flexibility and lower implementation cost to the fault tolerant controller, the imperfect premise matching (IPM) scheme is adopted, such that the premise membership functions of the fault tolerant controller can be chosen differently from those of IT2 fuzzy model. Finally, simulation results are provided to validate the effectiveness of the proposed FTC strategy.

Predictive and Prognostic Value of Plasma Zonulin for Gestational Diabetes Mellitus in Women at 24-28 Weeks of Gestation.

We aimed to examine the predictive and prognostic value of plasma zonulin for gestational diabetes mellitus (GDM) in women at 24-28 weeks of gestation. This retrospective study was carried out with pregnant women with GDM (n=98) and normal glucose tolerance (control group) (n=132). GDM was diagnosed according to American Diabetes Association (ADA) criteria with a one-step 75-g OGTT at 24-28 gestational weeks. Their serum zonulin levels measured during one-step 75-g OGTT and perinatal outcomes were compared, and the cut-off value of plasma zonulin for the prediction of GDM was calculated with receiver operating characteristic curve analysis. Plasma zonulin level was significantly higher in women with GDM compared to controls (28.8±24.9 and 7.3±11.3 ng/mL, respectively). According to logistic regression analysis, plasma zonulin levels and GDM were statistically significant. The plasma zonulin cut-off value was>45.2 ng/mL. The rate of cesarean section, the rate of meconium in the amniotic fluid, and the need for admission to the neonatal intensive care unit significantly differed between women with GDM and controls. In pregnant women with GDM, plasma zonulin increases, and with the cut-off level of>45.2 ng/mL, it can predict GDM with values of sensitivity and specificity levels significantly higher in pregnant women with GDM, suggesting that it can be used as a tool for its screening and early diagnosis.

Experimental Validation of an Active Fault Tolerant Control Strategy Applied to a Proton Exchange Membrane Fuel Cell

Reliability of proton exchange membrane fuel cells (PEMFCs) is a major issue for large industrialization and commercialization. Indeed, performance can be degraded due to abnormal operating conditions, namely, faults, which lead either to a transient decay of the fuel cell performance or to permanent damage that cannot be recovered. The literature shows that long-time exposure to faults leads to fuel cell degradation. Therefore, it is necessary to use tools that can not only diagnose these faulty conditions, but also modify the fuel cell operations to recover a healthy operating point. For that purpose, one approach is the Active Fault Tolerant Control (AFTC) strategy which is composed of three functions. First, a diagnosis part allows fault detection and identification. Then a decision part, which is an algorithm aiming at finding a new operating point that mitigates the occurring fault. Finally, a control part applies the mitigation strategy established by the decision algorithm. The present work focuses on the decision part. and aims to bring a new contribution to PEMFCs reliability improvement and address water management issues, namely, the cell flooding and membrane drying out with the developed AFTC tool. The strategy is tested and validated on a single PEMFC cell and results are presented, analyzed, and discussed.

The outcome of a multidisciplinary approach incorporating neoadjuvant chemoradiotherapy with S1 for resectable pancreatic ductal adenocarcinoma.

This study was performed to evaluate the efficacy of a multidisciplinary approach incorporating neoadjuvant chemoradiotherapy with S1 (S1-NACRT) for resectable pancreatic ductal adenocarcinoma. The medical records of 132 patients who received S1-NACRT for resectable pancreatic ductal adenocarcinoma from 2010 to 2019 were reviewed. The S1-NACRT regimen consisted of S1 at a dose of 80-120 mg/body/day together with 1.8Gy of radiation in 28 fractions. The patients were re-evaluated 4 weeks after S1-NACRT completion, and a pancreatectomy was then considered. Adverse events of S1-NACRT ≥grade 3 occurred in 22.7% of the patients, and 1.5% discontinued therapy. Of the 112 patients who underwent a pancreatectomy, 109 underwent R0 resection. Adjuvant chemotherapy with relative dose intensity ≥50% was administered to 74.1% of the patients who underwent resection. The median overall survival of all patients was 47 months, and the median overall survival and recurrence-free survival of patients who underwent resection was 71 and 32 months, respectively. According to the multivariate analyses of prognostic factors for overall survival in patients who underwent resection, negative margin status (hazard ratio: 0.182; P=0.006) and relative dose intensity of adjuvant chemotherapy ≥50% (hazard ratio 0.294; P < 0.001) were independent prognostic factors of overall survival. A multidisciplinary approach incorporating S1-NACRT for resectable pancreatic ductal adenocarcinoma demonstrated acceptable tolerability and good local control and resulted in comparable survival benefits.

Impact angle constrained fuzzy adaptive fault tolerant IGC method for Ski-to-Turn missiles with unsteady aerodynamics and multiple disturbances

An impact angle constrained fuzzy adaptive fault tolerant integrated guidance and control method for Ski-to-Turn (STT) missiles subject to unsteady aerodynamics and multiple disturbances is proposed. Unsteady aerodynamics appears when flight vehicles are in a transonic state or confronted with unstable airflow. Meanwhile, actuator failures and multisource model uncertainties are introduced. However, the boundaries of these multisource uncertainties are assumed unknown. The target is assumed to execute high maneuver movement which is unknown to the missile. Furthermore, impact angle constraint puts forward higher requirements for the interception accuracy of the integrated guidance and control (IGC) method. The impact angle constraint and the precise interception are established as the object of the IGC method. Then, the boundaries of the lumped disturbances are estimated, and several fuzzy logic systems are introduced to compensate the unknown nonlinearities and uncertainties. Next, a series of adaptive laws are developed so that the undesirable effects arising from unsteady aerodynamics, actuator failures and unknown uncertainties could be suppressed. Consequently, an impact angle constrained fuzzy adaptive fault tolerant IGC method with three loops is constructed and a perfect hit-to-kill interception with specified impact angle can be implemented. Eventually, the numerical simulations are conducted to verify the effectiveness and superiority of the proposed method.

Robust Non-Fragile Fault Tolerant Control for Ensuring the Safety of the Intended Functionality of Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) has the potential to significantly improve road safety, highway throughput and reduce fuel consumption. However, the safety of the intended functionality (SOTIF) of CACC that focuses on unreasonable risks related to performance limitations has not been addressed. Moreover, various unknown uncertainties, disturbances, and controller perturbations present in the road environment make the guarantee of SOTIF for CACC a more challenging problem. This study presents a robust non-fragile fault tolerant control (RNFTC) strategy as a quantitative risk reduction method for ensuring SOTIF of CACC with system uncertainty, multisource disturbances, and controller perturbations. First, an intermediate based robust estimation method is proposed to estimate the performance limitations of perception and actuation, system states, and matched disturbances, simultaneously. Second, a robust non-fragile <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{H}_{\infty }$ </tex-math></inline-formula> FTC method is proposed to accommodate the simultaneous presence of performance limitations and disturbances. Third, theorems for solving optimal estimator and controller gains of the proposed RNFTC are derived in terms of linear matrix inequalities (LMIs). The requirements for CACC system stability, robustness, non-fragile and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{H}_{\infty }$ </tex-math></inline-formula> performances under the proposed RNFTC are analyzed using Lyapunov theory. Finally, a series of comparative simulations with the CACC system are conducted to demonstrate the effectiveness and superiority of the proposed RNFTC method on ensuring SOTIF of CACC under unknown uncertainties, disturbances, and perturbations.

Study on tolerance control of flying-wing layout vectored thrust UAV

The flying-wing layout vectored thrust UAV often uses multiple sets of aerodynamic rudder surfaces and vector nozzles to jointly generate the required control force and torque, which belongs to a typical overdrive system. Multiple sets of rudder surfaces give UAV a higher redundancy configuration, but also result in multiplying the rudder surface failure rate. Especially for the statically unstable flying-wing UAV in lateral direction, the moment imbalance caused by the failure of the executive rudder will seriously affect the flight safety. Therefore, this paper takes the failure of elevator and rudder damage as an example, and proposes a kind of control distribution method of aerodynamic-based control and vectored thrust as auxiliary. The binary vector deflection mechanism is used to generate vector thrust, compensate damaged actuator mechanism rudder effect, release the control margin of the rudder actuator, and restore the maneuverability of the aircraft. Under the failure of the aerodynamic rudder actuator damage, the stable control UAV is realized.

Relationship Between NT-proBNP Levels and Left Ventricular Ejection Fraction in Patients with Unstable Angina and Diabetes Mellitus and Preserved LVEF.

N-terminal pro-B-type natriuretic peptide (NT-proBNP) is suggested to be altered in patients with systolic heart failure or acute coronary syndrome. We explored the relationship between left ventricular ejection fraction (LVEF) and levels of NT-proBNP in patients with unstable angina and type 2 diabetes mellitus and preserved LVEF.Patients with unstable angina were divided into normal glucose tolerance (controls) and type 2 diabetes mellitus groups. The plasma NT-proBNP concentration was measured in these patients within 30 minute of admission for a comparative study. The severity of coronary arterial lesions was evaluated using Syntax scores. Results: NT-proBNP levels were not significantly different in patients with unstable angina and type 2 diabetes mellitus (median [quartiles]: 167.0 [66.1, 623.3] pg/mL) from those of controls (116.0 [69.8, 233.0], P = 0.278). Subsequent analyses indicated that ln (NT-proBNP) was positively associated with the following parameters: left ventricular end-diastolic diameter (r = 0.495, P = 0.019), left ventricular end-systolic diameter (r = 0.648, P = 0.001), and Syntax score (r = 0.567, P = 0.006); ln (NT-proBNP) was negatively associated with LVEF (r = -0.652, P = 0.001) in patients with unstable angina and type 2 diabetes mellitus. In multiple linear regression analysis, ln (NT-proBNP) levels were significantly independently correlated with the LVEF and Syntax score. However, no correlation was observed between ln (NT-proBNP) and each parameter in patients with unstable angina and normal glucose tolerance (controls).The NT-proBNP level is independently correlated with the LVEF in patients with unstable angina and type 2 diabetes mellitus and preserved LVEF.

Down-Regulation of PLAC1 in the Placenta of Gestational Diabetes Mellitus Patients and its Clinical Significance

Background: Placenta-specific 1 (PLAC1) is specifically expressed in the placenta and plays a fundamental role in placenta function. Aberrant expression of PLAC1 has been reported in pregnancy-related disorders; however, its expression in gestational diabetes mellitus (GDM) has not been clearly elucidated. This study aimed to investigate the expression of PLAC1 in the placenta of GDM patients, and its relationship with clinical characteristics. Methods: This was a case-control study. Placental tissues were collected from 37 GDM patients (GDM group) and 38 pregnant women with normal glucose tolerance (control group), matched with respect to maternal age and gestational weeks. We examined the expression of PLAC1 in the placenta of both groups and determined its association with clinical indicators. The localization of PLAC1 was confirmed by immunohistochemistry analyses. Results: PLAC1 expression was significantly lower in the placenta of GDM patients. For the control group, PLAC1 was positively correlated with pre-pregnancy body mass index (BMI), BMI at delivery, the fasting insulin, triglyceride levels, and homeostasis model assessment during delivery. In the case of GDM patients, there was no correlation between PLAC1 and these indices. Additionally, PLAC1 protein was mainly expressed in the cytoplasm of syncytiotrophoblasts and chorionic stromal cells. Conclusions: The expression of PLAC1 was reduced in the GDM placenta, which provides insight into the pathophysiological changes occurring in the placenta of these patients.

Fault Diagnosis and Fault Tolerant Control of Wind Turbines: An Overview

Wind turbines are playing an increasingly important role in renewable power generation. Their complex and large-scale structure, however, and operation in remote locations with harsh environmental conditions and highly variable stochastic loads make fault occurrence inevitable. Early detection and location of faults are vital for maintaining a high degree of availability and reducing maintenance costs. Hence, the deployment of algorithms capable of continuously monitoring and diagnosing potential faults and mitigating their effects before they evolve into failures is crucial. Fault diagnosis and fault tolerant control designs have been the subject of intensive research in the past decades. Significant progress has been made and several methods and control algorithms have been proposed in the literature. This paper provides an overview of the most recent fault diagnosis and fault tolerant control techniques for wind turbines. Following a brief discussion of the typical faults, the most commonly used model-based, data-driven and signal-based approaches are discussed. Passive and active fault tolerant control approaches are also highlighted and relevant publications are discussed. Future development tendencies in fault diagnosis and fault tolerant control of wind turbines are also briefly stated. The paper is written in a tutorial manner to provide a comprehensive overview of this research topic.

Fuzzy model based fault estimation and fault tolerant control for flexible spacecraft with unmeasurable vibration modes

This paper investigates the problem of anti-disturbance fault estimation and attitude tracking fault tolerant control for a flexible spacecraft subject to actuator faults, external disturbances, input saturation, and configuration misalignment. Different form the traditional methods, both the nonlinear dynamics subsystem and attitude control system are reconstructed into Takagi–Sugeno fuzzy models, where partial nonlinear term is remained to assist the design of fuzzy controller. A fuzzy fault estimation observer with proportional–integral adaptive laws is first designed. Without measuring any dynamic information of flexible appendages, estimated values of unknown actuator faults and vibration disturbances of flexible appendages can be obtained simultaneously. This is the most important advantage of the proposed fault estimation scheme over the previous methods. Then, a fuzzy sliding mode fault tolerant control scheme, based on fewer fuzzy rules and less computational burden, is developed under the framework of feedback linearisation and feedforward compensation. The actuator faults and vibration disturbances are counteracted in real time. Regional pole placement and virtual controller with input saturation are adopted to tune the control input and avoid the radical control torque scheduling. Finally, numerical simulations are given to illustrate the validity of the proposed fault estimation and fault tolerant control strategies.

Risk reduction for safety of the intended functionality of CACC with complex uncertainties: A cooperative robust non-fragile fault tolerant strategy

Safety of the intended functionality (SOTIF) of connected and autonomous vehicles (CAVs) is very challenging due to heterogeneous performance limitations and complex uncertainties in real road environments. In this paper, a cooperative robust non-fragile fault tolerant control (CRNFTC) strategy is presented to reduce the risks caused by multi-vehicle performance limitations of perception and actuation systems for ensuring SOTIF of cooperative adaptive cruise control (CACC). First, an intermediate based cooperative robust estimation method is proposed, by combining ego and cooperative information, system states, matched disturbances, performance limitations of perception and actuation of the vehicles in the platoon are simultaneously estimated. Existence conditions of estimators are given with respect to predecessor following (PF) and bi-directional (BD) communication network topologies. Then, based on the estimation, a distributed robust non-fragile fault tolerant H∞ control method is proposed, such that compensation of the effects of heterogeneous performance limitations and matched disturbances, and suppression of the remaining unmatched disturbances can be achieved. The sufficient condition and optimal solution of the proposed CRNFTC are obtained by using Lyapunov theory with explicit consideration of the system uncertainty and controller perturbation. The efficacy and superiority of the proposed CRNFTC for ensuring SOTIF of the CACC of PF and BD communication network topologies with complex uncertainties are substantiated via a series of simulations and quantitative comparisons.

Finite time fault tolerant tracking control for multiple unmanned aerial vehicles with actuator faults

SummaryAn adaptive fast nonsingular integral terminal sliding mode control scheme is proposed for the distributed formation control problem of multiple unmanned aerial vehicles (UAVs) affected by actuator faults and external disturbances. In order to achieve a good cooperative tracking performance of UAVs during mission execution, the adverse effect of the lumped disturbances composed of actuator failures, wind and vortex disturbances is estimated by the cerebellar model articulation neural network, meanwhile the tangent function is introduced to eliminate the chattering of the sliding mode. Then the analysis of superior convergence performance of the fast nonsingular integral terminal sliding manifold is implemented, and the finite time stability of the closed‐loop formation flight control system is proved. Finally, the simulation experiments verify that the proposed approach is superior to the nonsingular integral terminal sliding mode control for the formation control system of faulty multiple UAVs.

Iterative Learning Control for Actuator Fault Uncertain Systems

An iterative learning fault-tolerant control method is designed for an actuator fault intermittent process with simultaneous uncertainties for the system parameters. First, an intermittent fault tolerance controller is designed using 2D system theory, and the iterative learning control (ILC) intermittent process is transformed into a 2D Roesser model. Secondly, sufficient conditions for the controller’s existence are analyzed using the linear matrix inequality (LMI) technique, and the control gain matrices are obtained by convex optimization with LMI constraints. Under these conditions for all additive uncertainties for the system parameters and admissible failures, the controller can ensure closed-loop fault-tolerant performance in both the time and batch directions, and it can also meet the H∞ robust performance level against outside disturbances. Eventually, the algorithm’s computational complexity is analyzed, and the effectiveness of the algorithm is verified by simulation with respect to an injection molding machine model. Compared with traditional ILC laws, which do not consider actuator faults, the proposed algorithm has a better convergence speed and stability when the time-invariant and time-variant actuator faults occur during implementation.