Search

This study aimed to examine the structural alterations of the deep gray matter (DGM) in the basal ganglia circuitry of Parkinson's disease (PD) patients with freezing of gait (FOG) using quantitative susceptibility mapping (QSM) and neuromelanin-sensitive magnetic resonance imaging (NM-MRI). Twenty-five (25) PD patients with FOG (PD-FOG), 22 PD patients without FOG (PD-nFOG), and 30 age- and sex-matched healthy controls (HCs) underwent 3-dimensional multi-echo gradient recalled echo and NM-MRI scanning. The mean volume and susceptibility of the DGM on QSM data and the relative contrast (NM RC-SNpc) and volume (NM volume-SNpc) of the substantia nigra pars compacta on NM-MRI were analyzed among groups. A multiple linear regression analysis was performed to explore the associations of FOG severity with MRI measurements and disease stage. The PD-FOG group showed higher susceptibility in the bilateral caudal substantia nigra (SN) compared to the HC group. Both the PD-FOG and PD-nFOG groups showed lower volumes than the HC group in the bilateral caudate and putamen as determined from the QSM data. The NM volume-SNpc on NM-MRI in the PD-FOG group was significantly lower than in the HC and PD-nFOG groups. Both the PD-FOG and PD-nFOG groups showed significantly decreased NM RC-SNpc. The PD-FOG patients showed abnormal neostriatum atrophy, increases in iron deposition in the SN, and lower NM volume-SNpc. The structural alterations of the DGM in the basal ganglia circuits could lead to the abnormal output of the basal ganglia circuit to trigger the FOG in PD patients. [ABSTRACT FROM AUTHOR]

Various therapies are used in patients with internet gaming disorder (IGD), but their comparative effectiveness in reducing IGD symptoms is unknown. The present systematic review and meta-analysis evaluated the effectiveness of pharmacotherapy, psychotherapy and pharmacological-psychological combined therapy on IGD related-outcomes and its comorbid mental disorders. Following PRISMA guidelines, a search of MEDLINE, EMBASE, Ovid Emcare, PsycINFO and the Cochrane Clinical Trials Library was conducted by Aug 04, 2023. We pooled effect sizes as within-group Hedges's g and performed meta-regression using random effects models. Systematic review identified 43 studies and 32 of them with 1738 participants were included for meta-analysis. Pharmaco-, psycho- and combined therapies showed large-to-moderate effect sizes for IGD symptoms and comorbid mental disorders. Combined therapies (Hedges's g = −2.11, 95% confidence interval: −2.87 to −1.35) showed larger effect size than pharmacotherapies (Hedges's g = −1.10, −1.31 to −0.89) or psychotherapies (Hedges's g = −0.99, −1.22, −0.76) on IGD reduction at post-intervention. The effects maintained at follow-up in psycho- and combined therapies. Bupropion and cognitive behavioral therapy showed advantages over their counterparts. The three types of therapies are promising to reduce IGD symptoms and comorbidities, but cautious interpretation is required given the limitations and high heterogeneity in the existing interventions. • Pharmaco-, psycho- and combined therapies were promising to reduce IGD symptoms and comorbid mental disorders. • Combined therapy was more effective than pharmacotherapies or psychotherapies alone on IGD reduction at post-intervention. • The effects on IGD reduction maintained at follow-up in psycho- and combined therapies. • Bupropion and cognitive behavioral therapy showed advantages over their counterparts. • Cautious interpretation is required given the limitations and high heterogeneity in the existing interventions. [ABSTRACT FROM AUTHOR]

Given the importance of reliability and availability in wind farms, this paper focuses on the development of fault diagnosis and fault-tolerant control schemes in a cooperative framework (referred to as active fault-tolerant cooperative control) at the wind farm level against the decreasing power generation caused by turbine blade erosion and debris build-up on the blades over time. In more details, the paper presents a novel integrated fault detection and diagnosis and fault-tolerant control approach oriented to the design and development of two active fault-tolerant cooperative control schemes for an offshore wind farm. Each of the schemes employs a fault detection and diagnosis system to provide accurate and timely diagnosis information to be used in an appropriate automatic signal correction algorithm for accommodation of faults in the wind farm. The effectiveness and performance of the proposed schemes are evaluated and compared using different simulations on a high-fidelity offshore wind farm benchmark model in the presence of wind turbulences, measurement noises and realistic fault scenarios. [ABSTRACT FROM AUTHOR]

Experimental study on the ballistic behavior of mosaic Silicon Carbide (SiC) ceramics bonding with Ultra-High Molecular Weight Polyethylene (UHMWPE) plate is presented against 7.62 mm×51 mm Armor Piercing (AP) projectile. The effect of SiC ceramics on the ballistic performance of mosaic SiC/UHMWPE composite armors is systematically investigated, and the bulletproof process of the composite armor combining the hard/brittle SiC and soft/flexible UHMWPE is clarified in detail. The test results show that the ballistic performance of composite armors is significant influenced by the geometry of mosaic SiC ceramics and the impact zone of front layer, different impact zones are defined for the cylindrical mosaic SiC/UHMWPE composite armor. The residual velocities of AP projectile are varied from 648 m/s to 0 m/s for the cylindrical, hexagonal and square mosaic SiC ceramics, when the launch speeds of bullets are 780 m/s with a standard deviation of 10 m/s. The bulge lengths of UHMWPE plate are also changed from 16.5 mm to 43.2 mm for different structures of mosaic SiC ceramic front layer. The bulletproof property can be significantly enhanced by prolonging the interaction time between bullet and target. The conclusions of this paper are practically useful for designing the hard/flexible composite armor systems. [ABSTRACT FROM AUTHOR]

This paper studies a robust fault tolerant control of a class of nonlinear switched systems with strong structural uncertainties and actuator faults. This paper presents a new robust fault tolerant state feedback method, by using the average dwell time technique to stabilize the switched nonlinear systems exponentially under an arbitrary switching law. Comparing with the existing results, the method of this paper has three features: (1) this method is applicable to the switched nonlinear systems with strong structural uncertainties and faulty actuators and also the nominal case of the considered systems, there is no need to change any structures and/or parameters of the controller. (2) The switching law is arbitrary provided that the average switching is slow enough in the average sense. (3) This method treats all actuators in the same way, no need to separate faulty actuators from the healthy ones. The simulation result verifies the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Motion planning methodologies for parallel parking have been well developed in the last decade. In contrast to the prevailing and emerging parking motion planners, this work provides a precise and objective description of the parking scenario and vehicle kinematics/dynamics. This is achieved by formulating a unified optimal control problem that is free of subjective knowledge (e.g., human experiences). The concerned optimal control problem, when parameterized into a large-scale nonlinear programming (NLP) problem, is extremely difficult to solve. This bottleneck has hindered many research efforts previously. Although the feasible regions of NLP problems are clearly defined, the majority of NLP-solving processes still require high-quality initial guesses, which accelerate the convergence process. In this work, we propose a spatio-temporal decomposition based initialization strategy to generate reliable initial guesses, so as to facilitate the NLP-solving process. In contrast to the typical facilitation strategies in robotic motion/path planning, our spatio-temporal decomposition strategy considers only objective kowledge, further breaking the limitation of subjective knowledge and making full use of a vehicle's maneuver potential. A series of comparative simulations verifies that the proposed initialization strategy is advantageous over its prevailing competitors, and that the proposed motion planner is promising for on-line planning missions. Theoretical analysis that supports our initialization strategy is given as well. [ABSTRACT FROM AUTHOR]

This paper aims to address the dual-input problem for civil aircraft equipped with side-sticks. A concept of full-altitude attitude angles envelope is firstly proposed; at low altitude this envelope protects the aircraft from striking ground, while at high altitude it restricts attitude angles within a threshold to guarantee passenger-ride qualities. Model Predictive Control (MPC) strategy is utilized in this paper; at each operation point, given linearized dynamics of the aircraft, cost function and inequalities constraints for MPC are specified, associated control laws are generated. Flight simulation investigates the performance of MPC protection laws; two flight records at high altitude and a record simulating the take-off and landing process are presented. Based on the test records, the proposed MPC-based protection framework is considered to be applicable. [ABSTRACT FROM AUTHOR]

With growing worldwide interest in commercial, scientific, and military issues associated with both oceans and shallow waters, there has been a corresponding growth in demand for the development of unmanned surface vehicles (USVs) with advanced guidance, navigation and control (GNC) capabilities. This paper presents a comprehensive literature review of recent progress in USVs development. The paper first provides an overview of both historical and recent USVs development, along with some fundamental definitions. Next, existing USVs GNC approaches are outlined and classified according to various criteria, such as their applications, methodologies, and challenges. Finally, more general challenges and future directions of USVs towards more practical GNC capabilities are highlighted. [ABSTRACT FROM AUTHOR]

Among renewable energy sources, wind power is expected to contribute a larger and rapidly growing portion of the world's energy portfolio. However, the increased penetration of wind power into the power grid has challenged the reliable and stable operation of the grid. This motivates new opportunities in the design and development of novel control schemes capable of actively maintaining the necessary balance between power generation and load, which in turn regulates the grid frequency when plenty of winds are available. This paper presents two active power control schemes that are developed based on adaptive pole placement control and fuzzy gain-scheduled proportional-integral control approaches. The active power control is conducted collectively across a wind farm to provide rapid power response while maintaining safe structural loading on turbines’ components. The proposed active power control schemes are evaluated and compared by a series of simulations on an advanced wind farm benchmark model in the presence of wind turbulences, measurement noises, and grid load variations. It is further demonstrated that the mentioned schemes are able to tolerate probable occurrence of sudden imbalance between generation and load due to relevant faults/failures in the wind farm or electric grid. [ABSTRACT FROM AUTHOR]

Unmanned Aircraft Systems (UASs) are becoming ever more promising over the last decade. The Sense and Avoid (S&A) system plays a profoundly important role in integrating UASs into the National Airspace System (NAS) with reliable and safe operations. After analyzing the manner of S&A system, this paper systematically presents an overview on the recent progress in S&A technologies in the sequence of fundamental functions/components of S&A in sensing techniques, decision making, path planning, and path following. The approaches to these four aspects are outlined and summarized, based on which the existing challenges and potential solutions are highlighted for facilitating the development of S&A systems. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative integrated path planning and trajectory tracking control framework for a quadrotor unmanned aerial vehicle (UAV) in the presence of environmental and systematic uncertainties to achieve integrated guidance and control. Firstly, in order to perform real-time path planning, a computationally cost-effective planning algorithm is designed to find an optimal and smooth path while avoiding both static and dynamic obstacles. Then, by employing the pure-pursuit path following approach, the generated geometric path is converted to a trajectory profile related to time, which serves as the reference commands for the low-level trajectory tracking controller. Finally, a novel adaptive sliding mode trajectory tracking controller is proposed to compensate model uncertainties and maintain the desired tracking performance for the studied quadrotor UAV. With the proposed adaptive schemes, overestimation of uncertain parameters can be avoided, which further contributes to avoiding control chattering of the system. The performance of the proposed framework is validated through comparative simulation and experimental tests based on a quadrotor UAV subject to model uncertainties and environmental obstacles, which confirms the effectiveness and superiority of the proposed approach for practical applications. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a bibliographical review on reconfigurable (active) fault-tolerant control systems (FTCS) is presented. The existing approaches to fault detection and diagnosis (FDD) and fault-tolerant control (FTC) in a general framework of active fault-tolerant control systems (AFTCS) are considered and classified according to different criteria such as design methodologies and applications. A comparison of different approaches is briefly carried out. Focuses in the field on the current research are also addressed with emphasis on the practical application of the techniques. In total, 376 references in the open literature, dating back to 1971, are compiled to provide an overall picture of historical, current, and future developments in this area. [Copyright &y& Elsevier]

This paper proposes an adaptive fault-tolerant cooperative control (FTCC) scheme for networked unmanned aerial vehicles (UAVs) in the presence of actuator faults and wind effects by artfully introducing fractional order calculus, proportional–integral–derivative (PID), and recurrent neural networks. Fractional order sliding-mode surface and PID-type error mapping are first utilized to transform the synchronization tracking errors of all UAVs into a new set of errors. Then, based on these newly constructed errors, an FTCC scheme is developed to synchronously track their references. Moreover, Butterworth low-pass filter (BLF) and recurrent neural network (RNN) learning strategies are assimilated to handle the unknown terms induced by the actuator faults and wind effects. Finally, theoretical analysis and comparative hardware-in-the-loop experimental demonstrations have shown the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, the classical least squares (LS) and recursive least squares (RLS) for parameter estimation have been re-examined in the light of the present day computing capabilities. It has been demonstrated that for linear time-invariant systems, the performance of blockwise least squares (BLS) is always superior to that of RLS. In the context of parameter estimation for dynamic systems, the current computational capability of personal computers are more than adequate for BLS. However, for time-varying systems with abrupt parameter changes, standard blockwise LS may no longer be suitable due to its inefficiency in discarding “old” data. To deal with this limitation, a novel sliding window blockwise least squares approach with automatically adjustable window length triggered by a change detection scheme is proposed. Two types of sliding windows, rectangular and exponential, have been investigated. The performance of the proposed algorithm has been illustrated by comparing with the standard RLS and an exponentially weighted RLS (EWRLS) using two examples. The simulation results have conclusively shown that: (1) BLS has better performance than RLS; (2) the proposed variable-length sliding window blockwise least squares (VLSWBLS) algorithm can outperform RLS with forgetting factors; (3) the scheme has both good tracking ability for abrupt parameter changes and can ensure the high accuracy of parameter estimate at the steady-state; and (4) the computational burden of VLSWBLS is completely manageable with the current computer technology. Even though the idea presented here is straightforward, it has significant implications to virtually all areas of application where RLS schemes are used. [Copyright &y& Elsevier]

Concurrent occurrences of actuator faults and wind effects can significantly threaten the flight safety of multiple unmanned aerial vehicles (multi-UAVs). To address this difficult control problem against actuator faults and wind effects, a composite decentralized fractional-order (FO) backstepping adaptive neural fault-tolerant control (FTC) method is presented for the attitude synchronization tracking of multi-UAVs, which is integrated with neural networks (NNs), disturbance observers (DOs), FO calculus, and high-order sliding-mode differentiators (HOSMDs). The distinctive feature of this work is addressing the attitude synchronization tracking control problem with actuator faults and wind effects in a decentralized framework and proposing a composite approximation method for multi-UAVs. It is shown that by using Lyapunov methods the synchronization tracking control is achieved even when multi-UAVs simultaneously encounter wind effects and actuator faults. Comparative simulation results illustrate the theoretical feasibility. [ABSTRACT FROM AUTHOR]

Recently, multiple unmanned vehicles have attracted a great deal of attention as viable solutions to a wide variety of civilian and military applications. Among many topics in the field of multiple unmanned systems, formation control and coordination is of great importance. This paper presents a comprehensive literature review on the strategies and methodologies applied for formation control of multiple unmanned ground vehicles in both normal and faulty situations. First, the basic definitions of formation control and coordination are provided as well as their classification. Second, a comprehensive literature review of formation control strategies is introduced. Moreover, an overview on fault detection and diagnosis and fault-tolerant cooperative control of UGVs is presented. Finally, open problems, challenges, and future directions are highlighted. [ABSTRACT FROM AUTHOR]

This paper addresses the approaching trajectory control problem for the final phase of non-cooperative spacecraft proximity operations in the presence of disturbances and even input saturation. As a stepping stone, a novel line-of-sight tracking model is developed to describe attitude maneuver towards the target in the proximity. Then, a two-stage artificial potential function is employed to enable the pursuer spacecraft to comply the safety trajectory during approaching the target. In each stage, gradients of potential function are analyzed and the local minimum problem associated with potential function can be addressed. Furthermore, a saturated control law is proposed to ensure a reliable real-time tracking measurement of the target, and the controller rigorously enforces safe path and actuator magnitude constraints. The associated stability proof is accomplished through Lyapunov method. Simulations are carried out to evaluate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With focusing on solar photovoltaic (PV) systems operating at microgrid (MG) level, this study investigates the impacts of different physical faults and cyberattacks as well as designing an intelligent faults/attacks detection and diagnosis system. The ability to quickly identify and diagnose faults/attacks enables local controllers and energy management system to accommodate or mitigate the negative effects of physical faults or cyberattacks in a MG. This allows the MG to carry on operating without experiencing any significant interruptions. In this regard, the current paper investigates a hybrid AC/DC MG made up of different distributed energy resources (DER), including solar PV arrays, wind turbines, and battery energy storage systems. An intelligent hybrid diagnosis (IHD) scheme is introduced for online monitoring and diagnosing the data to reflect the real-time status of the PV system operating at the MG level. This hybrid system uses three parallel units, including a "fuzzy inference system (i.e., a rule-based unit)", a "power spectrum estimator (i.e., a signal-based unit)", and an "adaptive neuro-fuzzy inference system (i.e., a model-based unit)". A realistic MG benchmark model with a wide range of operating conditions and dynamic electrical loads in the presence of potential MG disturbances is used to demonstrate the high performance and resilience of the proposed IHD scheme under various types of faults/attacks scenarios. • The impacts of physical faults and cyberattacks on photovoltaic (PV) systems at microgrid (MG) level are investigated. • A faults/attacks detection and diagnosis scheme referred to as intelligent hybrid diagnosis (IHD) scheme is presented. • A hybrid AC/DC MG composed of several renewable distributed energy resources (DER) is considered. • Three parallel diagnosis units including rule-based, signal-based, and model-based units for IHD scheme are designed. • Simulations on realistic MG model with wide range of operating conditions in the presence of disturbances are performed. [ABSTRACT FROM AUTHOR]

In the close formation flight, the wake vortex induced by the leading aircraft will have adverse effects on the safe flight of the trailing unmanned aerial vehicle (UAV). Hence, this paper investigates a difficult problem of safe control for the trailing UAV against actuator faults, input saturation, and wake vortex effect. By using disturbance observers, external wake vortex, disturbances, and internal actuator faults are estimated. Then, with the help of estimated knowledge of disturbance, backstepping control laws are developed for the longitudinal dynamics and the lateral-directional dynamics, respectively. One of the key features of the proposed strategy is that, the inherent problem, i.e., “explosion of complexity” in conventional backstepping control, is solved by the presented dynamic surface control scheme. Another key feature is that external wake vortex, disturbances, and internal actuator faults, input saturation are simultaneously considered. It is shown by Lyapunov stability analysis that the closed-loop system is uniformly ultimately bounded with safety requirements guaranteed even in the presence of wake vortex and actuator faults. The effectiveness of the proposed approach is further validated by simulation results. [ABSTRACT FROM AUTHOR]

Generally, the relative parameters of continuous multi-impacts are ambiguous in the practical engineering. In this paper, continuous twice-impacts of Ultra-High Molecule Weight Polyethylene (UHMWPE) laminate which is fixed by four bolted joints are designed and conducted by experiment and simulation. The experimental results of first impact are used to verify the numerical model, in which a solid blunt projectile penetrates the laminate with the velocity of 216 m/s. The obtained results of experiment and simulation indicate that strong lateral effects can be observed for the twice-impacts of UHMWPE target fixed with bolted joints, then the deformation responses of bolt holes are studied to discuss parameters identification of secondary non-penetration impact, i.e., the velocity and impact position of secondary penetrator are identified based on inverse problem model. Finally, the numerical results calculated with the identification parameters are in good agreement with the twice-impacts test. The research scheme of this paper is significant to recognize the process of multi-impacts. [ABSTRACT FROM AUTHOR]

Although locus coeruleus (LC) has been demonstrated to play a critical role in the cognitive function of Parkinson's disease (PD), the underlying mechanism has not been elucidated. The objective was to investigate the relationship among LC degeneration, cognitive performance, and the glymphatic function in PD. In this retrospective study, 71 PD subjects (21 with normal cognition; 29 with cognitive impairment (PD-MCI); 21 with dementia (PDD)) and 26 healthy controls were included. All participants underwent neuromelanin-sensitive magnetic resonance imaging (NM-MRI) and diffusion tensor image scanning on a 3.0 T scanner. The brain glymphatic function was measured using diffusion along the perivascular space (ALPS) index, while LC degeneration was estimated using the NM contrast-to-noise ratio of LC (CNR LC). The ALPS index was significantly lower in both the whole PD group (P = 0.04) and the PDD subgroup (P = 0.02) when compared to the controls. Similarly, the CNR LC was lower in the whole PD group (P < 0.001) compared to the controls. In the PD group, a positive correlation was found between the ALPS index and both the Montreal Cognitive Assessment (MoCA) score (r = 0.36; P = 0.002) and CNR LC (r = 0.26; P = 0.03). Mediation analysis demonstrated that the ALPS index acted as a significant mediator between CNR LC and the MoCA score in PD subjects. The ALPS index, a neuroimaging marker of glymphatic function, serves as a mediator between LC degeneration and cognitive function in PD. • Exploring the path of locus coeruleus (LC) affects cognitive function. • Multimodal MRI imaging address the function of glymphatic system and LC. • LC degeneration is related to cognition in Parkinson's disease (PD). • Impaired glymphatic function as a mediator in this relationship in PD. [ABSTRACT FROM AUTHOR]

Study results of developing formation control system for multi-spacecraft that requires avoiding obstacles and maintaining the formation configuration are presented. In particular, nonlinear adaptive feedback control law is developed by employing special potential functions and a kind of time-varying sliding manifold, to enable the spacecraft formation in a specific configuration by taking into account the obstacle avoidance requirement while tracking a moving target in a way of cooperation or not. Moreover, capability for handling multiple tasks by the proposed control system is demonstrated in the presence of disturbances and parametric uncertainties. The stability proof is based on a Lyapunov-like analysis and the properties of the proposed potential functions. Numerical simulation of the proposed method is presented to demonstrate the advantages with respect to obstacle avoidance, fast tracking and formation flying configuration reconstruction capability. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the results of a study on fault-tolerant control of a ship propulsion benchmark [Izadi-Zamanabadi, R., & Blanke, M. (1999). A ship propulsion system as a benchmark for fault tolerant control. Control Engineering Practice, 7 (2), 227–239] which uses estimated or virtual measurements as feedback variables. The estimator operates on a self-adjustable design model so that its outputs can be made immune to the effects of a specific set of component and sensor faults. The adequacy of sensor redundancy is measured using the control reconfigurability [Wu, N. E., Zhou, K., & Salomon, G. (2000). Reconfigurability in linear time-invariant systems. Automatica, 36 (11), 1767–1771] and the number of sensor based measurements are increased when this level is found inadequate. As a result, sensor faults that are captured in the estimator''s design model can be tolerated without the need for any reconfiguration actions. Simulations for the ship propulsion benchmark show that, with additional sensors added as described and the estimator in the loop, satisfactory fault-tolerance is achieved under two additive sensor faults, an incipient fault, and a parametric fault, without having to alter the original controller in the benchmark. [Copyright &y& Elsevier]

The single-axis maneuver planning problem is investigated for underactuated spacecraft with one unactuated axis fixed in a certain direction of the spacecraft in the presence of a single conical forbidden pointing zone. Specifically, a nonnominal Euler rotation scenario is formulated by imposing admissible constraints on rotation axes, and it is proven that the singular sensitive axis can be pointed along an arbitrary inertial direction outside the forbidden zone by at most two principal rotations. Given this fact, an exact solution is obtained by numerically solving a quartic trigonometric function equation about the first rotation angle, while enforcing the rotation axes tangent to the forbidden cone for the shorter path. Furthermore, an approximate but computationally efficient solution is analytically developed by Ferrari's formulas for the linearized quartic trigonometric function equation around the first tangent direction, where the smallest real one is selected from the four candidate roots. The solvability of the two-step planning schemes is also assured by the corresponding accessible regions. Finally, comprehensive numerical simulations are conducted to corroborate the effectiveness of both the exact and approximate planning schemes. [ABSTRACT FROM AUTHOR]

This paper proposes an active fault-tolerant control strategy for a quadrotor helicopter against actuator faults and model uncertainties while explicitly considering fault estimation errors based on adaptive sliding mode control and recurrent neural networks. Firstly, a novel adaptive sliding mode control is proposed. In virtue of the proposed adaptive schemes, the system tracking performance can be guaranteed in the presence of model uncertainties without stimulating control chattering. Then, due to the fact that model-based fault estimation schemes may fail to correctly estimate fault magnitudes in the presence of model uncertainties, a fault estimation scheme is proposed by designing a parallel bank of recurrent neural networks. With the trained networks, the severity of actuator faults can be precisely estimated. Finally, by synthesizing the proposed fault estimation scheme with the developed adaptive sliding mode control, an active fault-tolerant control mechanism is established. Moreover, the issue of actuator fault estimation error is explicitly considered and compensated by the proposed adaptive sliding mode control. The effectiveness of the proposed active fault-tolerant control strategy is validated through real experiments based on a quadrotor helicopter subject to actuator faults and model uncertainties. Its advantages are demonstrated in comparison with a model-based fault estimator and a conventional adaptive sliding mode control. [ABSTRACT FROM AUTHOR]

• Both multiple quadcopters grouped to different blocks and one block are considered. • Spraying time is reduced by 10.8% and 13.2% in simulation and actual flight tests. • The optimization complexity of one quadcopter's path planning is significantly reduced. • A simulation prototype by MATLAB GUIs and Stateflow is built for mission planner. As the approaching of Agriculture 4.0 era and advancements of new technologies of Unmanned Aerial Vehicles (UAVs) and particularly quadcopter UAVs, plant protection quadcopters are becoming increasingly popular and practical in pesticide spraying, fertilization, pollination, seeding, and other agricultural activities. One of the main problems for plant protection quadcopters is completing planning tasks efficiently and quickly. Therefore, this paper proposes an autonomous task assignment and decision-making method for coverage path planning by multiple cooperative quadcopters. The Sequential Quadratic Programming (SQP) method is adopted to acquire the optimal solution for the proposed problem. Then, a simulation platform by MATLAB Graphical User Interfaces (GUIs) is established using the Stateflow technique, and multiple ZY-UAV-680 quadrotor UAVs are employed to carry out the actual flight tests. Finally, simulations and actual flight tests are conducted to demonstrate the effectiveness of the autonomous optimal task assignment and decision-making method. The final results show that: the proposed method can divide multiple UAVs reasonably to several blocks; the time differences between the simulation test and real flight test are only 39.8 sec and 20.6 sec, and accounts for 6.6% and 3.9% of the spraying time spent on real flight test by three cooperative quadrotors, respectively; the optimal scheme can save 60.8 sec and 80.0 sec in the simulation tests and the real flight tests, which accounts for 10.8% and 13.2% of the time spent on average scheme, respectively. Therefore, it can be concluded that the simulation results can match the real flight test results quite well regardless of average scheme or optimal scheme, and the optimal scheme is more efficient and timesaving than the average scheme. [ABSTRACT FROM AUTHOR]

Abstract Background and aims Cardiovascular disease (CVD) is the leading cause of death in chronic kidney disease (CKD) patients, however, the underlying mechanisms that link CKD and CVD are not fully understood and limited treatment options exist in this high-risk population. microRNAs (miRNA) are critical regulators of gene expression for many biological processes in atherosclerosis, including endothelial dysfunction and inflammation. We hypothesized that renal injury-induced endothelial miRNAs promote atherosclerosis. Here, we demonstrate that dual inhibition of endothelial miRNAs inhibits atherosclerosis in the setting of renal injury. Methods Aortic endothelial miRNAs were analyzed in apolipoprotein E-deficient (Apoe −/-) mice with renal damage (5/6 nephrectomy, 5/6Nx) by real-time PCR. Endothelial miR-92a-3p and miR-489-3p were inhibited by locked-nucleic acid (LNA) miRNA inhibitors complexed to HDL. Results Renal injury significantly increased endothelial miR-92a-3p levels in Apoe −/-;5/6Nx mice. Dual inhibition of miR-92a-3p and miR-489-3p in Apoe −/− ;5/6Nx with a single injection of HDL + LNA inhibitors significantly reduced atherosclerotic lesion area by 28.6% compared to HDL + LNA scramble (LNA-Scr) controls. To examine the impact of dual LNA treatment on aortic endothelial gene expression, total RNA sequencing was completed, and multiple putative target genes and pathways were identified to be significantly altered, including the STAT3 immune response pathway. Among the differentially expressed genes, Tgfb2 and Fam220a were identified as putative targets of miR-489-3p and miR-92a-3p, respectively. Both Tgfb2 and Fam220a were significantly increased in aortic endothelium after miRNA inhibition in vivo compared to HDL + LNA-Scr controls. Furthermore, Tgfb2 and Fam220a were validated with gene reporter assays as direct targets of miR-489-3p and miR-92a-3p, respectively. In human coronary artery endothelial cells, over-expression and inhibition of miR-92a-3p decreased and increased FAM220A expression, respectively. Moreover, miR-92a-3p overexpression increased STAT3 phosphorylation, likely through direct regulation of FAM220A, a negative regulator of STAT3 phosphorylation. Conclusions These results support endothelial miRNAs as therapeutic targets and dual miRNA inhibition as viable strategy to reduce CKD-associated atherosclerosis. Graphical abstract Image 1 Highlights • Aortic endothelial miR-92a-3p levels are increased in a mouse model of renal injury. • Dual inhibition of miR-92a-3p and miR-489-3p significantly reduced atherosclerotic lesion area (28.6%) after a week. • Dual miRNA inhibition in 5/6Nx; Apoe −/− mice significantly altered TGFβ signaling pathway and STAT3 transcriptional activity. • Tgfb2 and Fam220a are novel targets of miR-489-3p and miR-92a-3p, respectively. • Within human endothelial cells, miR-92a-3p directly regulates Fam220a, which negatively regulates STAT3 activity. [ABSTRACT FROM AUTHOR]

There are significant advantages using the autonomous underwater vehicle (AUV) for underwater search. Compared with a single AUV, multi-AUV offers greater efficiency and better stability in underwater search. At the same time, the theoretical and technical level of autonomous navigation and cooperative control of multi-AUV formation is the key to the implementation of the underwater search task. The following key factors are worth discussing in the application of multi-AUV in underwater search: task allocation, path planning, and formation control. The purpose of this paper is to grasp the application and development trend of multi-AUV formation in underwater search, so as to summarize the past, present, and future research and development trends of this investigation field in detail. • To the best of authors' knowledge, this is the first systematic and comprehensive survey of multi-AUV underwater search, and is intended to assist research and development of multi-AUV underwater search applications. • Several aspects of task allocation, path planning, and formation control are considered and reviewed. The strengths, weaknesses, limitations, and challenges of the respective algorithms of the above techniques are explicitly discussed, to gain a deeper understanding of how multi-AUV multi-target search is conducted. • The opportunities and challenges of this research are listed based on the purpose of using multi-AUV underwater multi-target search. [ABSTRACT FROM AUTHOR]

This paper addresses the control problem of air-breathing hypersonic vehicles subject to input nonlinearities, aerodynamic uncertainties and flexible modes. An adaptive backstepping controller and a dynamic inverse controller are developed for the altitude subsystem and the velocity subsystem, respectively, where the former eliminates the problem of “explosion of terms” inherent in backstepping control. Moreover, a modified smooth inverse of the dead-zone is proposed to compensate for the dead-zone effects and reduce the computational burden. Based on this smooth inverse, an input nonlinear pre-compensator is designed to handle input saturation and dead-zone nonlinearities, which leads to a simpler control design for the altitude subsystem subject to these two input nonlinearities. It is proved that the proposed controllers can guarantee that all closed-loop signals are bounded and the tracking errors converge to an arbitrarily small residual set. Simulation results are carried out to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper explores the fault-tolerant control (FTC) problem for full-state error constrained attitude tracking of an uncertain spacecraft. The existing FTC solutions to this problem generally rely on an uniform strong controllability (USC) assumption that may not hold in the presence of multiplicative actuator faults. In this work, a sufficient condition for the USC assumption is presented to help evaluate the applicability of existing FTC solutions. Then, based on the unified error transformation method and symmetric barrier Lyapunov functions, a saturated adaptive robust FTC algorithm is proposed, which can eliminate the USC assumption without requiring the multiplicative actuator faults to be differentiable, while ensuring that (i) full-state error constraints are never violated; (ii) all closed-loop signals are bounded, despite the simultaneous presence of inertia uncertainties, disturbances, and actuator faults. Finally, simulation results are provided to verify our theoretical findings. [ABSTRACT FROM AUTHOR]

• A novel AHNM, which not only compensates l 1 -norm with l 2 -norm, but also adaptively evaluates the importance of each singular value by introducing a significance factor, is proposed. • The proposed AHNM is efficiently solved by using the alternating minimization method. In particular, all the subproblems associated with the proposed AHNM model have closed-form solutions. • Based on the proposed AHNM, we construct a general image restoration framework and develop an efficient image restoration algorithm. • Extensive experimental results demonstrate that our proposed AHNM method outperforms many state-of-the-art methods in terms of quantitative and qualitative quality. Rank minimization methods have achieved promising performance in various image processing tasks. However, there are still two challenging problems in the existing works. One is that most of the current methods only regularize singular values by using a single l 1 -norm, such as the well-known nuclear norm minimization (NNM) and the weighted nuclear norm minimization (WNNM). Consequently, many small singular values are shrunk to zero, which is unbeneficial for restoring image details. The other is that how to adaptively evaluate the importance of each singular value is still a suspending problem. In this paper, we propose a novel rank minimization method, namely adaptive hybrid norm minimization (AHNM) model, to solve the above problems. Specifically, for each singular value, we employ l 2 -norm to compensate for l 1 -norm, and introduce a significance factor to assess its importance adaptively. More importantly, we show that closed-form solutions for all subproblems can be derived simply by using alternating optimization. With the aid of the proposed AHNM model, we further develop a general yet effective image restoration algorithm based on the nonlocal self-similarity (NSS) of images. Numerous experimental results demonstrate that the proposed AHNM model consistently outperforms many state-of-the-art restoration methods, including model-based methods and deep learning-based methods. [ABSTRACT FROM AUTHOR]

A centralized multi-AGV motion planning method is proposed. In contrast to the prevalent planners with decentralized (decoupled) formulations, a centralized planner contains no priority assignment, decoupling, or other specification strategies, thus is free from being case-dependent and deadlock-involved. Although centralized motion planning is computationally expensive, it deserves investigations in schemes that are sensitive to solution quality but insensitive to computation time. Specifically, centralized multi-AGV motion planning is formulated as an optimal control problem in this work, wherein differential algebraic equations are used to describe the AGV dynamics, mechanical restrictions, and exterior constraints. Orthogonal collocation direct transcription method is adopted to discretize the original infinite-dimensional optimal control problem into a large-scale nonlinear programming (NLP) problem, which is solved using interior point method thereafter. Exhaustive simulations are conducted on 10-AGV formation reconfiguration tasks. Simulation results show the validation, unification, and real-time implementation potential of the introduced centralized planner. Particularly, the computation time on a PC reduces to several seconds with near-optimal initial guess in the NLP solving process, making receding horizon replanning possible via this centralized planner. [ABSTRACT FROM AUTHOR]

Graph Neural Networks (GNNs) are widely utilized for graph data mining, attributable to their powerful feature representation ability. Yet, they are prone to adversarial attacks with only slight perturbations of input data, limiting their applicability to critical applications. Vulnerability analysis of GNNs is thus essential if more robust models are to be developed. To this end, a Layer-wise Relevance Propagation based Adversarial attacking (LRP2A) model is proposed 1 1 Data and code are available at https://github.com/duiyady/LRP2A.. Specifically, to facilitate applying LRP to the "black-box" victim model, we train a surrogate model based on a sophisticated re-weighting network. The LRP algorithm is then leveraged for unraveling "contributions" among the nodes in the downstream classification task. Furthermore, the graph adversarial attacking algorithm is intentionally designed to be both interpretable and efficient. Experimental results prove the effectiveness of the proposed attacking model on GNNs for node classification. Additionally, the adoption of LRP2A allows the choice of the adversarial attacking strategies on the GNN interpretable, which in turn can gain deeper insights on the GNN's vulnerability. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of optimal reliability in over-actuated systems. Overloading an actuator decreases its overall lifetime and reduces its average performance over a long time. Therefore, performance and reliability are two conflicting requirements. While appropriate reliability is related to average loads, good performance is related to fast response and sufficient loads generated by actuators. Actuator redundancy allows us to address both performance and reliability at the same time by properly allocating desired loads among redundant actuators. The main contribution of this paper is the on-line optimization of the overall plant reliability according to performance objective using an MIT (Massachusetts Institute of Technology) rule-based method. The effectiveness of the proposed method is illustrated through an experimental application to an octocopter helicopter testbed. [ABSTRACT FROM AUTHOR]

This paper presents a dual adaptive fault-tolerant control strategy for a quadrotor helicopter based on adaptive sliding mode control and adaptive boundary layer. Within the proposed adaptive control strategy, both model uncertainties and actuator faults can be compensated without the knowledge of the uncertainty bounds and fault information. By virtue of the proposed adaptive control scheme, the minimum discontinuous control gain is adopted, which significantly reduces the control chattering effect. As compared to the existing adaptive sliding mode control schemes in the literature, larger actuator faults can be tolerated by employing the proposed control scheme while suppressing control chattering. Moreover, boundary layer is used to smoothen control discontinuity and further eliminate control chattering. Nevertheless, the choice of boundary layer thickness is a trade-off between system stability and tracking accuracy. By explicitly considering this fact, an adaptive boundary layer is developed and synthesized with the proposed adaptive control framework to ensure stability and tracking accuracy of the considered system. When the control parameter tends to be overestimated, the thickness of boundary layer can be appropriately adjusted to avoid control parameter overestimation. Simulation and experimental tests of a quadrotor helicopter are both conducted to validate the effectiveness of the proposed control scheme. Its advantages are demonstrated in comparison with a conventional adaptive sliding mode control scheme. [ABSTRACT FROM AUTHOR]