Hierarchical Distributed Adaptive Fault-Tolerant Control of Nonlinear Fractional-Order Multiagent Systems With Faults and Periodic Disturbances Using Event-Triggered Communication.

This article presents a distributed fault-tolerant control (FTC) scheme for nonlinear fractional-order (FO) multiagent systems (MASs) with the order lying in (0, 1, such that the proposed control architecture can be directly applied to both FO and integer-order (IO) systems without any modifications. To handle the unexpected actuator faults encountered by the FO MASs, a hierarchical FTC mechanism is developed for each system by constructing an event-triggered distributed FO estimator at the upper layer to estimate the leader system's output via conditionally triggered neighboring information, and an FTC unit at the lower layer to counteract the loss-of-effectiveness faults via Nussbaum function with FO criteria. To further address the unknown nonlinear functions involving bias faults and periodic disturbances, the Fourier series expansion technique is used to construct the input variables of fuzzy neural networks (FNNs), such that the FNNs with dynamically adjusted weight matrices, centers, and widths can be developed for each FO system to act as the learning module. It is shown by FO Lyapunov stability analysis that all follower systems can track the leader system against faults and periodic disturbances. Simulation results on FO systems and hardware-in-the-loop experiment results on IO fixed-wing unmanned aerial vehicles show the extensive feasibility of the developed scheme.

Decentralized Implicit Inverse Control for Large-Scale Hysteretic Nonlinear Time-Delay Systems and Its Application on Triple-Axis Giant Magnetostrictive Actuators.

This article proposes fuzzy-logic systems (FLSs)-based decentralized adaptive implicit inverse control scheme for a class of large-scale nonlinear systems with time delays and multihysteretic loops. Our novel algorithms feature hysteretic implicit inverse compensators designed to effectively mitigate multihysteretic loops in large-scale systems. In this article, hysteretic implicit inverse compensators can replace the traditional hysteretic inverse models, which are exceedingly difficult to construct, and no longer necessary. The authors provide three contributions: 1) a searching mechanism to obtain the approximate value of the practical input signal from the so-called hysteretic temporary control law; 2) the arbitrarily small L∞ norm of the tracking error attained by utilizing the proposed initializing technique, which applies the combination of FLSs and a finite covering lemma to deal with time delays; and 3) the construction of a triple-axis giant magnetostrictive motion control platform, which validates the effectiveness of the proposed control scheme and algorithms.

State Estimation for Recurrent Neural Networks With Intermittent Transmission.

This work addresses the state estimation problem for recurrent neural networks over capacity-constrained communication channels. The intermittent transmission protocol is used to reduce the communication load, where a stochastic variable with a given distribution is used to describe the transmission interval. A corresponding transmission interval-dependent estimator is designed, and an estimation error system based on it is also derived, whose mean-square stability is proved by constructing an interval-dependent function. By analyzing the performance in each transmission interval, sufficient conditions of the mean-square stability and the strict (Q,S,R) - γ -dissipativity are established for the estimation error system. Finally, the correctness and the superiority of the developed result are illustrated by a numerical example.

Differential flatness-based adaptive robust tracking control for wheeled mobile robots with slippage disturbances.

Wheeled mobile robots (WMRs) have a wide range of applications in logistics transportation and industrial productions, among which the motion control has always been one of the hot spots in the current WMR researches. However, most of previous designed controllers assumed that the WMR motion had no slippage. Ignoring the slippage factors usually results in a decrease in control performance and even leads to unstable motion. To address such a challenge, a kinematic model with differential flatness is established through dynamic feedback-linearization, which comprehensively considers the multidirectional slippage of mobile robot, including longitudinal and steering slippage. Subsequently, benefited from the one-to-one mapping of states and inputs to flat outputs in differential flat system, an adaptive robust control (ARC) method is proposed to stabilize the system. Different from previous robust control studies, even if the knowledge of the upper bound of system uncertainties is unknown in advance, the proposed adaptive robust controller can still achieve satisfying performance by adaptive estimation of the upper bound of system uncertainties. The effectiveness and feasibility of the proposed method are confirmed by comparative experiments on WMR with slippage disturbance.

Reinforcement Learning-Based Fractional-Order Adaptive Fault-Tolerant Formation Control of Networked Fixed-Wing UAVs With Prescribed Performance.

This article investigates the fault-tolerant formation control (FTFC) problem for networked fixed-wing unmanned aerial vehicles (UAVs) against faults. To constrain the distributed tracking errors of follower UAVs with respect to neighboring UAVs in the presence of faults, finite-time prescribed performance functions (PPFs) are developed to transform the distributed tracking errors into a new set of errors by incorporating user-specified transient and steady-state requirements. Then, the critic neural networks (NNs) are developed to learn the long-term performance indices, which are used to evaluate the distributed tracking performance. Based on the generated critic NNs, actor NNs are designed to learn the unknown nonlinear terms. Moreover, to compensate for the reinforcement learning errors of actor-critic NNs, nonlinear disturbance observers (DOs) with skillfully constructed auxiliary learning errors are developed to facilitate the FTFC design. Furthermore, by using the Lyapunov stability analysis, it is shown that all follower UAVs can track the leader UAV with predesigned offsets, and the distributed tracking errors are finite-time convergent. Finally, comparative simulation results are presented to show the effectiveness of the proposed control scheme.

Early versus delayed mobilization for arthroscopic rotator cuff repair (small to large sized tear): a meta-analysis of randomized controlled trials.

BACKGROUND: The timing to start passive or active range of motion (ROM) after arthroscopic rotator cuff repair remains unclear. This systematic review and meta-analysis evaluated early versus delayed passive and active ROM protocols following arthroscopic rotator cuff repair. The aim of this study is to systematically review the literature on the outcomes of early active/passive versus delayed active/passive postoperative arthroscopic rotator cuff repair rehabilitation protocols. METHODS: A systematic review and meta-analysis of randomized controlled trials (RCTs) published up to April 2022 comparing early motion (EM) versus delayed motion (DM) rehabilitation protocols after arthroscopic rotator cuff repair for partial and full-thickness tear was conducted. The primary outcome was range of motion (anterior flexion, external rotation, internal rotation, abduction) and the secondary outcomes were Constant-Murley score (CMS), Simple Shoulder Test Score (SST score) and Visual Analogue Scale (VAS). RESULTS: Thirteen RCTs with 1,082 patients were included in this study (7 RCTs for early passive motion (EPM) vs. delayed passive motion (DPM) and 7 RCTs for early active motion (EAM) vs. delayed active motion (DAM). Anterior flexion (1.40, 95% confidence interval (CI), 0.55-2.25) and abduction (2.73, 95%CI, 0.74-4.71) were higher in the EPM group compared to DPM. Similarly, EAM showed superiority in anterior flexion (1.57, 95%CI, 0.62-2.52) and external rotation (1.59, 95%CI, 0.36-2.82), compared to DAM. There was no difference between EPM and DPM for external rotation, retear rate, CMS and SST scores. There was no difference between EAM and DAM for retear rate, abduction, CMS and VAS. CONCLUSION: EAM and EPM were both associated with superior ROM compared to the DAM and DPM protocols. EAM and EPM were both safe and beneficial to improve ROM after arthroscopic surgery for the patients with small to large sized tears.

Graph-Based Multicentroid Nonnegative Matrix Factorization.

Nonnegative matrix factorization (NMF) is a widely recognized approach for data representation. When it comes to clustering, NMF fails to handle data points located in complex geometries, as each sample cluster is represented by a centroid. In this article, a novel multicentroid-based clustering method called graph-based multicentroid NMF (MCNMF) is proposed. Because the method constructs the neighborhood connection graph between data points and centroids, each data point is represented by adjacent centroids, which preserves the local geometric structure. Second, because the method constructs an undirected connected graph with centroids as nodes, in which the centroids are divided into different centroid clusters, a novel data clustering method based on MCNMF is proposed. In addition, the membership index matrix is reconstructed based on the obtained centroid clusters, which solves the problem of membership identification of the final sample. Extensive experiments conducted on synthetic datasets and real benchmark datasets illustrate the effectiveness of the proposed MCNMF method. Compared with single-centroid-based methods, the MCNMF can obtain the best experimental results.

Comparative Analysis of Posterior Approach Versus Anterior Approach for Posterior Tibial Plateau Fractures: A Systematic Review and Meta-analysis.

BACKGROUND: Posterior tibial plateau fractures can lead to significant posttraumatic instability if not treated properly. It remains unclear which surgical approach achieves better patient outcomes. The objective of this systematic review and meta-analysis was to assess postoperative outcomes in patients undergoing anterior, posterior, or combined approach for posterior tibial plateau fractures. METHODS: The PubMed, Embase, Web of Science, The Cochrane Library, and Scopus were searched for studies published before October 26, 2022, comparing anterior, posterior, or combined approaches for posterior tibial plateau fractures. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Outcomes included complications, infections, range of motion (ROM), operation time, union rates, and functional scores. Significance was set at p < 0.05. Meta-analysis was conducted with STATA software. RESULTS: In total, 29 studies with a total of 747 patients were included for quantitative and qualitative analysis. Compared with other approaches, the posterior approach for posterior tibial plateau fractures was associated with a better ROM and shorter operative time. The complication rates, infection rates, union time, and hospital for special surgery (HSS) scores were not significantly different between surgical approaches. CONCLUSIONS: The posterior approach for posterior tibial plateau fractures offers advantages such as improved ROM and shorter operative time. However, there are concerns regarding prone positioning in patients with medical or pulmonary comorbidities and indications in polytrauma cases. Further prospective studies are needed to determine the optimal approach for these fractures. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Morel-Lavallee lesions and number of surgeries for associated injuries predict surgical site infection risk following pelvic ring injury osteosynthesis.

We examined the incidence and causative factors of surgical site infection (SSI) following osteosynthesis for pelvic ring injury by reviewing the data of 97 consecutive patients with pelvic ring injuries treated between 2014 and 2019. Osteosyntheses, including internal or external skeletal fixation with plates or screws, were performed based on fracture type and patient's condition. Fractures were treated surgically, with a 36 months minimum follow-up period. Eight (8.2%) patients experienced SSI. The most common causative pathogen was Staphylococcus aureus. Patients with SSI had significantly worse functional outcomes at 3, 6, 12, 24, and 36 months than those without. For patients with SSI, the average Merle d'Aubigné and Majeed scores at 3, 6, 12, 24, and 36 months after injury were 2.4, 4.1, 8.0, 11.0, and 11.3, and 25.5, 32.1, 47.9, 61.9, and 63.3, respectively. Patients with SSI had a higher likelihood of undergoing staged operations (50.0 vs. 13.5%, p = 0.02), more surgeries for associated injuries (6.3% vs. 2.5%, p = 0.04), higher likelihood of Morel-Lavallee lesions (50.0% vs. 5.6%, p = 0.002), higher incidence of diversional colostomy (37.5% vs. 9.0%, p = 0.05), and longer intensive care unit stay (11.1 vs. 3.9 days, p = 0.001) than those without. The contributing factors for SSI were Morel-Lavallee lesions (odds ratio [OR] 4.55, 95% confidence interval [95% CI] 3.34-50.0) and other surgeries for associated injuries (OR 2.37, 95% CI 1.07-5.28). Patients with SSI after osteosynthesis for pelvic ring injuries may have worse short-term functional outcomes.

Active Human-Following Control of an Exoskeleton Robot With Body Weight Support.

This article presents an active human-following control of the lower limb exoskeleton for gait training. First, to improve safety, considering the human balance, the OpenPose-based visual feedback is used to estimate the individual's pose, then, the active human-following algorithm is proposed for the exoskeleton robot to achieve the body weight support and active human-following. Second, taking the human's intention and voluntary efforts into account, we develop a long short-term memory (LSTM) network to extract surface electromyography (sEMG) to build the estimation model of joints' angles, that is, the multichannel sEMG signals can be correlated with flexion/extension (FE) joints' angles of the human lower limb. Finally, to make the robot motion adapt to the locomotion of subjects under uncertain nonlinear dynamics, an adaptive control strategy is designed to drive the exoskeleton robot to track the desired locomotion trajectories stably. To verify the effectiveness of the proposed control framework, several recruited subjects participated in the experiments. Experimental results show that the proposed joints' angles estimation model based on the LSTM network has a higher estimation accuracy and predicted performance compared with the existing deep neural network, and good simultaneous locomotion tracking performance is achieved by the designed control strategy, which indicates that the proposed control can assist subjects to perform gait training effectively.

Energy scheduling for DoS attack over multi-hop networks: Deep reinforcement learning approach.

This paper studies the energy scheduling for Denial-of-Service (DoS) attack against remote state estimation over multi-hop networks. A smart sensor observes a dynamic system, and transmits its local state estimate to a remote estimator. Due to the limited communication range of the sensor, some relay nodes are employed to deliver data packets from the sensor to the remote estimator, which constitutes a multi-hop network. To maximize the estimation error covariance with energy constraint, a DoS attacker needs to determine the energy level implemented on each channel. This problem is formulated as an associated Markov decision process (MDP), and the existence of an optimal deterministic and stationary policy (DSP) is proved for the attacker. Besides, a simple threshold structure of the optimal policy is obtained, which significantly reduces the computational complexity. Furthermore, an up-to-date deep reinforcement learning (DRL) algorithm, dueling double Q-network (D3QN), is introduced to approximate the optimal policy. Finally, a simulation example illustrates the developed results and verifies the effectiveness of D3QN for optimal DoS attack energy scheduling.

Modeling and tracking control of dielectric elastomer actuators based on fractional calculus.

Dielectric elastomer actuators (DEAs) show broad application prospects in the area of soft robots since they offer merits of fast response, large deformation, light weight and high energy conversion efficiency. Practical soft robot applications would usually require the study on the modeling and control of the DEA. However, the DEA has a memory property, which results in a highly nonlinear characteristics, bringing difficulties to the subject. To address this issue, an effective strategy is the utilization of the fractional order model, which is a type of modeling approach that can accurately characterize the memory property of a material with a small amount of parameters. Meanwhile, the fractional order controller can better handler the memory property, and it owns a better flexibility than traditional integer order controllers. With the above considerations, this paper proposes a modeling strategy and a tracking control strategy for the DEA on the basis of the fractional calculus. In the proposed strategy, a fractional order model is established to characterize the complicated nonlinear characteristics of the DEA. Then, to facilitate the computer simulation, the Oustaloup filter is used to construct an integer order approximation model (IOAM) of the fractional order model. Since the IOAM is difficult to be employed in the system controller design due to its high order, the IOAM is further simplified into a reduced order model based on the square root balance truncation algorithm. To realize the high accuracy control of the DEA, a feedforward-feedback combined controller is devised, which is composed of a feedforward controller and a fractional order proportional integral feedback controller (FOPIFC). Among which, the feedforward controller is devised based on the analytical inverse of the reduced order model to compensate the complicated nonlinear characteristics of the DEA, and the FOPIFC is devised to handle the bad influence from the modeling error and uncertainties on the control performance. Based on the proposed strategy, control experiment was conducted, and the root-mean-square errors in experiment are all below 0.7%, indicating the superiority of the presented modeling and tracking control strategies.

On convergence of extended state observers for nonlinear systems with non-differentiable uncertainties.

The analysis of convergence of extended state observers (ESOs) requires the total disturbance to be differentiable. However, this requirement is not satisfied in many control engineering practices. In this paper, we attempt to analyze the convergence of ESOs for nonlinear systems with non-differentiable uncertainties. A decomposition method is first presented to divide the non-differentiable total disturbance into a differentiable signal and a bounded but non-differentiable signal. Based on this decomposition, we give out the convergence of both nonlinear and linear ESOs (NLESO/LESO), low- and high-power ESOs (LPESO/HPESO), and fixed-time ESO (FxESO). We also derive the explicit formulas for the estimation errors of these ESOs. Simulations and experiments demonstrate the correctness of the analysis results.

Modeling Based on a Two-Step Parameter Identification Strategy for Liquid Crystal Elastomer Actuator Considering Dynamic Phase Transition Process.

Liquid crystal elastomer (LCE) is a promising candidate for actuation in light-driven soft robot applications. Due to the fact that LCE has complex hysteretic nonlinearities, which are highly dependent on the environment, modeling of actuators made of LCE is a very challenging issue. In this article, a model is proposed to describe the deformation of the LCE actuator accurately and analytically by considering the dynamic phase transition process of LCE molecules. First, an overview of the physical process of LCE's deformation is presented, and the schematic of the LCE actuator, as well as the modeling scheme are then introduced. Next, a thermodynamic analysis of the system's free energy is performed to establish the model for the LCE actuator, which gives the relationship between the system's deformation and the temperature. Here, to describe the complex hysteretic nonlinearity in the model, the dynamic process of the phase transition of LCE molecules is exploited. To effectively identify the model parameters, a two-step parameter identification strategy based on the differential evolution algorithm and nonlinear least-squares method is utilized. Finally, experimental results verify the validity of the proposed model. This modeling provides an approach to describe LCE's deformation with high accuracy and can fully reflect the physical nature of LCE's deformation, especially hysteresis. It can be utilized as a basis for accurate control over LCE actuators in photoresponsive soft robot applications.

Guaranteeing Global Stability for Neuro-Adaptive Control of Unknown Pure-Feedback Nonaffine Systems via Barrier Functions.

Most existing approximation-based adaptive control (AAC) approaches for unknown pure-feedback nonaffine systems retain a dilemma that all closed-loop signals are semiglobally uniformly bounded (SGUB) rather than globally uniformly bounded (GUB). To achieve the GUB stability result, this article presents a neuro-adaptive backstepping control approach by blending the mean value theorem (MVT), the barrier Lyapunov functions (BLFs), and the technique of neural approximation. Specifically, we first resort the MVT to acquire the intermediate and actual control inputs from the nonaffine structures directly. Then, neural networks (NNs) are adopted to approximate the unknown nonlinear functions, in which the compact sets for maintaining the approximation capabilities of NNs are predetermined actively through the BLFs. It is shown that, with the developed neuro-adaptive control scheme, global stability of the resulting closed-loop system is ensured. Simulations are conducted to verify and clarify the developed approach.

A retrospective study of hip posterior fracture-dislocation: closed reduction at the emergency department or in the operation theater?

BACKGROUND: For hip posterior fracture-dislocation, the current consensus is to perform joint reduction within 6 h to prevent sequelae. However, whether a closed reduction (CR) should be performed at the emergency department (ED) or in the operation theater (OT) remains debatable. We aimed to assess the incidence and factors predictive of CR failure at the ED in patients with hip posterior fracture-dislocation. METHODS: Patients with hip posterior fracture-dislocation between 2009 and 2019 were included. Age, sex, body mass index (BMI), injury severity score, new injury severity score, time from injury to first reduction attempt (TIR), presence of associated femoral head fracture, posterior wall marginal impaction, and posterior wall fragment size were compared between patients with CR success and patients with CR failure at the ED. RESULTS: Fifty-five patients with hip posterior fracture-dislocation experienced CR attempts at the ED and were enrolled in the study. Thirty-eight (69.1%) hips were reduced successfully at the ED, and 17 (30.9%) experienced failure. No significant differences in age, sex, BMI, presence of femoral head fracture, marginal impaction, or size of the posterior wall fragment were found between the groups. TIR was significantly shorter in the successful CR group (2.24 vs. 4.11 h, p = 0.01). According to receiver operating characteristic curve analysis, 3.5 h was the cut-off time. CONCLUSIONS: For patients with hip posterior fracture-dislocation, TIR was a critical factor for successful CR. If the time interval exceeds 3.5 h from injury, the success rate of bedside CR at the ER is likely to decrease, and the OT should be prepared in case of failed bedside CR.

Influence of associated femoral head fractures on surgical outcomes following osteosynthesis in posterior wall acetabular fractures.

BACKGROUND: To date, no study has compared the surgical outcomes between posterior wall acetabular fractures with and without associated femoral head fractures. Therefore, we evaluated whether an associated femoral head fracture increases the incidence of fracture sequelae, including post-traumatic osteoarthritis (PTOA) and osteonecrosis of the femoral head (ONFH), following osteosynthesis for posterior wall acetabular fractures. METHODS: This retrospective clinical study enrolled 183 patients who underwent osteosynthesis for posterior wall acetabular fractures between 2009 and 2019 at a level-1 trauma center. The incidence of PTOA, ONFH, and conversion to total hip arthroplasty (THA) was reviewed. RESULTS: The incidence of PTOA, ONFH, and conversion to THA following osteosynthesis were 20.2%, 15.9%, and 17.5%, respectively. The average time for conversion to THA was 18.76 ± 20.15 months (range, 1-82). The results for the comparison of patients with associated femoral head fractures and isolated posterior wall acetabular fractures were insignificant (PTOA: 27.3% vs. 15.7%, p = 0.13; ONFH: 18.2% vs. 14.3%, p = 0.58; conversion to THA: 20.4% vs. 15.7%, p = 0.52). Upon evaluating other variables, only marginal impaction negatively affected ONFH incidence (odds ratio: 2.90). CONCLUSIONS: Our methods failed to demonstrate a significant difference in the rate of PTOA, ONFH, or conversion to THA in posterior wall acetabular fractures with and without an associated femoral head fracture. Beyond femoral head fractures, the marginal impaction of the acetabulum could have led to early sequelae. LEVEL OF EVIDENCE: Level III.

Refined Fractional-Order Fault-Tolerant Coordinated Tracking Control of Networked Fixed-Wing UAVs Against Faults and Communication Delays via Double Recurrent Perturbation FNNs.

This article investigates the fault-tolerant coordinated tracking control problem for networked fixed-wing unmanned aerial vehicles (UAVs) against faults and communication delays. By supplementing the commonly used Gaussian functions in the fuzzy neural networks (FNNs) with sine-cosine functions and constructing two kinds of recurrent loops within the FNN architecture, double recurrent perturbation FNNs are cleverly designed to learn the unknown terms containing faults and uncertainties. Then, adaptive laws are designed for double recurrent perturbation FNNs. Moreover, by assimilating fractional-order calculus into the sliding-mode surfaces and the control signals, refined transient-state and steady-state adjustment performances can be obtained. It is shown by Lyapunov stability analysis that all fixed-wing UAVs can coordinately track their desired trajectories and the tracking errors are uniformly ultimately bounded. Comparative simulation results are provided to show the effectiveness of the proposed control strategy.

Fat Embolism Syndrome and in-Hospital Mortality Rates According to Patient Age: A Large Nationwide Retrospective Study.

Introduction: Fat embolism syndrome (FES) is a rare life-threatening condition that can develop after traumatic orthopedic injuries. Controversy remains concerning the epidemiology in the elderly population. Therefore, this study aims to report FES related to in-hospital mortality stratified by age. Methods: A retrospective trauma cohort study was conducted using data from the National Trauma Data Bank (NTDB) from 2007 to 2014. All FES cases were included in the study with the diagnosis of FES (ICD9 958.1). Death on arrival cases were excluded. Patients were stratified by age cohort: less than 40 (G1), 40-64 (G2), and greater than 65 (G3) years of age. The primary outcome evaluated was in-hospital mortality. Multivariable regression models were performed to adjust for potential confounders. Results: Between 2007 and 2014, 451 people from a total of 5,836,499 trauma patients in the NTDB met the inclusion criteria. The incidence rate was 8 out of 100,000. The inpatient mortality rate was 11.8% for all subjects with the highest mortality rate of 17.6% in patients over 65. Multivariable analyses demonstrated that age greater than 65 years was an independent predictor of mortality (aOR 24.16, 95% CI 3.73, 156.59, p=0.001), despite higher incidence and injury severity of FES among patients less than 40. No significant association with length of hospital stay, length of intensive unit care, or length of ventilation use was found between the groups. Subgroup analysis of the elderly population also showed a higher mortality rate for FES in femoral neck fracture patients (18%) than other femoral fractures (14%). Conclusion: In this retrospective cohort analysis, old age (≥ 65 years) was found to be an independent risk factor for in-hospital mortality among fat embolism syndrome patients. Elderly patients specifically with femoral neck fractures should be monitored for the development of FES.