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.

Postoperative Reduction Quality May Be the Most Important Factor That Causes Worse Functional Outcomes in Open and Closed Pelvic Fractures.

BACKGROUND: Data on the functional outcomes of patients with open pelvic fractures after osteosynthesis are limited, and whether open fracture is a risk factor for worse outcomes, as compared with closed fracture, remains unclear. This study aimed to compare the functional outcomes of patients with open and closed pelvic fractures and evaluate potential factors that might affect outcomes. METHODS: Overall, 19 consecutive patients with open pelvic fractures and 78 patients with closed pelvic fractures between January 2014 and June 2018 were retrospectively reviewed. All fractures were surgically treated, with a minimal follow-up period of three years. Patients' demographic profile, associated injuries, management protocol, quality of reduction, and outcomes were recorded and analyzed. RESULTS: Patients with open pelvic fractures had higher new injury severity score, higher incidence of diverting colostomy, and longer length of stay. Both radiological and functional evaluations revealed no significant differences between the two groups at 1-year and 3-year evaluations. Multiple logistic regression analysis identified poor radiological outcomes (using Lefaivre criteria) and longer length of stay as risk factors for worse short-term functional outcomes. At 3-year evaluation, fair-to-poor radiological outcomes (using Matta/Tornetta and Lefaivre criteria) and the presence of diverting colostomy were potential risk factors. CONCLUSIONS: Compared with closed pelvic fracture, open pelvic fracture was not an indicator of worse functional outcomes. Functional outcomes may be comparable between patients with open and closed pelvic fractures at different time points within three years postoperatively. Achieving anatomical reduction in a fracture is crucial, because it might affect patient satisfaction.

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.

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.

Trauma Center Outcomes After Transition From Level 2 to Level 1: A National Trauma Data Bank Analysis.

BACKGROUND: Previous US-based studies have shown that a trauma center designation of level 1 is associated with improved patient outcomes. However, most studies are cross-sectional, focus on volume-related issues and are direct comparisons between levels. This study investigates the change in patient characteristics when individual trauma centers transition from level 2 to level 1 and whether the patients have similar outcomes during the initial period of the transition. STUDY DESIGN: We performed a retrospective cohort study that analyzed hospital and patient records included in the National Trauma Data Bank from 2007 to 2016. Patient characteristics were compared before and after their hospitals transitioned their trauma level. Mortality; complications including acute kidney injury, acute respiratory distress syndrome, cardiac arrest with CPR, deep surgical site infection, deep vein thrombosis, extremity compartment syndrome, surgical site infection, osteomyelitis, pulmonary embolism, and so on; ICU admission; ventilation use; unplanned returns to the OR; unplanned ICU transfers; unplanned intubations; and lengths of stay were obtained following propensity score matching, comparing posttransition years with the last pretransition year. RESULTS: Sixteen trauma centers transitioned from level 2 to level 1 between 2007 and 2016. One was excluded due to missing data. After transition, patient characteristics showed differences in the distribution of race, comorbidities, insurance status, injury severity scores, injury mechanisms, and injury type. After propensity score matching, patients treated in a trauma center after transition from level 2 to 1 required significantly fewer ICU admissions and had lower complication rates. However, significantly more unplanned intubations, unplanned returns to the OR, unplanned ICU transfers, ventilation use, surgical site infections, pneumonia, and urinary tract infections and higher mortality were reported after the transition. CONCLUSIONS: Trauma centers that transitioned from level 2 to level 1 had lower overall complications, with fewer patients requiring ICU admission. However, higher mortality and more surgical site infections, pneumonia, urinary tract infections, unplanned intubations, and unplanned ICU transfers were reported after the transition. These findings may have significant implications in the planning of trauma systems for administrators and healthcare leaders.

Surgical outcomes of elderly patients aged more than 80 years with distal radius fracture: comparison of external fixation and locking plate.

BACKGROUND: To compare the outcomes after surgical intervention, including external fixation (EF) with the optional addition of K-pins or open reduction and internal fixation (ORIF) with a volar locking plate (VLP), in patients with distal radius fracture aged > 80 years. METHODS: We reviewed 69 patients with a distal radius fracture aged > 80 years who treated under surgical intervention from 2011 to 2017 retrospectively. Their demographic data and complications were recorded. Preoperative, postoperative, and last follow-up plain films were analyzed. The functional outcomes of wrist range of motion were also evaluated. RESULTS: 41 patients were treated with EF with the optional addition of K-pins, while 28 patients were treated with ORIF with a VLP. The radiological parameters, including ulnar variance and radial inclination, at the last follow-up were significantly more acceptable in the VLP group (p = 0.01, p = 0.03, respectively). The forearm supination was significantly better in patients treated with VLP (p = 0.002). The overall incidence of complications was lower in the VLP group (p = 0.003). CONCLUSION: VLP provides better radiological outcomes, wrist supination and lower complication rates than EF. Therefore, although EF is still widely used because of its acceptable results and easy application, we recommend VLP as a suitable treatment option for distal radius fracture in the geriatric population aged > 80 years.

High incidence of surgical site infection may be related to suboptimal case selection for non-selective arterial embolization during resuscitation of patients with pelvic fractures: a retrospective study.

BACKGROUND: In most institutions, arterial embolization (AE) remains a standard procedure to achieve hemostasis during the resuscitation of patients with pelvic fractures. However, the actual benefits of AE are controversial. In this study, we aimed to explore AE-related outcomes following resuscitation at our center and to assess the predictive value of contrast extravasation (CE) during computed tomography (CT) for patients with hemodynamically unstable closed pelvic fractures. METHODS: We retrospectively reviewed data from patients who were treated for closed pelvic fractures at a single center between 2014 and 2017. Data regarding the AE and clinical parameters were analyzed to determine whether poor outcomes could be predicted. RESULTS: During the study period, 545 patients were treated for closed pelvic fractures, including 131 patients who underwent angiography and 129 patients who underwent AE. Nonselective bilateral internal iliac artery embolization (nBIIAE) was the major AE strategy (74%). Relative to the non-AE group, the AE group had higher values for injury severity score, shock at hospital arrival, and unstable fracture patterns. The AE group was also more likely to require osteosynthesis and develop surgical site infections (SSIs). Fourteen patients (10.9%) experienced late complications following the AE intervention, including 3 men who had impotence at the 12-month follow-up visit and 11 patients who developed SSIs after undergoing AE and osteosynthesis (incidence of SSI: 11/75 patients, 14.7%). Nine of the 11 patients who developed SSI after AE had undergone nBIIAE. The positive predictive value of CE during CT was 29.6%, with a negative predictive value of 91.3%. Relative to patients with identifiable CE, patients without identifiable CE during CT had a higher mortality rate (30.0% vs. 11.0%, p = 0.03). CONCLUSION: Performing AE for pelvic fracture-related hemorrhage may not be best practice for patients with no CE detected during CT or for unstable patients who do not respond to resuscitation after exclusion of other sources of hemorrhage. Given the high incidence of SSI following nBIIAE, this procedure should be selected with care. Given their high mortality rate, patients without CE during imaging might be considered for other hemostasis procedures, such as preperitoneal pelvic packing.

Surgical outcome of atypical subtrochanteric and femoral fracture related to bisphosphonates use in osteoporotic patients with or without teriparatide treatment.

BACKGROUND: Atypical subtrochanteric fracture and femoral fracture have been considered to be rare complications related to long-term bisphosphonates use. A reduced bone turnover rate may lead to delayed bone healing. Limited data have revealed that teriparatide treatment may reverse the effect of bisphosphonates and be effective in bone healing. METHODS: We reviewed patients with atypical subtrochanteric and femoral fracture related to bisphosphonates use between January 2008 and December 2014. Thirteen female patients were enrolled. Radiographic findings were compatible with the characteristics of atypical fracture. Surgical intervention was performed for all, and teriparatide use was advised postoperatively. Outcome measures included perioperative results, and clinical and radiographic outcome. RESULTS: Of the 13 female patients enrolled, 10 had subtrochanteric and 6 had proximal femoral fracture; 3 had bilateral fractures. The mean age of the patients at surgery was 70.15±6.36 years. Most fractures (68.8%) presented prodromal thigh pain. All patients were treated with an intramedullary fixation system without severe complications. The patients were divided into 2 groups based on whether they had received treatment with teriparatide or not. The mean time to bone union was 4.4 months in the teriparatide-treated group, and 6.2 months in the non-teriparatide-treated group (p=0.116). Six patients (75%) in the teriparatide-treated group and 4 (50%) in the non-teriparatide-treated group (p= 0.3) achieved bone union within 6 months. The means of the modified Harris Hip Score and Numerical Rating Scale were significantly better in the teriparatide-treated group at postoperative 6 months. Seven patients had the same ability to walk at the 1-year follow-up as they did before the atypical fracture. CONCLUSIONS: Teriparatide treatment in patients with atypical fracture may help in fracture healing, hip function recovery, and pain relief in this reduced bone turnover patient group.

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.

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.

Adaptive Neural Control for Hysteretic Nonlinear Systems With Hysteresis Neural Direct Inverse Compensator and Its Application.

Aiming at high precision control for a class of hysteretic nonlinear systems, a new hysteresis direct inverse compensator-based adaptive output feedback control scheme is designed in this article. First, a novel long short-term memory neural network (LSTMNN)-based hysteresis inverse compensator is established to compensate the asymmetric hysteresis nonlinearity, where the LSTMNN is used as the prediction mechanism for model operator weights, rather than the overall mapping of hysteresis input and output. Second, by designing the modified high-gain K -Filter states observer and the error transformed function, the unmeasurable states are estimated with arbitrarily small estimation error and the prespecified tracking performance is achieved. Lastly, the biconical dielectric elastomer actuator (DEA) motion platform is constructed. Then, the effectiveness of the proposed LSTMNN-based hysteresis inverse compensator and control scheme are verified on the experimental platform. The experimental results illustrate the effectiveness and advantages of proposed control scheme.

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.

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.

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.

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.

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.