Flexible Joint Research Articles

Singular Perturbation-Based Adaptive Integral Sliding Mode Control for Flexible Joint Robots

The flexible joint robot (FJR) typically experiences parametric variations, non-linearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This paper proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. Firstly, the underactuated FJR is modelled into two simple second order fast and slow subsystem by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce chattering based on two state observers with no requirements of the velocity and acceleration measurements in the FJR system. Furthermore, an adaptive laws for switching gains are proposed for both slow and fast subsystems in the FJR to remove the requirements of knowing the up-bound of the disturbances and uncertainties. The closed loop stability of not only slow and fast subsystems but also the overall FJR is proved using the Lyapunov theorem. Finally, the simulation and experimental results demonstrate the superiority of proposed control in terms of less tracking error, significant noise suppression, and strong robustness in comparison with existing controllers.

Data-Driven Inverse Kinematics Approximation of a Delta Robot with Stepper Motors

The Delta robot is a parallel robot that is over-actuated and has a highly nonlinear dynamic model, which poses a significant challenge to its control design. The inverse kinematics that maps the motor angles to the position of the end effector is highly nonlinear and extremely important for the control design of the Delta robot. It has been experimentally shown that geometry-based inverse kinematics is not accurate enough to capture the dynamics of the Delta robot due to manufacturing component errors, measurement errors, joint flexibility, backlash, friction, etc. To address this issue, we propose a neural network model to approximate the inverse kinematics of the Delta robot with stepper motors. The neural network model is trained with randomly sampled experimental data and implemented on the hardware in an open-loop control for trajectory tracking. Extensive experimental results show that the neural network model achieves excellent performance in terms of the trajectory tracking of the Delta robot under different operation conditions, and outperforms the geometry-based inverse kinematics model. A critical numerical observation indicates that neural networks trained with the specific trajectory data fall short of anticipated performance due to a lack of data. Conversely, neural networks trained on random experimental data capture the rich dynamics of the Delta robot and are quite robust to model uncertainties compared to geometry-based inverse kinematics.

Enhancing robustness and noise rejection in flexible joint manipulators: an optimized sliding mode controller with enhanced gray wolf optimization for trajectory tracking

The objective of this study is to enhance the performance of a nonlinear three-rigid-link manipulator (RLM) with a focus on trajectory tracking, robustness against disturbances and noises, and adaptability to joint flexibility. To achieve this, we have employed an optimized sliding mode controller with a proportional integral derivative (PID) sliding manifold. The tuning process involves selecting the critical gains of the controller that minimizes the integral time absolute error (ITAE), serving as the objective function (OBJF) to optimize the performance of the robot manipulator. To identify the optimal gains of the controller, we have utilized a new optimization algorithm known as memory enhanced linear population size reduction gray wolf optimization (MELGWO). The efficacy of this algorithm is compared to other existing optimization methods in the literature. Moreover, this research has delved into the impact of joint flexibility on the robot system’s performance. Encouragingly, the results demonstrate that the optimized SMC–PID with MELGWO adaptation can effectively address joint flexibility while maintaining acceptable performance levels.

Mechanical Behavior of Honeybee Forewing with Flexible Resilin Joints and Stripes.

The flexibility of insect wings should be considered in the design of bionic micro flapping-wing aircraft. The honeybee is an ideal biomimetic object because its wings are small and possess a concise vein pattern. In this paper, we focus on resilin, an important flexible factor in honeybees' forewings. Both resilin joints and resilin stripes are considered in the finite element model, and their mechanical behaviors are studied comprehensively. Resilin was found to increase the static deflections in chordwise and spanwise directions by 1.4 times and 1.9 times, respectively. In modal analysis, natural frequencies of the first bending and first torsional modes were found to be decreased significantly-especially the latter, which was reduced from 500 Hz to 217 Hz-in terms of resilin joints and stripes, closely approaching flapping frequency. As a result, the rotational angle amplitude in dynamic responses is remarkable, with an amplification ratio of about six. It was also found that resilin joints and stripes together lead to well-cambered sections and improve the stress concentrations in dynamic deformation. As resilin is widespread in insect wings, the study could help our understanding of the flexible mechanism of wing structure and inspire the development of flexible airfoils.

Inverse identification of cohesive zone parameters for sintered nano-silver joints based on dynamic convolution neural network

The inverse identification of cohesive zone parameters is an important topic in the field of fracture mechanics. In this paper, three data-driven models, including multilayer perceptron (MLP), convolutional neural network (CNN), and dynamic convolutional neural network (DCNN), were presented to predict the cohesive zone parameters of sintered nano-silver end notched flexure (ENF) joints. Based on the construction of experimental and numerical datasets of load versus displacement curves, bilinear cohesive zone model (CZM) parameters of sintered silver joints are adopted as the prediction target. The investigation shows that MLP, CNN, and DCNN are all valid for predicting CZM parameters through load versus displacement curves with reasonable accuracy. However, DCNN has better prediction accuracy and performance than those of CNN and MLP models based on loss analysis, statistical indicator comparison, and K-fold cross-validation. DCNN can be adopted as the suitable surrogate model for CZM parameters inverse identification with high prediction accuracy. Otherwise, DCNN is also not sensitive to the load versus displacement curves data length. However, the computation efficiency of DCNN during the training process is not as high as that of MLP. Those three methods presented in this paper are very hopeful to be adopted for other inverse identifications of CZM parameters for various kinds of adhesive joints.

Sensor fault estimation based on L∞ unknown input observer

Abstract This study investigates the fault estimation problem for a class of Lipschitz non-linear systems with sensor faults and disturbances. An augmented system consisting of system states and sensor faults is constructed to estimate sensor faults by designing an augmented state. A novel L∞ performance index is presented to reduce the influence of disturbances on fault estimation results. An unknown input observer (UIO) is proposed based on the L∞ performance index to achieve an asymptotic estimation of sensor faults. The design conditions of the L∞ UIO are deduced and solved using linear matrix inequalities. The effectiveness of the proposed L∞ UIO and the fault estimation performance are demonstrated via numerical simulations of a single-link flexible joint robot.

The construction of long-acting exendin-4 analog and its hypoglycemic effect in diabetic mice

Exendin-4 is a glucagon-like polypeptide-1 (GLP-1) analog derived from lizard venom, but its short half-life affects drug administration compliance. An anti-HSA nanobody with a smaller size to guide the peptide coupling to Human Serum Albumin(HSA) in vivo may be a feasible strategy for constructing inexpensive, long-acting exendin-4 analogs. For this purpose, a fusion protein (exendin-4-(G4S)3-sdAbHSA), in which a humanized anti-HSA nanobody to the C-terminal of exendin-4 through the (Gly4Ser)3 flexible joint, was constructed. The target gene was designed according to the preferred codons and cloned into expression vector pET21b of Escherichia coli. The fusion protein could be efficiently expressed as a soluble protein, and purified to a purity over 98% by two steps of chromatography columns. In the streptozotocin-induced mouse diabetes model, the purified product had similar hypoglycemic activity as exendin-4, but dropped to the lowest value from 1 to 2 h to more than 8–10 h. The results show that this construction form does not interfere with the binding of exendin-4 to GLP-1 receptor, and can significantly prolong its half-life in vivo. This study has important reference value for constructing long-acting exendin-4 analogs and establishing efficient and green production process.

Dynamic Modeling and Parameter Identification of Double Casing Joints for Aircraft Fuel Pipelines

Double casing joints are flexible pipe joints used for connecting aircraft fuel pipelines, which can compensate for the displacement and corner of the connected pipes and have complex mechanical characteristics. However, it is difficult to use sensors to directly measure the mechanical connection parameters of flexible joints. In this paper, we construct a coupling dynamics model and parameter identification of a double casing joint. Firstly, we analyze the structure and working principle of double-layer casing joints and establish the dynamics model of a single-layer flexible joint based on the transfer matrix method. Then, we deduce the coupling matrix of the inner and outer pipeline according to the deformation coordination conditions combined with matrix dimension extension. We establish the coupling dynamics model of flow–solid coupling of double casing joints. Furthermore, parameters such as equivalent stiffness and damping of each motion of the double casing joint in the casing unit are identified using the force-state mapping (FSM) method, and an analytical solution in the frequency domain under hammering excitation is given by the dynamics model. Finally, the dynamics test bench of the double casing joint for aircraft fuel is set up, and the free mode test of the double casing joint assembly is carried out. The results show that under free boundary hammering excitation, the theoretical and experimental frequency-domain response results are well matched, both obtaining seven main resonance peaks, and the maximum error is 9.45%, which shows the validity of the pipeline dynamics modeling method with a double casing joint.

Acute effect of static stretching on non-muscular tissue stiffness and joint flexibility: a comparative study between older and young men.

Non-muscular tissue stiffness is assumed to have a negative impact on joint flexibility, and a reduction in non-muscular tissue stiffness may be important, especially in older adults. The present study aimed to compare the acute effects of static stretching on non-muscular tissue stiffness between older and young adults and to investigate whether a decrease in tissue stiffness improves joint flexibility. Twenty older (62-83years) and 20 young (21-24years) males participated. Ankle dorsiflexion static stretching (five sets of 90s each) was performed, and before and after stretching, the ankle dorsiflexion range of motion (RoM), passive ankle joint stiffness, and shear wave speed (SWS) (an index of stiffness) of the sciatic nerve, tibial nerve, and posterior thigh fascia were measured. Stretching led to an increase in RoM and a decrease in passive joint stiffness in both groups (P < 0.001) with no significant between-group differences (P ≥ 0.055). The between-group difference in the effect of stretching on SWS was evident only for the sciatic nerve, and a decline in sciatic nerve SWS was only observed in the older adult group (pre-stretching: 2.5 ± 0.3m/s; post-stretching: 2.3 ± 0.4m/s; P = 0.027). A significant positive repeated-measures correlation was observed between the sciatic nerve SWS and passive joint stiffness (P = 0.014, rrm = 0.540). The reduction in sciatic nerve stiffness by stretching was noticeable in older men and led to improved joint flexibility. These findings may provide insight into tissue adaptation by stretching and may be used to explore effective exercises for improving joint flexibility in older adults.

High-Precision Control of Industrial Robot Manipulator Based on Extended Flexible Joint Model

High-precision industrial manipulators are essential components in advanced manufacturing. Model-based feedforward is the key to realizing the high-precision control of industrial robot manipulators. However, traditional feedforward control approaches are based on rigid models or flexible joint models which neglect the elasticities out of the rotational directions and degrade the setpoint precision significantly. To eliminate the effects of elasticities in all directions, a high-precision setpoint feedforward control method is proposed based on the output redefinition of the extended flexible joint model (EFJM). First, the flexible industrial robots are modeled by the EFJM to describe the elasticities in joint rotational directions and out of the rotational directions. Second, the nonminimum-phase EFJM is transformed into a minimum-phase system by using output redefinition. Third, the setpoint control task is transformed from Cartesian space into joint space by trajectory planning based on the EFJM. Third, a universal recursive algorithm is designed to compute the feedforward torque based on the EFJM. Moreover, the computational performance is improved. By compensating the pose errors caused by elasticities in all directions, the proposed method can effectively improve the setpoint control precision. The effectiveness of the proposed method is illustrated by simulation and experimental studies. The experimental results show that the proposed method reduces position errors by more than 65% and the orientation errors by more than 62%.

Automatic vibration control method for grasping end of flexible joint robot

Because flexible robots have flexible components such as reducers, there are problems of accuracy deviation and end vibration in the process of external interference and trajectory tracking. This leads to the proposal of a Sliding Mode Control Approach Based on RBF Neural Network (SMC-RBF) parameter optimization. This method is mainly applied to reduce the end vibration and running position error of flexible robot. Firstly, the Newton-Euler method is used to establish the dynamic model of robot considering joint flexibility. At the same time, the experiment optimizes the Sliding Mode Control (SMC) method through RBF neural network. The experiments verify the control methods of the two-joint flexible robot and the six-joint flexible robot respectively. In the control of two-joint robot, the maximum tracking curve error of SMC is only about 0.25 rad under the interference of pulse signal; And the recovery time is only about 1 s. In the control of 6-joint robot, the maximum error of RBF-sliding mode control method on XYZ axis is 0.7 mm, 0.25 mm and 1.25 mm respectively; The error on three axes is smaller than that of traditional PD control method. The results demonstrate that the tracking error of the improved mode control is small, the chattering phenomenon of the robot system is weakened as well.

Insights into Bending Stiffness Modeling of Elementary Flexure Hinges

Flexure hinges are widely used in mechanical devices, especially for micro- or even nano-scale applications, where conventional joints based on conjugate surfaces prove unsuitable. However, to achieve accurate motion of devices whose joints are flexure hinges, knowledge of stiffness models that correlate applied forces or bending moments with the resulting displacements is required. Nonlinear bending models are typically too complex and difficult to implement. Therefore, it is preferred to use linear models, which admit analytical solutions. The purpose of this paper is to show what is lost in terms of accuracy in reducing a nonlinear bending stiffness model associated with a flexure hinge when simplifications are made to obtain an analytical solution. An analysis of the simplification process leading to a linear stiffness model and its analytical solution is presented. From this study arises an increased awareness of flexure joints in terms of the accuracy obtained with their stiffness models, suggesting important information to the user in choosing the level of complexity required to model them in a specific application. A comparison between analytical and numerical results is provided in the form of maps and tables so as to make that choice as clear as possible.

Distributed robust‐multivariate‐observer‐based FDI attacks estimation for nonlinear multi‐agent systems with directed graphs

AbstractThis article investigates the distributed robust estimation problem for false data injection (FDI) attacks in nonlinear multi‐agent systems with directed graphs. To approximate the realistic attack scenario, the case where both the actuator network channel and sensor network channel suffering from FDIs are considered, and the attack signals contain time‐varying circumstances. A novel distributed robust‐multivariate‐observer (DRMO) strategy is developed such that the online estimation of FDI attack dynamics can be realized with the partially unknown nonlinear dynamics, attack transient increments, and disturbances impact being eliminated. The designed DRMO scheme only depends on the received compromised/uncompromised measurement output information on the account that whole state information cannot be measured directly. Finally, two simulation examples, including a network of four one‐link flexible joint manipulator systems with comparisons to existing methods, are given to show the effectiveness of the proposed scheme.

Preparation of Soft Embalmed Cadavers by the Modified Thiel Embalming Technique for Surgical Skill Training and Development of a Universal Quantitative Scoring System to Assess the Suitability of Soft Embalmed Cadavers for Such Training Purposes.

Background Cadaver dissection plays an important role in learning anatomy. A surgeon must have a thorough knowledge of anatomy of the operating region to perform safe surgery. Skill laboratories give opportunities to surgeons to practice on cadavers before venturing onto real patients. The most common method of cadaver preservation is through formalin fixation. In the process of fixation, formalin destroys the tissue characteristics and also has issues such as smell, eye irritation, hardening of tissue, and risk of carcinogenesis. The Thiel embalming technique and its modifications were developed to address those issues. Our primary objective was to find the benefits of soft embalmed cadavers over formalin-fixed bodies and, secondly, to find out microbial flora in soft embalmed cadavers. Study design This is a basic study. Methods Four cadavers were prepared for the soft embalming purpose for our workshop for surgeons on spine fixation. Due to unavailability, we replaced 4-chloro-3-methylphenol 1% with phenol 1%. The bodies were preserved in refrigerators at 4°C before being used for the workshop purpose. The delegates and faculties were given a questionnaire to assess their experience of the cadavers in terms of odor, irritation, tissue characteristics, joint mobility, and imaging characteristics. The results were calculated using statistical analysis. Swabs were taken from a few of the cadavers for culture to find the organisms. Results There were 14 questions in the questionnaire, and the data collected were divided into two groups, faculties, and delegates. JASP software was used to analyze the data. The questions addressed various aspects of cadavers such as color, odor, tissue pliability, joint flexibility, imaging characteristics, mucosal irritation, and earlier experience in working with cadavers. Cronbach α was used to find the correlation between the various characteristics analyzed. The authors intend to name the domains being measured: surgical suitability (scores of items 8 to 12), imaging suitability (scores of items 5 and 6), and smell score (scores of items 5 and 6). It can be a guide to constructing and refining a better quantitative scale to measure the "quality of soft-embalmed cadavers for surgical training." Conclusions Skill laboratories give opportunities to young surgeons and trainees to learn and improve their skills before applying them to real patients. This was our first attempt to develop soft embalmed cadavers at our center and our state. We used the parent solution with some variations as per the availability of chemicals at our place and found that the features of the preserved cadavers were good and well-suited to address our purpose. Therefore, with some variations in the parent formulations, centers situated in remote and less developed places can formulate their own solution to develop soft embalmed cadavers and establish cadaver skill laboratories. This will benefit the local surgeons and trainees. The authors tried to develop a few domains through statistical analysis, which can be used to assess and compare the quality of cadavers prepared at various centers.

Femtosecond pulse laser-engineered glass flexible structures instrumented with an in-built Bragg grating sensor.

The advent of near-infrared femtosecond pulse laser has enabled the highly-resolved manufacturing of micro/nano structures in various materials including glass. In this paper, we make use of an automated femtosecond laser system, so-called Femtoprint, to design a monolithic self-instrumented mechanism that we use for in-built strain sensing. To that aim, a flexible structure is designed and produced from a silica planar substrate. It has a flexural joint in which an optical waveguide and a Bragg grating have been directly inscribed using femtosecond pulse laser. The latter provides a non-destructive and non-intrusive measurement tool. The axial strain sensitivity of the in-built Bragg grating has been experimentally determined to be 1.22 pm/μ ϵ, while its temperature sensitivity is 10.51 pm/°C. The demonstration of such instrumented glass flexible mechanisms paves the way towards a new class of highly integrated sensors suitable for applications at the microscale or in harsh environments.

Accuracy Analysis and Experimental Study of a Six-Dimensional Force Sensor with Circular Flexible Spherical Joints.

This paper proposed a circular flexible spherical joint to reduce the processing difficulty and manufacturing cost, and design a six-dimensional force sensor based on it. This paper analyzes the influence of the structural parameters of the flexible spherical joints on the accuracy of the six-dimensional force sensor by comparing the force mapping matrix of flexible spherical and ideal spherical joints. As the force mapping matrix is related to the stiffness matrix, the stiffness matrix of a six-dimensional force sensor based on a circular flexible spherical joint and the force mapping matrix of the generalized external force acting on the sensor was derived. Finally, a set of optimal parameters was selected to create a prototype and was verified through finite elements and experiments. The results show that the six-dimensional force sensor with a circular flexible spherical joint has good accuracy and provides some guidance for the design and analysis of the sensor.

Kinematics, dynamics, and control of underwater robotic snake based on a rigid-soft unified model

ABSTRACT With the advancement of underwater biomimetic robots, many kinds of underwater snake robots have been developed to perform various marine inspection and maintenance operations. This paper introduces an innovative biomimetic extension to underwater robotic vehicles, an underwater rigid-soft snake robot, which is operated by a combination of rigid propulsion modules and soft joint modules. The essential point is how to jointly mathematically model soft joints and rigid modules with different physical property. The Constant Curvature assumption is widely used in modeling of soft module robots. However, the limitation of this assumption is that it can't accurately describe the deformation of soft robots when performing dynamic tasks. We propose a methodology, rigid-soft unified model, for kinematic and dynamic modeling by viewing soft joint as flexible universal joint. The motion analysis of the robot under the influence of water flow in different postures is completed. Furthermore, we develop a closed loop hierarchical trajectory controller for the snake robot. Especially in the part of dynamic control system, we compare the tracking performance of different controllers.

Experimental validation of a novel curved steel damper for steel frames with flexible beam-column joints

In this study, results of an experimental program are presented to validate the performance of a novel energy dissipation device (EDD) designed for use in moment-resisting steel frame structures with flexible beam-column connections. The EDD, composed of a curved steel plate, stiffeners, and flanges on both ends, was tested in laboratory conditions using a displacement control quasi-static loading protocol. Three half-scale steel frames were used, one serving as a control and the other two incorporating the device in both column-beam joints. The device was fabricated using two different materials, mild steel, and stainless steel, and the results were compared. The results of the experimental program revealed that the frames equipped with the energy dissipation device performed significantly better than the control frame. This was observed qualitatively, in terms of the amount of damage sustained by the frames, and quantitatively, through measurements of the frames' capacity and displacement ductility. Frames that were equipped with dampers showed an approximately 1.5-fold increase in displacement ductility and an 84–113% increase in cumulative energy dissipation compared to the control frame. Overall, this research highlights the potential of this novel energy dissipation device to enhance the seismic performance of moment-resistance steel frame structures.

Prioritization of transmission and distribution system operator collaboration for improved flexibility provision in energy markets

The effective use of the flexibility sources of transmission and distribution networks necessitates smooth coordination between transmission and distribution system operators (TSO–DSO) as well as proper interfacing between the energy and flexibility markets. In this paper, mathematical centralized/decentralized optimization frameworks of flexibility market structures is proposed for four market mechanisms of a transmission-level centralized market, a local distribution- and centralized transmission-level market, a TSO priority market, and a TSO–DSO price equilibrium market. Further, prioritization mechanisms are developed by allocating ramp flexibilities in multi-interval day-ahead market clearing procedures for the wholesale (transmission level) and local markets (distribution level) to reduce the prediction error and improve the performance of the real-time flexibility market, which is a single-interval optimization market. Accordingly, the concurrent provision of the energy and flexibility requirements of the transmission and distribution networks is explored in a joint energy and flexibility day-ahead market. As a base case, the centralized market model does not prioritize TSO–DSO flexibility. The second market model gives the DSO priority in terms of providing flexibility. The DSO starts by using the resources of the distribution network. It then makes the upstream market an offer for the flexibility capacities of the remaining unused resources. In the third proposed market, the TSO receives priority in providing flexibility. The optimization frameworks proposed for the third market mechanisms are formulated as mixed-integer linear programming models (MILP). In addition, to ensure a higher resilience, a lower complexity of algorithms, and the possibility to better adapt to the efficient flexibility allocation in the TSO/DSO collaboration, an approach of the decentralized alternating direction method of multipliers (ADMM) in the decentralized optimization framework is performed to clear the proposed wholesale market while taking into account the local markets at the distribution level. Finally, to evaluate the proposed multi-level centralized/decentralized optimization frameworks, simulation results are performed on a modified IEEE 30-bus/118-bus transmission network with three/five IEEE 33-node distribution networks connected. In the case studies, various market clearing and prioritization mechanisms are implemented and evaluated through numerical simulations.

Design of a Novel NNs Learning Tracking Controller for Robotic Manipulator with Joints Flexibility

The precise tracking control problem for the robotic manipulator with flexible joints, subjected to system uncertainties and external disturbances, is addressed. A novel control scheme is presented that does not use link velocity measurements and high-order derivatives of the link states. The control scheme employs neural networks-based observers to estimate both motor velocity and link velocity. By using the virtually applied torque, the link controller is designed based on rigid link dynamics, and the motor controller is designed using the dynamic surface control technique. The proposed control scheme can guarantee that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The simulation results confirm our theoretical analysis, and a comparison study demonstrates the advantages of the proposed control scheme compared to the standard DSC method.