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The physics-informed neural network (PINN) is an effective alternative method for solving differential equations that do not require grid partitioning, making it easy to implement. In this study, using automatic differentiation techniques, the PINN method is employed to solve differential equations by embedding prior physical information, such as boundary and initial conditions, into the loss function. The differential equation solution is obtained by minimizing the loss function. The PINN method is trained using the Adam algorithm, taking the differential equations of motion in structural dynamics as an example. The time sample set generated by the Sobol sequence is used as the input, while the displacement is considered the output. The initial conditions are incorporated into the loss function as penalty terms using automatic differentiation techniques. The effectiveness of the proposed method is validated through the numerical analysis of a two-degree-of-freedom system, a four-story frame structure, and a cantilever beam. The study also explores the impact of the input samples, the activation functions, the weight coefficients of the loss function, and the width and depth of the neural network on the PINN predictions. The results demonstrate that the PINN method effectively solves the differential equations of motion of damped systems. It is a general approach for solving differential equations of motion. [ABSTRACT FROM AUTHOR]

Based on the semi-active suspension controller of an automobile, the control law can be adjusted based on the control law reorganization idea, and the active fault-tolerant controller of the semi-active suspension is designed to make the fault closed loop system and the fault-free suspension semi-active suspension. Active suspension closed-loop systems have the same closed-loop pole or proximity system performance. Bench test and simulation results show that: the fault suspension under the control of the active fault-tolerant controller lags behind its performance level after some time and can quickly recover to the same performance as the fault-free automotive semi-active suspension level. And the simulation test and bench test results are basically consistent. Based on the concept of control law reorganization to design the active fault-tolerant control strategy of semi-active suspension, it can effectively realize the active fault-tolerant control of the semi-active suspension of the vehicle to improve the suspension control quality and reliability, and optimize the suspension design.

Hyperentangled state analysis is an important module in high-capacity quantum communication. We present a self-assisted deterministic hyperentangled-Bell-state analysis (HBSA) scheme for photon system entangled in three degrees of freedom (DOFs), where 64 polarizationdouble longitudinal momentum hyperentangled Bell states are completely distinguished. In this HBSA scheme, the four first longitudinal momentum Bell states are distinguished determinately by nondestructive first longitudinal momentum Bell state analyzer, which is constructed with crossKerr nonlinearity medium. The 16 second longitudinal momentum-polarization hyperentangled Bell states are distinguished determinately by self-assisted second longitudinal momentum-polarization hyperentangled Bell state analyzer using linear optical elements, where the first longitudinal momentum Bell state and time-bin entangled state are used as auxiliary. Using this self-assisted method, the application of nonlinear optical resource in HBSA scheme has been largely reduced, which makes this self-assisted deterministic HBSA scheme has potential application prospects in highcapacity quantum communication. [ABSTRACT FROM AUTHOR]

The physics-informed neural network (PINN) is an effective alternative method for solving differential equations that do not require grid partitioning, making it easy to implement. In this study, using automatic differentiation techniques, the PINN method is employed to solve differential equations by embedding prior physical information, such as boundary and initial conditions, into the loss function. The differential equation solution is obtained by minimizing the loss function. The PINN method is trained using the Adam algorithm, taking the differential equations of motion in structural dynamics as an example. The time sample set generated by the Sobol sequence is used as the input, while the displacement is considered the output. The initial conditions are incorporated into the loss function as penalty terms using automatic differentiation techniques. The effectiveness of the proposed method is validated through the numerical analysis of a two-degree-of-freedom system, a four-story frame structure, and a cantilever beam. The study also explores the impact of the input samples, the activation functions, the weight coefficients of the loss function, and the width and depth of the neural network on the PINN predictions. The results demonstrate that the PINN method effectively solves the differential equations of motion of damped systems. It is a general approach for solving differential equations of motion.

Dielectric elastomer actuators (DEAs) offer robust, high-energy-density solutions for soft robotics. The proposed end effector consists of three spring roll configuration DEAs, each acting as a robotic finger, using a 3M VHB-F9473PC adhesive membrane. Spring roll DEAs can be designed to achieve highly specialised actuations depending on the electrode patterning and structural supports. This allows a spring roll DEA-based soft end effector to be tailor-made by simply altering the electrode patterning. The lateral force, bending angle and response time of the actuator are measured experimentally and compared with the predictions of an analytical model. The cylindrical actuator measures 70 mm in length and 15 mm in diameter and achieves a lateral force of 30 mN, a bending angle of 6.8° and a response time of ≈ 1 s. Spring roll configuration DEAs are shown to reduce the effects of viscoelasticity seen in the membrane, making the actuator more controllable at higher voltages. The dielectric constant of the membrane is shown to be a limiting factor of actuation, with a decrease in dielectric constant resulting in larger actuation. The end effector successfully grips numerous light objects for extended periods, showing the applicability of spring roll DEAs for soft end effectors. [ABSTRACT FROM AUTHOR]

The maglev planar motor is one of the most promising industrial applications. The planar motor can increase flexibility in modern manufacturing with the multidirectional motion of the mover. In levitation control, the decoupling matrix is used to decouple the strong cross-coupling effect. The Lorentz force-based wrench matrices can be precomputed and stored in the lookup table. However, the motion range is restricted by the data range. This paper presents a wrench–current decoupling strategy to extend the use of small lookup data for long-range planar motion. The horizontal data range is 40 mm by 40 mm, which is determined from the minimally repetitive area of the planar coil array. The quadrant symmetry transformation is used to estimate the data for other areas. The experiment results demonstrated the accomplishment of the developed technique for long-range motion with a maximum motion stroke of 380 mm. The disc-magnet movers can levitate with a large air gap of 30 mm and have a total roll and pitch rotation range of 20 degrees. [ABSTRACT FROM AUTHOR]

[Display omitted] The compound eyes of the dragonfly, Pantala flavescens Fabricius, are covered by micro-scaled ocelli capable of sensing polarized light, an attractive property for radar stealth and counterreconnaissance. In this work, we fabricated biomimetic electromagnetic wave absorption materials (EAMs) by analyzing the covert information identifications of biological systems and focusing on the design of metastructures and microstructures. Several bionic metasurfaces with anisotropic double-V meta atoms made up of (FeCoNiSi 8.9 Al 8.9)C 0.2 high-entropy-alloy (HEA) ribbons for multiple-degrees-of-freedom recognition and broadband absorption are presented. The covert phase, amplitude, and angular momentum of electromagnetic waves were controlled and recognized as information by manipulating the rotation angle θ of meta atoms. A vortex wave with a topological charge of 1 was generated to recognize linearly polarization and left- and right-handed circular polarization. In addition, the polarization conversion enhanced absorption. The hierarchical nanostructures of HEA ribbons give rise to suitable electromagnetic loss and a superior impedance match. Finally, inspired by the structure of compound eyes, the designed multilayer metamaterials realized effective absorption (reflection loss (RL) ≤ − 10 dB) within the 4.5–18 GHz regime under 2.8 mm thickness. These materials provide evidence for a new way for integrated EAMs and metamaterials. [ABSTRACT FROM AUTHOR]

Dielectric elastomer actuators (DEAs) offer robust, high-energy-density solutions for soft robotics. The proposed end effector consists of three spring roll configuration DEAs, each acting as a robotic finger, using a 3M VHB-F9473PC adhesive membrane. Spring roll DEAs can be designed to achieve highly specialised actuations depending on the electrode patterning and structural supports. This allows a spring roll DEA-based soft end effector to be tailor-made by simply altering the electrode patterning. The lateral force, bending angle and response time of the actuator are measured experimentally and compared with the predictions of an analytical model. The cylindrical actuator measures 70 mm in length and 15 mm in diameter and achieves a lateral force of 30 mN, a bending angle of 6.8° and a response time of ≈1 s. Spring roll configuration DEAs are shown to reduce the effects of viscoelasticity seen in the membrane, making the actuator more controllable at higher voltages. The dielectric constant of the membrane is shown to be a limiting factor of actuation, with a decrease in dielectric constant resulting in larger actuation. The end effector successfully grips numerous light objects for extended periods, showing the applicability of spring roll DEAs for soft end effectors.

The maglev planar motor is one of the most promising industrial applications. The planar motor can increase flexibility in modern manufacturing with the multidirectional motion of the mover. In levitation control, the decoupling matrix is used to decouple the strong cross-coupling effect. The Lorentz force-based wrench matrices can be precomputed and stored in the lookup table. However, the motion range is restricted by the data range. This paper presents a wrench–current decoupling strategy to extend the use of small lookup data for long-range planar motion. The horizontal data range is 40 mm by 40 mm, which is determined from the minimally repetitive area of the planar coil array. The quadrant symmetry transformation is used to estimate the data for other areas. The experiment results demonstrated the accomplishment of the developed technique for long-range motion with a maximum motion stroke of 380 mm. The disc-magnet movers can levitate with a large air gap of 30 mm and have a total roll and pitch rotation range of 20 degrees.

Hyperentangled state analysis is an important module in high-capacity quantum communication. We present a self-assisted deterministic hyperentangled-Bell-state analysis (HBSA) scheme for photon system entangled in three degrees of freedom (DOFs), where 64 polarizationdouble longitudinal momentum hyperentangled Bell states are completely distinguished. In this HBSA scheme, the four first longitudinal momentum Bell states are distinguished determinately by nondestructive first longitudinal momentum Bell state analyzer, which is constructed with cross-Kerr nonlinearity medium. The 16 second longitudinal momentum-polarization hyperentangled Bell states are distinguished determinately by self-assisted second longitudinal momentum-polarization hyperentangled Bell state analyzer using linear optical elements, where the first longitudinal momentum Bell state and time-bin entangled state are used as auxiliary. Using this self-assisted method, the application of nonlinear optical resource in HBSA scheme has been largely reduced, which makes this self-assisted deterministic HBSA scheme has potential application prospects in highcapacity quantum communication. [ABSTRACT FROM AUTHOR]

In traditional wireless power transfer (WPT) system, the output power and efficiency of the system decrease sharply when there is an angular misalignment between the transmitter and receiver. To solve this problem, this paper proposes an omnidirectional WPT system based on the tripolar pad to power up electronic devices, which can realize multiple degrees-of-freedom wireless charging. Firstly, the circuit model of the omnidirectional WPT system based on tripolar pad is established with LCC compensation network, the expression of output power is calculated, and the effect of cross-coupling between transmitting coils on the system is analyzed in detail. Through finite element analysis (FEA) simulation with ANSYS Maxwell, the expression of mutual inductance with rotation angle is fitted, which proves that the output power is independent of the rotation angle. Besides, it is found that the tripolar pad can generate a rotating magnetic field, which enables the receiving coil to pick up magnetic energy under an arbitrary angular misalignment. Then, considering the requirements of practical application, the design method of the proposed omnidirectional WPT system is given. Finally, a 100 W experimental prototype is set up to verify the effectiveness of the proposed WPT system. The output power fluctuation is within ± 8.7%, which verifies that the output power is independent of the rotation angle. [ABSTRACT FROM AUTHOR]

In this study, a moving track tracking method of multi degree of freedom manipulator based on particle filter algorithm is proposed. By constructing the transformation matrix and the Jacobian matrix, the kinematics of the multi degree of freedom manipulator is analyzed. According to the three coordinates of the end of the multi degree of freedom manipulator, the forward kinematics model is solved and the inverse kinematics model is obtained. Particle filter algorithm is adopted to track the moving trajectory of multi degree of freedom manipulator, and the trajectory tracking error is corrected. Experiments show that this method has the advantages of small difference between the trajectory of the multi degree of freedom manipulator and the actual target trajectory, such as high trajectory tracking accuracy and short tracking time, and can meet the requirements of people for the trajectory control accuracy of the joint manipulator. It is expected that this paper can provide valuable references and help for the application field of robots as well as the actual life and production activities. [ABSTRACT FROM AUTHOR]

Parametric resonance has been observed, both numerically and experimentally, in various studies of wave energy converters (WECs). Large heave motions induce a periodic variation in the metacentric height of a WEC body and, consequently, cause a harmonic variation in pitch/roll restoring coefficients, which can parametrically excite the pitch/roll modes. Current studies attempt to determine the onset conditions of parametric resonance, by detecting the boundaries between stable and unstable regions in the parameter space. In the literature, some studies aim to make use of parametric resonance for improving power capture. In contrast, some studies try to suppress the effect of parametric resonance, as it can reduce power capture efficiency in the primary degree of freedom. However, how energy transfers from one mode to another is not fully understood. This study aims to analyse energy transfer between heave and pitch/roll modes when parametric resonance occurs. A generic cylindrical point absorber is studied as a WEC floater to consider non-linear wave-structure interaction, including non-linear Froude-Krylov and viscous forces. A heave-pitch-roll three-degree-of-freedom model is derived for numerical study of the energy transfer between different operational modes.

Encoding computing qubits in multiple degrees of freedom (DOFs) of a photonic system allows hyperparallel quantum computation to enlarge channel capacity with less quantum resource, and constructing high-fidelity hyperparallel quantum gates is always recognized as a fundamental prerequisite for hyperparallel quantum computation. Herein, we propose an approach for implementing a high-fidelity photonic hyperparallel controlled-phase-flip (CPF) gate working with polarization, spatial-mode, and frequency DOFs, through utilizing the practical interaction between the single photon and the diamond nitrogen vacancy (NV) center embedded in the cavity. Particularly, the desired output state of the gate without computation errors coming from the practical interaction is obtained, and the robust fidelity is guaranteed in the nearly realistic condition. Meanwhile, the requirement for the experimental realization of the gate is relaxed. In addition, this approach can be generalized to complete the high-fidelity photonic three-DOF hyperparallel CPFN gate and parity-check gate. These interesting features may make the present scheme have potential for applications in the hyperparallel quantum computation.

This paper introduces the modular design and manufacturing method, mechanical model, and test verification of a new type of soft actuator driven by fluid. First, the modular design scheme and driving principle of omnidirectional bending and elongation of the soft actuator are described. Three print-based elastic air cavities constrained by fire lines are distributed radially inside the actuator. The actuator can complete the 3 DOF motions of omnidirectional bending and elongation. From the basic principle of material mechanics, a novel mechanical model of the soft elastomer actuator is established. By numerically solving the nonlinear model, the relationship between actuator elongation/bending angle and driving pressure is obtained. The theoretical prediction and test results show that the deformation of the actuator exhibits a linear relationship with pressure when the chambers are charged. Additionally, the maximum allowable load force on the actuator terminal also exhibits good linearity when the driving pressure increases. Furthermore, the established mechanical model, which considers gravity effects can more accurately describe the features of bend and elongation of the actuator. The results shows that the proposed model is more convenient than the FEM models. This study provides theoretical support for accurate control of a soft actuator.

The encoding in multiple degrees of freedom can effectively improve the performance of current quantum key distribution, but the collective channel noise reduces the security of these proposals. In this article, we propose a high capacity quantum key distribution with single-photon in polarization and spatial-mode degrees of freedom, and protect the quantum states against the general collective noise by error-rejection in two degrees of freedom and quantum channel multiplexing. The states transmission and measurements in the presented quantum key distribution can be realized deterministically. The security analysis under the intercept-measure-resend eavesdropping and controlled-NOT operation eavesdropping attacks is conducted to verify the security, and the secure key rate analysis proves the efficiency of our proposal. These advantages make our proposal useful in practical quantum communication under current experimental conditions.

Manipulators are widely used in automation equipment or object-oriented grasping and handling. However, the traditional manipulator has the disadvantages of large mass and volume, high joint inertia, and easy to damage the clamping object. A wire-driven manipulator based on compliant curved beam joints is proposed. The manipulator is mainly composed of grasping part, moving part and driving part. The main structure and motion principle of the manipulator are described, and the static analysis of the manipulator is carried out to verify the rationality of the manipulator. [ABSTRACT FROM AUTHOR]

A multiple-degree-of-freedom (multi-DOF) motor can constitute small-sized and lightweight systems capable of performing complicated motions. Furthermore, the prospects for applications to industrial instruments via a direct drive are promising. This study aimed to develop practical multi-DOF motors capable of performing high-power rotary and linear motions using conventional three-phase inverters. A motor that performs rotary and linear motions is proposed. First, a method is presented for installing a salient pole on a needle with magnets. The method facilitates the use of soft magnetic materials with low eddy-current loss as iron cores. This study demonstrated the effectiveness of the salient pole for increasing the electromagnetic force. The model is used to explain the interactive magnetic interference generated by the armature currents for rotational and translation motions. [ABSTRACT FROM AUTHOR]

The optimal cost of a three-qubit Fredkin gate is 5 two-qubit entangling gates, and the overhead climbs to 8 when restricted to controlled-not (CNOT) gates. By harnessing higher-dimensional Hilbert spaces, we reduce the cost of a three-qubit Fredkin gate from 8 CNOTs to 5 nearest-neighbor CNOTs. We also present a construction of an n -control-qubit Fredkin gate with 2 n + 3 CNOTs and 2 n single-qudit operations. Finally, we design deterministic and non-deterministic three-qubit Fredkin gates in photonic architectures. The cost of a non-deterministic three-qubit Fredkin gate is further reduced to 4 nearest-neighbor CNOTs, and the success of such a gate is heralded by a single-photon detector. Our insights bridge the gap between the theoretical lower bound and the current best result for the n -qubit quantum computation.

Human locomotion has been described as being generated by an impulsive (burst-like) excitation of groups of musculotendon units, with timing dependent on the biomechanical goal of the task. Despite this view is supported by many experimental observations on specific locomotion tasks, it is still unknown if the same impulsive controller (i.e. a low-dimensional set of time-delayed excitation primitives) can be used as input drive for large musculoskeletal models across different human locomotor tasks. For this purpose, we extracted, with non-negative matrix factorization, five non-negative factors from a large sample of muscle EMG signals in two healthy subjects during four motor tasks including walking, running, sidestepping, and crossover cutting maneuvers. The extracted non-negative factors were then averaged and parameterized to obtain task-generic Gaussian-shaped impulsive excitation curves or primitives. These were used to drive a subject-specific musculoskeletal model of the human lower extremity. Results showed that the same set of five impulsive excitation primitives could be used to predict the dynamics of 34 musculotendon units and the resulting hip, knee and ankle joint moments (i.e. NRMSE = 0.18±0.08, and R2 = 0.73±0.22 across all tasks and subjects) without substantial loss of accuracy with respect to using experimental EMG recordings (i.e. NRMSE = 0.16±0.07, and R2 = 0.78±0.18 across all tasks and subjects). Results support the hypothesis that dynamically different motor tasks might share similar neuromuscular control strategies. This might have implications in neurorehabilitation technologies such as human-machine interfaces for the torque-driven, proportional control of powered prostheses and orthoses. In this, device control commands (i.e. predicted joint torque) could be derived without direct experimental data but relying on simple parameterized Gaussian-shaped curves, thus decreasing the input drive complexity and the number of needed sensors.

This study describes the first application of a support vector machine (SVM) based scheme for real-time simultaneous and proportional myoelectric control of multiple degrees of freedom (DOFs). Three DOFs including wrist flexion-extension, abduction-adduction and forearm pronation-supination were investigated with 10 able-bodied subjects and two individuals with transradial limb deficiency (LD). A Fitts' law test involving real-time target acquisition tasks was conducted to compare the usability of the SVM-based control system to that of an artificial neural network (ANN) based method. Performance was assessed using the Fitts' law throughput value as well as additional metrics including completion rate, path efficiency and overshoot. The SVM-based approach outperformed the ANN-based system in every performance measure for able-bodied subjects. The SVM outperformed the ANN in path efficiency and throughput with the first LD subject and in throughput with the second LD subject. The superior performance of the SVM-based system appears to be due to its higher estimation accuracy of all DOFs during inactive and low amplitude segments (these periods were frequent during real-time control). Another advantage of the SVM-based method was that it substantially reduced the processing time for both training and real time control. [ABSTRACT FROM AUTHOR]

Human locomotion has been described as being generated by an impulsive (burst-like) excitation of groups of musculotendon units, with timing dependent on the biomechanical goal of the task. Despite this view being supported by many experimental observations on specific locomotion tasks, it is still unknown if the same impulsive controller (i.e., a low-dimensional set of time-delayed excitation primitives) can be used as input drive for large musculoskeletal models across different human locomotion tasks. For this purpose, we extracted, with non-negative matrix factorization, five non-negative factors from a large sample of muscle electromyograms in two healthy subjects during four motor tasks. These included walking, running, sidestepping, and crossover cutting maneuvers. The extracted non-negative factors were then averaged and parameterized to obtain task-generic Gaussian-shaped impulsive excitation curves or primitives. These were used to drive a subject-specific musculoskeletal model of the human lower extremity. Results showed that the same set of five impulsive excitation primitives could be used to predict the dynamics of 34 musculotendon units and the resulting hip, knee and ankle joint moments (i.e., NRMSE = 0.18 ± 0.08, and R2 = 0.73 ± 0.22 across all tasks and subjects) without substantial loss of accuracy with respect to using experimental electromyograms (i.e., NRMSE = 0.16 ± 0.07, and R2 = 0.78 ± 0.18 across all tasks and subjects). Results support the hypothesis that biomechanically different motor tasks might share similar neuromuscular control strategies. This might have implications in neurorehabilitation technologies such as human-machine interfaces for the torque-driven, proportional control of powered prostheses and orthoses. In this, device control commands (i.e., predicted joint torque) could be derived without direct experimental data but relying on simple parameterized Gaussian-shaped curves, thus decreasing the input drive complexity and the number of needed sensors. [ABSTRACT FROM AUTHOR]

A new cascade control program was proposed based on modified internal model control to handle stable, unstable and integrating processes with time delay. The program had totally four controllers of which the secondary loop had two controllers and the primary loop had two controllers. The two secondary loop controllers were designed using IMC technique. They were decoupled completely and could be adjusted independently, which avoided the undesirable influence on performance of the primary controllers. The main controller in the primary loop was devised as a PID using the method of minimum sensitivity, which could guarantee not only the nominal performance but also the robust stability of the system. A setpoint filter was added in the primary loop to improve the tracking performance. All the controllers of the two closed-loops were designed analytically, and could be adjusted and optimized by single parameter respectively. Simulations were carried out on three various processes with time delay, and the results show that the proposed method can provide a better performance of both set-point tracking and disturbance rejection and robustness against parameters perturbation. [ABSTRACT FROM AUTHOR]

Abstract: In a previous article (Ref. [R. Glowinski, L.J. Shiau, Y.M. Kuo, G. Nasser, The numerical simulation of friction constrained motions (I): One degree of freedom models, Applied Mathematics Letters 17 (2004) 801–807]) the authors discussed the application of operator-splitting methods to the time-discretization of those mathematical relations describing the behavior of elasto-dynamical systems with friction, focusing on one-degree of freedom models. The main goal of the present article is to generalize the methodology discussed in Ref. [R. Glowinski, L.J. Shiau, Y.M. Kuo, G. Nasser, The numerical simulation of friction constrained motions (I): One degree of freedom models, Applied Mathematics Letters 17 (2004) 801–807]; there are no conceptual difficulties in doing so, the main issue being the computation of a vector-valued multiplier modeling the friction forces (or part of them). An iterative method allowing the computation of this multiplier will be discussed and the results of numerical experiments will be presented. [Copyright &y& Elsevier]