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Spherical motors capable of omnidirectional rotations in a ball joint provide a highly dexterous actuator system yet also present great challenges in developing a high-performance regulation and tracking controller due to the complex rotor dynamics. This article presents a complementary H2-H∞(C-H2-H∞) control method for precisely controlling the multidegree of freedom (DOF) orientation of spherical motors in presence of external disturbances as well as model uncertainties and inaccuracies. In order to deal with the tradeoff between the robustness and control performance resulted from conventional control methods, the proposed controller featured with a 2-DOF structure presents an H2 controller for a nominal plant and then complements it with an additional regulator designed in H∞sense to assure robustness. Unlike traditional H∞ or mixed H2and H∞ controller, the H∞regulation is conducted online in accordance with the monitored modeling mismatch in a way that does not adversely degrade the performance delivered by H2 control, hence, improving the conservativeness of the total control performance and leading to significant improvements of tracking accuracy and response time at same time. Both numerical simulations and experiments on a spherical motor testbed are conducted to validate the superior performance of the proposed controller versus conventional control methods. [ABSTRACT FROM AUTHOR]

Motivated by the increased needs of home-based rehabilitation for stroke patients, more and more interest has been drawn towards developing body-fixed sensors for monitoring affected joint motions. Although relatively accurate bone geometries can be obtained by scanning technologies, most human joints are approximated by simple circles and spheres to reduce the highly nonlinear kinematics to a tractable form for motion studies; many human joint-motion sensing challenges remain open. This article presents a novel magnetic tensor sensor (MTS) for noncontact tracing a human joint trajectory and a physics-based measurement model implemented on an artificial neural network (ANN) to account for un-modeled factors. The effects of input configurations and datatypes on measurement accuracy of an MTS/ANN have been numerically investigated with published data and experimentally evaluated on a prototype pantographic exoskeleton worn on a human shank/foot. As demonstrated experimentally, the MTS/ANN system calibrates the sensor intrinsic parameters, accounts for the environmental magnetic effects on the measurements, and can be trained with both offline and user-specific data. [ABSTRACT FROM AUTHOR]

This paper presents a distributed soft contact sensing method based on a sensitivity mapping function, which relates the change in measured voltages to that in the elastomer conductivity due to contact force acting on its surface. The sensitivity-image-based sensing system uses a small number of boundary electrodes with a multiplexer to create different electric-field patterns to generate a series of sensitivity images for machine learning, significantly reducing the number of training data typically obtained with single-point indentation measurements. The mapping function, which does not rely on the knowledge of the electric and conductivity fields during online sensing, can be trained with only a small amount of measured data in the order of the square of electrode number. The proposed method has been experimentally evaluated on two 16-electrode prototypes trained with 129 and 80 data for two typical applications, which are tactile perception on a flat surface and contact force measurement in a model knee joint, respectively. The former verifies the measurement accuracy of the contact position and force magnitude while the latter demonstrates the application of this method for measuring the internal joint forces between two curved surfaces. [ABSTRACT FROM AUTHOR]

This article presents a back-drivable spherical wrist with smart compliance for rendering human wrist-like capabilities in robotic applications. In order to synthetically impose both motion accuracy and active compliance for dedicated wrist manipulations, a robust hybrid control method is proposed that can switch between motion control (at free motion) and impedance control (at interactions with the environment). A sliding manifold is formulated so that when the control law drives the sliding manifold to zero, the motion/impedance errors will automatically converge to bounded regions despite system uncertainties/inaccuracies. Due to the direct-drive configuration of the proposed spherical wrist, the contact torque can be precisely estimated with an observer, providing an intuitive criterion of contact based on which the control modes can switch autonomously without external force/torque sensors and predefined geometric boundaries that are usually required in conventional hybrid force/position control. The concept is validated on a spherical wrist test-bed in the context of a throat swabbing process. The performance of the hybrid motion-impedance control evaluated against conventional impedance and admittance control methods demonstrate that the proposed spherical wrist enables a robotic system with both fine manipulations and smooth compliant interactions in wrist space. [ABSTRACT FROM AUTHOR]

This article presents a model-based eddy current (EC) testing method for the reconstruction of geometrical features, that may be hidden, through, or blind cavity in a large electrically conductive plate. Based on a distributed current source (DCS) modeling method, a perturbation model is formulated to convert the feature reconstruction problem into finding a possibility vector using a finite set of measured magnetic flux density (MFD) data and solved with the Tikhonov regularization method. The proposed method is numerically and experimentally validated and demonstrated by using the specimens with compound conductive/nonconductive geometrical features and comparing them with two published feature detection methods. Parametric studies are conducted to analyze the effects of feature shape, sensor configuration, and multi-coil excitation on reconstruction accuracy. [ABSTRACT FROM AUTHOR]

Undesired oscillations are often encountered in controlled systems at steady state due to high-frequency (HF) periodic disturbance and/or feedback noises. This article presents a computationally efficient alternative to derive an analytical harmonic model (AHM) that expresses the oscillatory variable as a series of harmonic kernel vectors and a position-independent harmonic amplitude vector for identifying the dominant harmonic components of the undesired effects on the manipulated variables. Illustrated in the context of an aircraft pressure-controlled piston pump (PC-PP) where the pressure feedback pulsations and the torque disturbances from the piston/slipper assemblies lead to HF swash-plate (SP) oscillation at steady state, the AHM and its significance were investigated experimentally on a PC-PP test-rig capable of simultaneously measuring the HF feedback pressure and SP-angle. Good agreements between the experimental and numerical results validate the AHM, and reveal that the HF SP-oscillation is dominated by its fundamental harmonic component, and primarily contributed by the disturbance torque. [ABSTRACT FROM AUTHOR]

This article presents an analytical method that offers both spectral and spatial information to predict local electric fields capable of driving neural activities for neuromuscular activation, and the findings of an experimental investigation on a common strategy utilizing multiple high-frequency (HF) electric fields to create an interference to recruit neural firing at depth. By introducing a cut-off frequency ${f} _{\text {cut}}$ too high to recruit neural firing in a frequency-based field descriptor, the analytical method offers an effective means to position a focused temporal interference (TI) without mechanically moving the electrodes. The experiment, which was conducted on both forearms of five healthy volunteers, validates the feasibility of the method for selective neuromuscular stimulation, where three nerve/muscles that control human fingers were independently stimulated with two current channels. The numerical and experimental findings demonstrate that the frequency-based method overcomes several limitations associated with surface-based electrical stimulation. [ABSTRACT FROM AUTHOR]

Loaded walking with a rucksack results in both gravitational and inertial forces of the load that must be borne by human carriers. The inertial force may be the source of metabolic burden and musculoskeletal injuries. This paper presents a lightweight backpack with a disturbance observer-based acceleration control to minimize the inertial force. The backpack was evaluated by seven participants walking on a treadmill at 5 km h−1 with a 19.4 kg load. Three experimental conditions were involved, including walking with a locked load (LOCKED), with an acceleration-controlled load (ACTIVE) using the designed backpack and walking with the same load using a rucksack (RUCKSACK). Our results showed that the ACTIVE condition reduces the load acceleration by 98.5% on average, and reduce the gross metabolic power by 8.0% and 11.0% as compared to LOCKED and RUCKSACK conditions respectively. The results demonstrate that the proposed active backpack can improve the loaded walking economy compared with a conventional rucksack in level-ground walking. [ABSTRACT FROM AUTHOR]

Motivated by the need to incorporate human spine mechanics into the design loop of wearable spine assistive devices, this article presents a spine-equivalent beam (SEB) model for analyzing kinematics and mechanics of a human spine in sagittal standing flexion. The model is capable of handling loads resulted from the head, arms, external payload, torso weight, and back muscle effects, and it also handles pelvis rotation. The derivation of the physiologically equivalent parameters is discussed, including initial curvature, cross-sectional area, area moment of inertia, force/moment of the back muscles, and the equivalent Young's modulus. The SEB model and its equivalent parameters are validated with published in vivo measurement collected by telemeterized implant embedded on subjects who have undergone vertebra body replacement surgery. Results show that the model is capable of predicting flexion angles and compression force experienced by the intervertebral discs throughout the flexion process, which provides a practical yet effective approach to incorporate the spine mechanics into the design of wearable spine assistive devices. [ABSTRACT FROM AUTHOR]

Motivated by the need to develop safe exoskeletons for collocated joint rehabilitation during the early stage of stroke recovery, this article presents a pantographic exoskeleton (PGE) capable of multi-degree-of-freedom motions in a single-joint collocated with the impaired joint. With minimum internal joint reactions in the presence of misalignment, the PGE “traces” the natural joint motion “like a pantograph” in the sagittal plane while performing in-bed rehabilitation, from which the joint parameters can be estimated for subsequent patient-specific motion training. An analytical model is presented to provide a rational basis for designing a collocated human-ankle/PGE mechanism, which has been numerically illustrated. The findings demonstrate that because the PGE joint do not restrict human ankle nature motion within the motion range of a typical ankle, it is less sensitive to joint misalignment as compared to conventional multijoint serial mechanisms that form a closed chain with the human limbs/joint. A prototype PGE has been designed; and its effectiveness for collocated ankle-joint manipulation has been experimentally investigated. Unlike conventional imaging methods that are prone to skin-marker errors and dependent on lumped-parameter approximations, the PGE directly measures the talus trajectory of the ankle-joint for characterizing its roll/slide motion and internal parameters. [ABSTRACT FROM AUTHOR]

In metal cutting, a good understanding of both the elastic-plastic deformation and the mechanical behavior of the workpiece material in the primary shear band (PSB) is essential to optimize machining process and ensure product quality, particularly when machining hard-to-cut materials (such as Titanium alloys) with a low thermal conductivity that gives rise to thermal stress localization near the tool-chip interface. This article presents an extended digital image correlation (DIC) method to obtain the highly intensive and localized elastic-plastic strain and stress fields in the PSB during cutting, the reconstruction of which requires the deformation history of each material point and an appropriate material constitutive model. Unlike existing DIC methods that infer elastic strains from two sequential images, the extended DIC not only reconstructs the displacement field but more importantly also captures the elastoplastic evolution of the material during the dynamic orthogonal cutting process, from which the plastic strain/stress fields in the PSB are determined experimentally. The effectiveness of the extended DIC method was evaluated numerically and experimentally for orthogonal cutting of Ti-6Al-4V alloys. [ABSTRACT FROM AUTHOR]

This paper presents an active control method, consisting of an adaptive sliding-mode controller (ASMC) and a displacement field reconstruction (DFR) method, for chatter suppression in turning of thin-walled workpieces (such as compressor disks and casings in aircraft engines) where low workpiece stiffness renders machining with potential regenerative chatter. Due to the presence of multi-modal dynamics, variant modal parameters, and measurement difficulties, active chatter control of thin plate turning has been challenging. Unlike existing controls based on a lumped-parameter single degree-of-freedom cutting model, a distributed-parameter dynamic model of a rotating thin plate with multiple vibration modes is used to analyze the machining stability with the designed controller. Moreover, model parameters of the plate are not needed to construct the controller. The DFR is employed to capture the plate dynamic behavior for feedback to the ASMC during turning, overcoming the long existing difficulties to measure plate vibration at the cutting point. A fast tool servo is utilized in the control implementation. Theoretical analyses, numerical simulations, and experimental evaluation on a lathe demonstrate that chatter in thin plate turning can be effectively attenuated with the proposed active control method. [ABSTRACT FROM AUTHOR]

This paper presents a new machine perception method based on eddy-current (EC) effects to reconstruct physical fields (EC field, electrical-conductivity field, and hidden geometrical features) of a nonferrous material commonly encountered in intelligent manufacturing using one-time finite magnetic flux density (MFD) measurements. An analytical model for EC testing system with conductor discretization is established and expressed in state-space representation. Two improvements (physical constraints and adaptive element refinement) are developed and integrated into the system model. The measurement models of physical fields using discrete MFD measurements are linearly established, reducing the physical field reconstruction to a linear inverse problem for solving using the Tikhonov regularization method. The EC-based machine perception is numerically illustrated by reconstructing the EC density field, conductivity field, and hidden geometrical features of aluminum plates. Additionally, the effects of element refinement, physical constraints, and sensor configurations on the reconstruction results are analyzed numerically. Using an experimental prototype consisting of an air-cored electromagnet and a two-dimensional (2-D) array of magnetic sensors with associated electronics, the effectiveness of the machine perception method and the accuracy of the reconstructed physical field are demonstrated experimentally. [ABSTRACT FROM AUTHOR]

This paper presents a new method that combines a physics-based model and finite-element (FE) based digital image correlation (DIC) with an interfacial continuity condition for simultaneous deformation measurements of strain field and material mechanical properties. The dual-domain global DIC method incorporates a model-based kernel that offers useful physical insights into the complex deformation and constrains the solutions to the iterative minimization of the DIC criterion, which leads to a faster convergence. Unlike local subset-based and global FE-based methods where the DIC is formulated to solve for the nodal displacements, the model-based DIC that accounts for complex deformation in the specific region is formulated to identify system parameters. Both domains, along with their interface and the continuity condition enforced on the global displacement field, are discretized and solved simultaneously in a single calculation. The dual-domain global DIC method has been investigated by comparing reconstructed strain fields and estimated parameters against targets simulated using the commercial FEA software COMSOL and published experimental data. Unlike FE-DIC which is noise sensitive, the model-based DIC is robust against the Gaussian noise effects. [ABSTRACT FROM AUTHOR]

Modular multiphase (MMP) PM motors have the ability to work continuously under a faulty mode. However, ripples in the spin torque of the motor and unbalanced forces incur rotor vibrations in postfault operations, which seriously degrade the performance of the PM motors. This paper presents a computationally efficient method to derive harmonic models for characterizing the pulsating torque and unbalanced forces of an MMP-PM motor under an open-circuit fault, and the corresponding optimal solutions to its inverse current model to remedy the fault. The model formulation, current harmonic identification, and remedial strategy for suppressing torque ripples and unbalanced forces are illustrated with an MMP-PM motor under an open-circuit fault; both odd and even number of phases are considered. The effectiveness of the harmonic models and remedy strategies are numerically validated with two typical (5- and 6-phase) MMP-PM motors under a one-phase/open- circuit fault and evaluated experimentally on a custom-designed 6-phase duplex motor. [ABSTRACT FROM AUTHOR]

Smart sensing is a prerequisite to information sharing in intelligent manufacturing where online measurements of multiple parameters are essential to infer system properties for process analysis and product-quality control. This paper presents methods to develop a novel eddy-current (EC) sensor capable of simultaneously measuring multiple parameters of a nonferrous electrically conductive workpiece (WP). Unlike traditional EC-sensors that base principles on lumped-parameter impedance or voltage change, the proposed method (referred to here as a multiparameter EC-sensor) directly measures the EC-generated magnetic flux density (MFD) to determine the displacement, thickness, and electrical conductivity of the WP. Specifically, an analytical model that characterizes the impedance and MFD field generated by the induced EC is presented, from which the design criteria for developing a multiparameter EC-sensor are established. The proposed methods, along with a prototype MFD-based EC sensor, have been validated and evaluated experimentally for simultaneous distance and thickness measurements and conductivity estimation of a titanium thin-walled WP in a lathe-turning process. [ABSTRACT FROM AUTHOR]

This paper presents an efficient method, which reconstructs the temperature field around the tool/chip interface from infrared (IR) thermal images, for online monitoring the internal peak temperature of the cutting tool. The tool temperature field is divided into two regions; namely, a far field for solving the heat-transfer coefficient between the tool and ambient temperature, and a near field where an artificial neural network (ANN) is trained to account for the unknown heat variations at the frictional contact interface. Methods to extract physics-based feature points from the IR image as ANN inputs are discussed. The effects of image resolution, feature selection, chip occlusion, contact heat variation, and measurement noises on the estimated contact temperature are analyzed numerically and experimentally. The proposed method has been verified by comparing the ANN-estimated surface temperatures against “true values” experimentally obtained using a high-resolution IR imager on a custom-designed testbed as well as numerically simulated using finite-element analysis. The concept feasibility of the temperature monitoring method is demonstrated on an industrial lathe-turning center with a commercial tool insert. Note to Practitioners—The internal tool-temperature field around the tool/chip interface during cutting offers essential information to monitor tool-wear and ensure surface-quality particularly in finishing cuts, which is difficult to be monitored because of the stringent real-time requirements (including low cost and high accuracy) in harsh working environments. This paper presents a potentially low-cost solution that combines noncontact surface temperature measurements with high-fidelity physics-based computational models for monitoring the internal peak temperature at the tool/chip frictional contact during cutting. This physics-based method requires only a small number of preselected features, and uses thermal isotherms and streamlines to detect and substitute any occlusions in the IR images. The method does not rely on high-resolution (HR) images to infer the steep temperature gradient near the tool-tip where the peak temperature occurs, and thus can be implemented with a relatively low-cost IR imager. Unlike traditional least-square methods that bases solutions to a heat-conduction partial differential equation (PDE), the ANN is trained with precomputed physics-based models based on a novel dual-field (far-field and near-field) approach. The ANN-based method not only eliminates the need to solve the time-demanding PDE in real time, but also effectively accounts for parameter variations due to the uncertain frictional heat-fluxes at the contact interface during cutting. [ABSTRACT FROM AUTHOR]

Machining complex thin-wall components (such as compressor disks and casings in aircraft engines) has been a challenging task, because workpiece deformations and vibrations not only compromise the surface integrity, but also induce residual stresses in the final products. This paper offers a physics-based method that accounts for the damping effects and external loads for reconstructing the dynamic displacement and strain fields of a thin-wall workpiece in real time with noncontact displacement measurements during machining. Given that part dynamic behaviors can be characterized by superposition of mode shapes, the time-varying displacement and strain fields are reconstructed with modal coefficients that are updated in real time using in situ measurements. The reconstruction method has been numerically verified with finite-element analyses with the sensor locations optimized using a genetic algorithm; both static and dynamic field reconstructions are analyzed. Tradeoffs between the number of sensors and the reconstruction efficiency in terms of computation time and error are discussed. The method has been evaluated experimentally on a lathe machine testbed, where the dynamics of the distributed physical fields have been successfully captured and analyzed, demonstrating its practicality as a real-time tool for continuously monitoring the displacement and strain distributions across a disk workpiece during machining. [ABSTRACT FROM AUTHOR]

This paper presents a new modeling method to determine the harmonic eddy current (EC) field induced in a nonferrous metal and its corresponding magnetic flux density (MFD) by an EC-based sensing system for geometrical measurements, which accounts for the boundary effects of the object. Modeled using a distributed current source (DCS) method in state-space representation, the EC field is formulated as a two-step constrained least-square problem to solve for its real and imaginary parts. Two practical techniques to improve the efficiency and accuracy of the EC solutions are illustrated. The first refines the DCS distribution based on the skin-depth effects, and the second takes advantages of commercial mesh-generation software to facilitate the modeling of EC induced in complex-shaped objects. The DCS-based EC models are verified numerically by comparing computed results with two-dimensional (2-D) analytical axisymmetric solutions and commercial finite-element analysis, and evaluated experimentally with an EC sensor that measures the MFD generated by the induced EC in different materials and geometrical configurations. [ABSTRACT FROM AUTHOR]

In metal cutting, the ability to model its tool temperature distribution is highly desirable, as it provides an effective means to monitor the tool and workpiece conditions, particularly when machining hard-to-machine materials that have a low heat conductivity. Because of the complex heat generation in the microscale tool–chip interface, the difficulty to infer its temperature distribution is a well-known problem. In the context of dry lathe turning, this paper presents a hybrid method that considers both the macroscale tool heat transfer and microscale machining mechanics to reconstruct the 3-D tool temperature field from nonobstructed infrared (IR) images. The microscale-mechanics model identifies the contact geometry and estimates the frictional heat input to determine the complete boundary conditions to solve the macroscale heat-transfer model for the steady-state 3-D temperature distribution that provides a basis for experimentally fitting the model by comparing the computed surface temperature with actual temperature measurements. Two sets of experimental results validating the reconstructed temperature on a customized orthogonal-cutting testbed with a high-resolution IR imager and evaluating the effectiveness of the hybrid method on a lathe-turning center are presented. The results demonstrate that with the hybrid macro–micro modeling, the 3-D steady-state temperature field of a typical commercial lathe tool insert can be accurately reconstructed from a relatively low-resolution IR image. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to design and control a permanent magnet (PM) motor capable of 6-D force/torque actuation for real-time compensation of external loads to achieve minimum bearing reaction (MBR). Unlike conventional multiphase designs, the current inputs to the stator-electromagnets (EMs) can be flexibly configured to enable 6-D force and/or torque actuation in one motor; two common motor structures (radial and axial types) are illustrated. Both the forward and inverse force/torque models are presented in terms of coordinate-independent kernel functions that characterize the force between an EM and a PM pole pair. Two closed-form solutions to the inverse model that solves for the current-input vector minimizing the total input energy to generate a desired force/torque vector, which can be computed within 1 ms, are derived and verified numerically. A feedforward MBR compensator designed to argument the proportional-integral-derivative (PID) speed regulator has been experimentally evaluated on a structurally smart spindle system to minimize bearing reactions. Experiments show that the MBR compensation effectively reduces vibrations and improves cutting quality. [ABSTRACT FROM PUBLISHER]

This paper presents a new thermal-field modeling method referred to here as a flexible division algorithm (FDA) for predicting the temperature fields of a mechatronic system, and its real-time applications where thermal effects have a significant influence on the performance and reliability of the final products. This algorithm, which takes advantages of the flexible division in 3-D space to deal with the spatial distribution of thermal fields, is built upon physical laws to derive the governing equations in state-space representation that facilitates the reconstruction and control of the thermal field being analyzed. Three numerical models (involving both Cartesian and cylindrical coordinates) are illustrated to highlight the effectiveness and usefulness of the FDA for real-time modeling and computing. In the context of a thin-walled component machining application, the FDA is evaluated numerically and validated experimentally. Its solutions agree well with results computed using commercial finite-element analysis (FEA) software, confirming its ability to obtain accurate results, but with significantly less computation time, and its effectiveness as a complement to FEA when real-time computing of a physical field is required. [ABSTRACT FROM PUBLISHER]

This paper presents a method utilizing geomagnetic field effects commonly found in nature to help the visually impaired persons (VIPs) navigate safely and efficiently; both indoor and outdoor applications are considered. Magnetic information indicating special locations can be incorporated as waypoints on a map to provide a basis to help the user follow a map that amalgamates the waypoints into spatial information. Along with a magnetic tensor sensor (MTS), a navigation system for helping VIPs more effectively comprehend their surroundings is presented. With the waypoint-enhanced map and an improved dynamic-time-warping algorithm, this system estimates the user's locations from real-time measured magnetic data. Methods using image data to enhance waypoints at dangerous locations are discussed. The MTS-enhanced method can be integrated into existing personal mobile devices (with built-in sound, image, video, and vibration alert capabilities) to take advantages of the rapidly developing internet, global positioning systems, and computing technologies to overcome several shortcomings of blind-assistive devices. A prototype MTS-enhanced system for indoor/outdoor navigation has been developed and demonstrated experimentally. Although the MTS and algorithm are presented in the context of way-finding for a VIP, the findings presented here provide a basis for a wide range of applications where geomagnetic field effects offer an advantage. [ABSTRACT FROM PUBLISHER]