Search

The mechanical parameters, including the Coulomb and viscous friction coefficients together with the moment of inertia, are of great interest for the performance optimization and condition evaluation of surface-mounted permanent magnet synchronous motor (SPMSM) drives. This article contributes a speed-controller-independent mechanical parameter identification scheme using open-loop speed response due to signal injection, which has not been reported in existing works. It is designed based on the premise that the viscous friction torque is disproportional to the rotor speed, which is a new progress toward estimating the mechanical parameters with high precision. Moreover, as a practical full-participation-type solution, this scheme involves a new electrical parameter estimation technique based on differential algebra to assist in identifying the mechanical parameters. This auxiliary technique attains the current-controller-free estimation of the electrical parameters with the inverter nonlinearity eliminated, thereby addressing the current controller self-commissioning and serving to acquire the accurate electromagnetic torque. The experimental evaluations on two prototype SPMSM drive systems validate the feasibility of this suggested scheme. [ABSTRACT FROM AUTHOR]

The improvement of sailing speed and endurance of microunderwater vehicle can be achieved by reducing the wall friction drag. We proposed a piezoelectric drag reducer (PDR), which can be embedded into the wall of the underwater vehicle without affecting the original streamline. We discussed the drag reduction characteristics of the PDR with different arrangement angles based on the simulation analyses, and a maximum friction drag reduction rate of 45.3% can be achieved when the arrangement angle between the direction of PDR and the incoming flow is 60°. The influences of key parameters on the turbulence characteristics are obtained with a view to select control parameters for meeting different drag reduction requirements. In order to verify the simulation results, we carried out experimental tests, the experimental data have been analyzed using turbulence statistical method. The relative errors of friction drag reduction results between simulation and experiment are less than 12%, which proved the effectiveness of the proposed arrangement and control parameter selection methods. Then, the feasibility of achieving high-efficiency active drag reduction of microunderwater vehicle, based on the proposed PDR, is verified to be effective according to the test results of total drag experiments. [ABSTRACT FROM AUTHOR]

With simple structure and control, impact inertial piezoelectric actuators are one promising type for precision positioning with large working stroke and high resolution. However, their applications still face some challenges, especially the incompatibility between speed and resolution as well as the motion instability due to the overturning moment. Therefore, innovative design of impact inertial actuators is urgently required. In this article, by designing an asymmetric compliant mechanism with a thick end and a thin end to generate asymmetric friction between the driving feet and U-groove, a novel impact inertial piezoelectric actuator was proposed. Its structure design, working principle, and output performances were addressed in detail. The results indicated that the thick end and thin end had quite different stepping characteristics, and the ideal stepping characteristic with quite small backward motion was achieved at the thick end. The displacement-time curves confirmed the motion stability of the actuator for bidirectional motions, and the small difference in forward and reverse speeds was explored. This actuator achieved the maximum speed of 7311 μm/s, the resolution of 221 nm, vertical and horizontal loading capacities being over 20 N and 1.4 N, respectively. Performance comparison with some previous impact inertial actuators further demonstrated the advancement. [ABSTRACT FROM AUTHOR]

Linear brakes are devices used to restrict relative linear motions between two points. The use of soft robotic technology has enabled the fabrication of lightweight linear brakes making use of frictional forces generated by a vacuum on jamming layers. This kind of device has significant potential for wearable devices as they are lightweight yet produce significant linear tensions which can be used to transfer loads or to selectively prevent certain motions of the body. However, vacuum-based devices have limitations in terms of maximum pressure and due to the decreasing frictional forces as the jamming layers decrease in contact area as they separate during the motion. This article introduces a positive and negative pressure linear brake where both positive and negative pressure is applied to jamming layers located inside of a pouch motor which is pressurized using positive pressures. This results in a soft linear brake capable of large braking forces and of adjusting its behavior through the variation of both positive and negative pressures. The proposed brake could sustain a linear tensile force approaching 500 N even at lower pressures and was implemented as a lower back support device intended for factory and healthcare workers. [ABSTRACT FROM AUTHOR]

Tendon–sheath artificial muscle (TSAM) is a type of artificial muscle, which is widely used in robotic flexible endoscopies. The characteristics of the tendon force/position transmission were studied recently, but the control issue of the TSAM twist is still barely concerned. In this article, an effective robust control scheme is proposed for the TSAM twist, which achieves satisfactory tracking performance. First, a rigorous model was developed for the TSAM twist with consideration of parameters uncertainty and actuator input constraints, moreover, the disturbance of the discontinuous friction (Coulomb friction) was analyzed. Next, by applying some signal operation methods, a nonlinear robust controller was designed. In addition, the stability of the control strategy was proven theoretically by utilizing Lyapunov-based theory. Finally, a series of hardware experiments were conducted on a robotic flexible ureteroscope test-bed. The feasibility of the proposed model, the effectiveness and robustness of the designed control method were extensively validated. [ABSTRACT FROM AUTHOR]

Aiming at the problem of two motors system of a large optical telescope, a feedforward friction compensated linear active disturbance rejection control (FFLADRC) algorithm is proposed in this article. The algorithm consists of a friction compensated linear active disturbance rejection control (FLADRC) and two nonlinear tracking differentiators (NTDs). The FLADRC realizes the control of the two motors system by decoupling and compensates the friction. The NTDs are used to generate reference position, velocity, and acceleration signals. First, a mathematical model of the two motors system is established. Second, the FFLADRC algorithm is derived using the idea of decoupling. Third, the parameters tuning method of the FFLADRC is given. Fourth, the stability and synchronization mechanisms of the algorithm are analyzed. Finally, the experiments are carried out on a large optical telescope. In the experiments, single motor control, master–slave control, cross-coupling control, and FFLADRC are compared. The results show that FFLADRC has the minimum synchronization error and tracking error, which verifies the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The accurate knowledge of tire–road friction coefficient (TRFC) contributes to the optimization of driver maneuvers for further improving the safety of intelligent vehicles. The performance of the existing estimation methods would decline when a vehicle performs complex driving maneuvers. In addition, the mass parameter mismatch also deteriorates the estimation accuracy of TRFC. To address these problems, in this article, an integrated scheme for TRFC estimation is proposed by combining a strong tracking unscented Kalman filter and an interactive multiple model unscented Kalman filter. Real-time experiments are implemented on a mass-produced vehicle to demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed approach has better estimation accuracy than the existing ones under various driving scenarios. [ABSTRACT FROM AUTHOR]

Although harmonic drives have been adopted by all sorts of industrial environments, the mathematical expression of its dynamics has not yet been fully solved. An intelligent algorithm based on data acquisition is used to analyze the kinematic parameter of the flexible manipulator offline to improve the accuracy of predicting output torque. In this study, a method is proposed to capture the dynamics of harmonic drive systems, such as temperature, speed, and load. A friction model is proposed, and the model parameters are estimated by MCMC (Markov chain Monte Carlo) approximation. The accuracy of the estimated parameters in different conditions is calculated, and the sensitivity to parameter uncertainty of the proposed model is considered.

In general, the friction coefficient of a soft object, which has a low elastic modulus, is greater than that of a hard object. Briefly, friction and hardness are physically correlated. Given this relationship, a question naturally arises: are they perceptually coupled? We hypothesized that the higher an object’s surface friction coefficient, the softer it would feel in a physically consistent manner. To confirm this hypothesis, we conducted two types of psychophysical experiments using skin-like materials made of polyurethane and human cheeks as stimuli considering the potential applications in cosmetics. In experiment 1, skin-like objects with the same dimensions and stiffness were coated with powders so that they had different friction coefficients. Participants actively explored and evaluated the softness of these surfaces using their fingers. Their exploratory motions were restricted to either pressing or rubbing. When participants repeatedly pressed the surfaces with no sliding motion, they judged the softness of all the surfaces to be equal. In contrast, when participants rubbed the surfaces, they judged the surfaces with lower friction (i.e., more slippery) as softer than the surfaces with higher friction. In experiment 2, the same results were obtained using human cheeks, one side of which was lubricated to be more frictional. This psychophysical interference between hardness and friction is paradoxical in terms of tribology and contact mechanics. We discuss the potential reasons that led to these results.

This article presents a high-efficient thermal analysis methodology and outlines a set of useful design guidelines for high-power linear ultrasonic motors. A thermal network modeling technique is introduced to rapidly calculate the temperature rise for a typical high-power linear ultrasonic motor with a V-shaped stator. First, a six-terminal equivalent circuit for Langevin piezoelectric transducer considering the prestress bolt loss and all three losses in piezoelectrics is proposed to calculate the stator loss. Then, the calculated losses along with the friction loss are used as inputs into the developed thermal network model to calculate the temperature rise of critical parts of the motor. Furthermore, an analytical mechanical model combined with the proposed thermal network is established to calculate the temporal–spatial distribution of the stator thermal stress for evaluating its fatigue under the heating-up process. Finally, some experimental measurements and finite-element simulations are conducted to validate the theoretical analyses. [ABSTRACT FROM AUTHOR]

Soft robots made from soft materials show great advantages over rigid robots in environmental adaptability and motion flexibility. However, too soft body makes them lose the load capacity, which limits their applications in locomotion. Although the crawling tensegrity robots with both rigid bars and flexible cables are potential to address this challenge, the existing inchworm friction drive methods are difficult to realize the motion of a single tensegrity unit. Besides, the lack of appropriate soft actuators and robot configuration also blocks the development of the crawling tensegrity robots. This article presents a new inchworm driving method realized by the inclined supporting feet. By using the twisted artificial muscle (TAM) as actuator, the combination of the TAM and the inclined supporting feet endows a single three-bar tensegrity unit with multimotion capacity and anisotropic stiffness characteristics. The designed tensegrity robot not only has high compliance but also displays high stiffness, which endows it with high load capacity. The prototype can carry a load of 150 g (7.5 times of its weight) to achieve straight and turning motions. This article provides a design idea for the crawling tensegrity robot and a theoretical foundation for improving the load capacity of high compliance robots. [ABSTRACT FROM AUTHOR]

The belt-drive control enables the mechanical system to gain the advantages of lightweight, vibration absorption, and high torque, while it brings strong nonlinear disturbances due to friction, backlash, and flexibility. Therefore an improved disturbance observer (DOB) control method based on the dual-rate loop structure is proposed in this article to suppress these disturbances. Only a linear low-frequency device model is required, which indicates that this method avoids the dependence on accurate identification of the nonlinear uncertain systems. The rate information on the motor-side is replaced with the input signal of inner loop due to the high bandwidth of inner motor loop, which greatly simplifies the design of the control system. In the case of insufficient system bandwidth, the proposed method integrates the favorable information of the load-side and the motor-side under the DOB framework. And the speed-commutation spikes and chatters resulting from disturbances on the flexible transmission chain can be more effectively suppressed by the proposed control structure compared with the conventional methods. [ABSTRACT FROM AUTHOR]

This article puts forward an idea for dc electromagnetically (EM) actuated switching devices operation improvement by means of an electronic controller application. The idea is aimed at applying compensation for the movable armature inertia and the time required for coil (de)energization. Based on the results of the measurements of the tested contactors switching parameters, the most efficient (de)energizing conditions for “near–to–zero” synchronized switching (NZSS) method application were determined. The NZSS process realization approach operates on the principle of controlling the driving coil supply voltage delivery moment. By means of the same controller circuit, voltage-zero synchronized contacts making and current-zero synchronized contacts breaking operations were realized. The method was experimentally verified for various supply conditions and load parameters. Long-term tests confirm the suitability of the method for low-voltage (LV) EM actuated switching devices. The circuit was able to control various EM drives with no modification required for the structure in which it was used. [ABSTRACT FROM AUTHOR]

Due to the wide distribution and high energy-saving potential of industrial robots, energy optimization techniques of industrial robots attract increasing attention. Dynamic time-scaling methods can optimize the energy consumption of robots only by stretching or shrinking reference trajectories in the time dimension. Dynamic time-scaling methods show advantages over other energy-saving techniques because time-scaling methods can achieve energy savings without hardware investment. Traditional dynamic time-scaling methods need to search the possible state transitions from the initial configuration to the final configuration to obtain the optimal solution. The integration of robot transient power has to be carried out for each possible state transition, which directly leads to intensive computation. Therefore, in this article, an efficient computation method for robot trajectory optimization is proposed. Based on parameter separation, an energy characteristic parameter model based on the dynamic time-scaling is developed, which describes the energy consumption during the state transition as a function of the scaling parameters. Based on the energy characteristic parameter model, the dynamic programming algorithm can replace the integral operation of transient power with the substitution calculations, which avoids intensive computation. Experimental results show that the proposed method can achieve 33.7% less energy consumption, and the computation time can be reduced by nearly 99%. [ABSTRACT FROM AUTHOR]

Tire states and capacity monitoring is critical for vehicle and wheel stabilization controls in automated driving and active safety systems. Tire capacity, which represents the performance margin of tire forces from its limits, determines the operational range for vehicle control systems and their actuation through steering or torques at each tire to maintain stability while performing trajectory following. This paper presents a generic tire capacity identification framework that can handle different normal loads, road surface friction, and combined-slip driving scenarios, which are challenging for stabilization and tracking control programs in automated driving systems. A novel measuring method for generating force-training data is designed by combining the indoor tire test procedure and tread rubber friction test rig, in order to obtain adequate and high-quality benchmark datasets. The results from large data sets from road experimenting and indoor tire test facilities, including pure- and combined-slip conditions, confirm effectiveness of the developed learning-based tire capacity estimation which utilizes notions from the model description with bounded uncertainty. More importantly, the proposed method can provide reliable tire properties ranging from the linear to the sliding regions. Further validation is performed on a real test car with on-board sensory measurements, and the results confirm accuracy of the proposed method for various free rolling and hard launch/brake scenarios. [ABSTRACT FROM AUTHOR]

This article proposes a nonlinear observer for estimating a powertrain transmitted torque of vehicles equipped with dual-clutch transmissions. A new dynamical model of vehicle driveline is presented. It introduces a single characteristic state based on the dynamic friction model to scale the clutch torque capacity, which is available from the actuator position-to-torque map. Based on this model, the generated torque on the clutch disk can be effectively estimated in real time, and the sensitivity of the estimated value caused by high gain feedback can be reduced in the observer. Also, the engine torque uncertainty is estimated from the integrated driveline model. The Lyapunov-based analysis is presented to prove the convergence of the proposed observer. The effectiveness of the proposed method is shown by experimental validations on a test vehicle that allows for real measurements of the input shaft torque of transmission. [ABSTRACT FROM AUTHOR]

The moving components and servo control systems of computer numerical control (CNC) machine tools spent a substantial energy but received less attention regarding energy saving. This article presents a novel energy saving methodology of feed system using a data-model hybrid driven design optimization approach for the integrated design of moving component structural geometry and control system. Surrogate models are built based on the design of experimental data to avoid time-consuming finite element analysis. The energy consumption mechanism model is constructed via energy flow analysis method. The data-model hybrid modeling method realizes the collaborative optimization of the machine tool feed system structure and controller, while simultaneously accelerating the optimization process. A multi-objective trade-off model with energy consumption and deformation is established. Three different multi-objective optimization approaches are taken to drive the developed multi-objective optimization model. The control performance of the feed system is demonstrated through simulation analysis. Results indicate that the optimized scheme can reduce energy consumption by over 10% and maximum deformation of the tool holder by over 14%. Note to Practitioners—This article is motivated by the problem that a significant energy consumption occurs when the CNC machine tool feed system continuously drives the moving components to move, accelerate or decelerate. The previous studies to cope with this problem broadly are to separately analyze energy-saving characteristics of the structure or control system of the CNC machine tool feed system. This article suggests a novel data-model hybrid approach for energy saving of machine tool feed system, which simultaneously integrates design of moving component structural geometry and servo control system. In this article, we mathematically derive an energy consumption mechanism model of the CNC machine tool feed system. By using surrogate assisted method, a multi-objective trade-off model with energy consumption and deformation is established. Simulation experiments indicate that this approach is feasible and can significantly reduce the energy consumption of CNC machine tool feed system. [ABSTRACT FROM AUTHOR]

Many previous works of soft wearable exoskeletons (exosuit) target at improving the human locomotion assistance, without considering the impedance adaption to interact with the unpredictable dynamics and external environment, preferably outside the laboratory environments. This article proposes a novel hierarchical human-in-the-loop paradigm that aims to produce suitable assistance powers for cable-driven lower limb exosuits to aid the ankle joint in pushing off the ground. It includes two primary loop layers: impedance learning in the external loop and human-in-the-loop adaptive management in the inner loop. Considering unknown terrains, its impedance model can be transferred to a quadratic programming problem with specified constraints, which a designed primal-dual optimization prototype then solves. Then, the presented impedance learning strategy is introduced to regulate the impedance model with the adaptive assistant powers for humans on different terrains. An adaptive controller is designed in the inner loop to balance the nonlinearities and compliance existing in the human-exosuit coexistence, while the robust mechanism compensates for disturbances to facilitate trajectory management without employing the general regressor. The advantage of the proposed technique over conventional solutions with fixed impedance parameters is that it can improve human walking performance over different terrains. Experiments demonstrate the significance of the approach. [ABSTRACT FROM AUTHOR]

This article presents a closed-form approach to constraining a flow within a given volume and around objects. The flow is guaranteed to converge and to stop at a single fixed point. The obstacle avoidance problem is inverted to enforce that the flow remains enclosed within a volume defined by a polygonal surface. We formally guarantee that such a flow will never contact the boundaries of the enclosing volume or obstacles. It asymptotically converges toward an attractor. We further create smooth motion fields around obstacles with edges (e.g., tables). Both obstacles and enclosures may be time-varying, i.e., moving, expanding, and shrinking. The technique enables a robot to navigate within enclosed corridors while avoiding static and moving obstacles. It was applied on an autonomous robot (QOLO) in a static complex indoor environment and tested in simulations with dense crowds. The final proof of concept was performed in an outdoor environment in Lausanne. The QOLO-robot successfully traversed a marketplace in the center of town in the presence of a diverse crowd with a nonuniform motion pattern. [ABSTRACT FROM AUTHOR]

Measuring contact friction in soft-bodies usually requires a specialised physics bench and a tedious acquisition protocol. This makes the prospect of a purely non-invasive, video-based measurement technique particularly attractive. Previous works have shown that such a video-based estimation is feasible for material parameters using deep learning, but this has never been applied to the friction estimation problem which results in even more subtle visual variations. Because acquiring a large dataset for this problem is impractical, generating it from simulation is the obvious alternative. However, this requires the use of a frictional contact simulator whose results are not only visually plausible, but physically-correct enough to match observations made at the macroscopic scale. In this paper, which is an extended version of our former work A. H. Rasheed, V. Romero, F. Bertails-Descoubes, S. Wuhrer, J.-S. Franco, and A Lazarus, “Learning to measure the static friction coefficient in cloth contact,” in Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit., 2020, pp. 9909–9918, we propose to our knowledge the first non-invasive measurement network and adjoining synthetic training dataset for estimating cloth friction at contact, for both cloth-hard body and cloth-cloth contacts. To this end we build a protocol for validating and calibrating a state-of-the-art frictional contact simulator, in order to produce a reliable dataset. We furthermore show that without our careful calibration procedure, the training fails to provide accurate estimation results on real data. We present extensive results on a large acquired test set of several hundred real video sequences of cloth in friction, which validates the proposed protocol and its accuracy. [ABSTRACT FROM AUTHOR]

To determine all the material constants of a piezoelectric crystal using the IEEE resonance method or ultrasonic method, several samples with specific geometries and orientations are required, and the obtained results may be somewhat self-contradictory. The resonant ultrasound spectroscopy (RUS) can determine full material constants of a single piezoelectric sample by matching the numerically computed eigenfrequencies to the measured resonance spectrum. However, typically the usage of PZT transducers for excitation and reception makes the testing complicated and may add additional mass and damping. In this work, we propose a new method called partial electrode electromechanical impedance spectroscopy (PE-EMIS), which can obtain all the elastic, piezoelectric constants, and related internal frictions of a piezoelectric crystal by just using a single sample without additional transducers. In PE-EMIS, two small PEs are fabricated on one corner of a piezoelectric sample, and the sample’s resonance frequencies, along with the internal frictions of the ${k}$ th eigenmode, can be accurately obtained from the conductance spectrum measured using an impedance analyzer. The PE-EMIS experiment is carried out on a rectangular parallelepiped PZT-4 piezoelectric ceramic, and the extracted material constants are highly repeatable. Three of the extracted elastic constants (${c}_{{11}}^{E}$ , ${c}_{{33}}^{D}$ , and ${c}_{{66}}^{E}$) are validated by the traditional wave propagation method. Due to its simplicity, convenience, and accuracy, the proposed PE-EMIS is expected to be widely used for characterization of piezoelectric materials in near future. [ABSTRACT FROM AUTHOR]

The backward motion is an intrinsic feature of the conventional piezoelectric stick-slip actuator (PSSA), limiting the output speed and applications. Various methods have been proposed for restraining the backward motion. Each method has its pros and cons for the practical application of driving a precision motion stage. A novel method for restraining the backward motion is proposed in this article, in which a passive damping foot is utilized to hold the runner when the active driving foot slips on the runner. An actuator is developed based on this mechanism. The structural dimensions of the actuator are determined with an analytic model and a finite element model. A prototype of the proposed actuator is fabricated and tested by experiments. The experiments validate the operating principle of the actuator for restraining the backward motion, which is eliminated (the backward ratio is less than 1%) when the passive damping foot has an appropriate clamping force. The proposed method is very valuable for designing a PSSA with no backward motion, and it can broaden the applications for precision manipulations. [ABSTRACT FROM AUTHOR]

In this article, we design a novel saturated proportional-derivative (PD) with sliding-mode control (SMC) method or saturated PD-SMC in short for 4-DOF tower crane systems under uncertain dynamics, external disturbances, as well as saturated control input constraints. The designed control method is model free, which can achieve accurate positioning and rapid swing suppression and elimination using only jib/trolly position/velocity and payload swing feedback with limited control inputs. Different from the existing control methods, the designed control method takes the advantages of simple structure and being easily realized in practical applications of the PD control, strong robustness of the SMC method with respect to model uncertainties and external disturbances, avoiding the requirements of accurate model knowledge associated with the SMC method, as well as rapid payload swing reduction of the swing suppression control. The stability of the controlled system is ensured by rigorous Lyapunov-based analysis. To the best of our knowledge, this is the first model-free control method without any linearization operations for tower crane systems with uncertain dynamics, external disturbances, and saturated control input constraints. Several experimental results are given to validate the superior control performance and strong robustness of the designed control method. [ABSTRACT FROM AUTHOR]

For permanent magnet synchronous linear motor (PMSLM), the traditional controller tuning method needs to identify the thrust coefficient and the mover mass separately. In order to simplify the parameter identification required for controller tuning of PMSLM, a strategy identifying the parameter named gain is proposed in this article. The gain is a parameter that combines the mover mass and thrust coefficient of PMSLM. The convergence time of the strategy is analyzed as well as the influence of the detent force on the identification error is investigated. After that, a controller tuning method based on the frequency domain is proposed and the geometric constraint relationship between the controller parameters is revealed. Eventually, combining the methods mentioned above, the experiment is carried out on a PMSLM prototype. The effectiveness of the proposed strategies is proved. [ABSTRACT FROM AUTHOR]

This paper presents an autonomous vehicle’s path planning and tracking system optimized for collision avoidance on slippery roads. During path planning, a path that can induce the maximum possible lateral acceleration is generated through the fifth-order spline in consideration of the tire-road friction. The generated path is tracked based on the model predictive control (MPC), and the nonlinearity generated by the tire and low friction surface is reflected through the extended bicycle model and the combined brushed tire model. Inside the controller, a new type of yaw rate constraint considering side-slip angles is utilized to prevent the vehicle from becoming unstable on slippery roads and maximize lateral maneuver of the vehicle at the same time. The proposed system is verified by the vehicle dynamics software CarSim, and the simulation results show that it significantly increases the possibility of collision avoidance in slippery road conditions. [ABSTRACT FROM AUTHOR]

Sliding friction pair composed of contact wire and pantograph slide is the key component of train current collection system. Contact temperature is one of the important factors affecting the current-carrying and wear performance of the friction pair. In this article, sliding electrical contact experiments under different experimental conditions were conducted. Based on the measured contour curve of the slide surface, two fractal parameters of the slide surface were calculated by using the structure function method. And the effect of contact current, contact pressure, and sliding speed on the fractal parameters was discussed. A temperature field simulation model of sliding electrical contact considering two rough contact surfaces was established with COMSOL Multiphysics software. The effect of surface roughness and fractal parameters on contact temperature was analyzed by simulation. When other simulation parameters keep constant, the contact temperature first drops and then rises as the average roughness height of the contact surface increases. The average roughness slope of the contact surface has little effect on the contact temperature under high speed and strong current conditions. The contact temperature continuously decreases with the increase of fractal dimension or the decrease of fractal roughness. The conclusions can be used as a basis for further research on the contact temperature characteristics of the friction pair to improve its electrical contact performance. [ABSTRACT FROM AUTHOR]

In this article, we address the problem of motion planning and control at the limits of handling, under locally varying traction conditions. We propose a novel solution method where traction variations over the prediction horizon are represented by time-varying tire force constraints, derived from a predictive friction estimate. A constrained finite time optimal control problem (CFTOC) is solved in a receding horizon fashion, imposing these time-varying constraints. Furthermore, our method features an integrated sampling augmentation procedure that addresses the problems of infeasibility and sensitivity to local minima that arise at abrupt constraint alterations, for example, due to sudden friction changes. We validate the proposed algorithm on a Volvo FH16 heavy-duty vehicle, in a range of critical scenarios. Experimental results indicate that traction adaptive motion planning and control improves the vehicle’s capacity to avoid accidents, both when adapting to low local traction, by ensuring dynamic feasibility of the planned motion, and when adapting to high local traction, by realizing high traction utilization. [ABSTRACT FROM AUTHOR]

Many innovative applications of vehicle control involve trajectory following while avoiding collisions, respecting actuator and dynamic limits, and using complex nonlinear dynamics. Additionally, these vehicle controllers must operate in the presence of difficult-to-model and uncertain dynamic forces which are often a function of the environment. To solve these problems, we present a design and experimental validation of neural network model predictive control (NNMPC), a method that uses vehicle operation data to construct a neural network model which is efficiently implemented in MPC. By learning a neural network model with a history of states and controls, NNMPC is capable of predicting vehicle dynamics in changing and complex operating conditions. We challenge NNMPC with the difficult task of automated racing near the friction limits without prior knowledge of the road-tire friction coefficient. The experimental results on an automated test vehicle demonstrate the capability of NNMPC to follow a trajectory near the limits on both high- and low-friction test courses. Furthermore, NNMPC outperforms a physics-based benchmark MPC on both the courses where the environmental latent state of road-tire friction is explicitly considered. [ABSTRACT FROM AUTHOR]

Robot end-effector tracking of a specific spatial path to fulfill certain requirements is a topic of great interest. First, considering both dynamic constraints and kinematic constraints, the planned velocity has characteristics of bounded high-order derivatives to ensure smooth motion. Second, to meet high-efficiency requirements, the feedrate of the end-effector should be planned within the best possible time. Although some studies have shown that they obtained the time-optimal solution by considering the second-order constraints, this is still an open problem for third-order constraints. Therefore, this article proposes an approximate time-optimal feedrate (ATOF) planning algorithm that considers third-order constraints. This algorithm is primarily based on the bidirectional scanning method, which includes two steps. First, we calculate the second-order time-optimal velocity (TOV2) curve under the third-order maximum velocity curve. Then, considering TOV2, we propose an ATOF algorithm that includes single-direction speed planning and speed curve smoothing. It is more practical for not only considering the Coulomb viscous friction and torque rate but also avoiding difficult calculations at the singular point and solves discontinuous joint-acceleration under second-order constraints. Finally, we design two sets of experiments to verify the higher calculation efficiency and effectiveness of the proposed ATOF algorithm. [ABSTRACT FROM AUTHOR]

The instantaneous large disturbances, which are typically characterized by large amplitudes and short durations, generally force the actual trajectory of a servo motor system to deviate from the desired trajectory dramatically. In view of this, a novel fast trajectory recovery scheme is proposed mainly from the perspective of trajectory planning. To this end, a two-loop constrained trajectory replanning based control framework is developed to recover the deviated trajectory in a minimum-time manner under various modeling uncertainties, kinematic and dynamic constraints. Comparative experiments on a servo motor testbed show superiorities of the proposed approach over other related algorithms. [ABSTRACT FROM AUTHOR]

Due to the premise of uniqueness and acceptance, fingerprint has been the most adopted biometric technologies in high-impact applications (e.g., smartphone security, monetary transactions and international-border verification). Although there are an array of commercial fingerprint scanners across different sensing modalities including optical, capacitive, thermal and ultrasonic, existing fingerprint technologies are vulnerable to spoofing attacks via fake-finger in Kang et al., 2003. In this paper, we investigate a new dimension of fingerprint sensing based on the friction-excited sonic wave (in simpler words, ”voice of fingerprint”) from a user swiping his fingertip on everyday surfaces. Specifically, we develop SonicPrint to leverage the intrinsic fingerprint ridge information in sonic wave for user identification. First, the complex ambient noise is isolated from the sonic wave using background isolation and adaptive segmentation models. Afterward, a series of multi-level friction descriptors that highlight the target fingerprint information is extracted. These descriptors are fed to a specially designed ensemble classifier for user identification. SonicPrint is practical as it leverages in-built microphones in smart devices, requiring no hardware modifications. As the first exploratory study, our experimental results with 31 participants over three different swipe actions on 12 different types of materials show up to a 98 percent identification accuracy. [ABSTRACT FROM AUTHOR]

In this article, a self-driving vehicle controller that optimizes the path a vehicle follows from its initial position to its destination is presented. The methods include clustering-based k-means, hierarchical, Gaussian matrix model, and self-organizing mapping. The real-time parallel implementation of the unsupervised machine learning algorithms could provide fast response times of under one microsecond during the lateral, longitudinal, and angular motion control of the autonomous vehicle. It was observed that a random selection of one of the machine learning methods may not always guarantee the optimality of the position and velocity variables as compared to the desired values. The proposed parallel implementation and optimization of the algorithms could have a significant contribution towards making transportation mobility more reliable and sustainable for future vehicular systems. [ABSTRACT FROM AUTHOR]

This article proposes a novel interaction force estimation scheme capable of estimating the interaction forces for industrial robots with high precision in the absence of force sensors. Specifically, we first establish the dynamic model of a class of industrial robots via model identification methods. Furthermore, a high-order finite-time observer (HOFTO) is established to estimate the interaction forces, where HOFTO serves as an interaction force observer and is designed to accurately estimate external time-varying interaction forces. In addition, we strictly analyze the stability of our approach in two different cases, endowing HOFTO with reliable estimation abilities in broader applications. Subsequently, we integrate the estimated force information into the applications of force control frameworks (e.g., collision detection and impedance control). Several evaluations on a real 6-axes robot demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, we propose a fixed-time slip control with an extended-state observer (ESO) using only wheel speed for anti-lock brake systems (ABS) in electric vehicles. In the proposed control strategy, the longitudinal tire-road friction is defined as the disturbance. The ESO is designed to estimate the wheel speed, longitudinal tire-road friction, and longitudinal vehicle speed. Based on the estimated longitudinal tire-road friction, an optimal desired slip generator is designed, which provides optimal desired slip in real-time to maintain a nearly maximum tire-road friction coefficient (TFC), according to road surface conditions. A fixed-time controller is developed to guarantee an upper bound of convergence time determined regardless of the initial slip tracking errors. The proposed method guarantees a uniform ultimate boundedness of the wheel-slip tracking error based on an analysis of closed-loop stability. The performance of the proposed method is validated via simulations by using CarSim and MATLAB/Simulink for three scenarios on a jump TFC road surface, on a split TFC road surface, and on a suddenly cornering jump TFC road surface. The proposed method, which only employs a wheel speed sensor, achieves a shorter braking distance and stopping time in comparison with classical ABS. [ABSTRACT FROM AUTHOR]

The use of regenerative braking and recent electrohydraulic or electromechanical brake-by-wire systems with enhanced dynamics enables improved antilock braking control performance in electric vehicles. However, the possible benefit is often limited by suboptimal control architectures with separate distributed controllers for electric motor (EM) and friction brake torque requests. Furthermore, oversimplifications in synthesis models for brake control design constrain the achievable performance. Instead, to date, threshold-based algorithms are widely used in modern production vehicles despite having been designed for slower hydraulic brake systems originally. To exploit the full potential, this work proposes a continuous nonlinear control design using input–output linearization for robust wheel speed tracking control. The design uses a unified controller for the redundant actuators. In addition, it explicitly considers drivetrain oscillations induced by regenerative braking using onboard EMs in the synthesis model. The stability for the resulting zero dynamics is shown through the Lyapunov analysis. The nonlinear controller is augmented by a subsequent control allocation for splitting the control effort on the redundant actuators. The allocation design ensures consistent control performance for both regenerative braking and hybrid braking while simultaneously aiming for high-energy recovery. The overall antilock braking control design is implemented in an electric test vehicle. Its tracking performance, disturbance attenuation, and robustness are experimentally validated through various emergency braking maneuvers on different road surfaces. [ABSTRACT FROM AUTHOR]

Arm movement recovery after stroke can improve with sufficient exercise. However, rehabilitation therapy sessions are typically not enough. To address the need for effective methods of increasing arm exercise outside therapy sessions we developed a novel armrest, called Boost. It easily attaches to a standard manual wheelchair just like a conventional armrest and enables users to exercise their arm in a linear forward-back motion. This paper provides a detailed design description of Boost, the biomechanical analysis method to evaluate the joint torques required to operate it, and the results of pilot testing with five stroke patients. Biomechanics results show the required shoulder flexion and elbow extension torques range from −25% to +36% of the torques required to propel a standard pushrim wheelchair, depending on the direction of applied force. In pilot testing, all five participants were able to exercise the arm with Boost in stationary mode (with lower physical demand). Three achieved overground ambulation (with higher physical demand) exceeding 2 m/s after 2–5 practice trials; two of these could not propel their wheelchair with the pushrim. This simple to use, dynamic armrest provides people with hemiparesis a way to access repetitive arm exercise outside of therapy sessions, independently right in their wheelchair. Significantly, Boost removes the requirements to reach, grip, and release the pushrim to propel a wheelchair, an action many individuals with stroke cannot complete. [ABSTRACT FROM AUTHOR]

This brief presents a low cost hardware-in-the-loop experimental design for large ship course control with actuator in the form of hybrid circuit, which can effectively capture the essential properties of friction and provide a more realistic environment to perform test. According to the Coulomb plus static friction model formulation, the velocity decision circuit, the absolute value circuit and the friction decision circuit are designed based on the basic circuit components and are validated by a series of simulations, respectively. Besides, the circuit of PID controller and the linear model of steering gear are also added to generate the closed-loop actuator. In addition, the model of the ship and the corresponding PID course controller are realized by the algorithm in the computer. The numerical model and the circuit implementation of realistic actuator can exchange information to establish a hardware-in-the-loop experimental platform. Finally, several experiments are carried out to verify the effectiveness of the proposed low-cost system. [ABSTRACT FROM AUTHOR]

A solid-liquid triboelectric nanogenerator (TENG) has attracted increasing research interest in relation to the development of regeneration energy based on water resources. The output of solid-liquid TENG remains unsolved, however, because of the low voltage output that impedes wide applications. To this end, in this work we developed a miniaturized microfluidic channel-based TENG device for highly efficient conversion of energy from the transport of a water droplet to an electrical output. We investigated an optimized design in a triboelectric material, the droplet transport and the electrostatic induction layer to provide a high voltage output and stable energy harvesting. The optimized device demonstrated maximum voltage amplitude 102 mV with an ultralow liquid consumption, 0.36 $\mu \text{L}$ , resulting in sample-energy conversion 283.33 mV/ $\mu \text{L}$. This novel device is expected potentially to address the limitations imposed by sample consumption in energy harvesting in the future. [ABSTRACT FROM AUTHOR]

Data-driven texture modeling and rendering has pushed the limit of realism in haptics. However, the lack of haptic texture databases, difficulties of model interpolation and expansion, and the complexity of real textures prevent data-driven methods from capturing a large variety of textures and from customizing models to suit specific output hardware or user needs. This work proposes an interactive texture generation and search framework driven by user input. We design a GAN-based texture model generator, which can create a wide range of texture models using Auto-Regressive processes. Our interactive texture search method, which we call “preference-driven,” follows an evolutionary strategy given guidance from user's preferred feedback within a set of generated texture models. We implemented this framework on a 3D haptic device and conducted a two-phase user study to evaluate the efficiency and accuracy of our method for previously unmodeled textures. The results showed that by comparing the feel of real and generated virtual textures, users can follow an evolutionary process to efficiently find a virtual texture model that matched or exceeded the realism of a data-driven model. Furthermore, for 4 out of 5 real textures, $\geq$ 80% of the preference-driven models from participants were rated comparable to the data-driven models. [ABSTRACT FROM AUTHOR]

A structural model has been developed for the REBCO-based VIPER cable [1], which is designed for high magnetic field applications. In this work, structural finite element analysis (FEA) is used to simulate the stresses incurred within the REBCO tape stacks under the following conditions: (1) bending to 1 m diameter (2) cooling down to 77 K and (3) repeated transverse electromagnetic Lorentz loadings up to 1600 kN/m. The effect of solder impregnation onto the stress state of the tapes was studied via a set of friction coefficients of 0.02 (perfect-slip), 0.2 (metal-to-metal contact), and 1 (no-slip). For bending, high friction between the tape-stack and solder results in high axial strain in the tape-stack which may lead to Ic degradation. During thermal cooldown, the stress on the tape-stack is negligible. However, the differential in thermal contraction between the copper and stainless-steel jackets leads to the formation of a small gap that may cause mechanical instability. Under cyclic Lorentz loading, a higher friction coefficient reduces the deformation of the cable by restricting the relative sliding between the neighboring tapes, which results in a more uniform stress distribution and a lower peak stress. A lower friction coefficient results in larger deformation of the solder and stack and a higher peak stress. In addition, due to the accumulated plastic deformation and stress concentration in the solder, both the averaged von Mises stress and the peak stress of the outermost four tapes increase with each of the first three loading cycles. These results may explain the early-stage degradation observed in the experiments conducted on VIPER cables (Z. S. Hartwig et al., 2020). [ABSTRACT FROM AUTHOR]

This article proposes a non-smooth funnel control (NSFC) strategy based on the extended state observer (ESO) for motor-drive servo systems with unknown dynamics. These unknown dynamics, including the modeling error, the external disturbances, and the non-linear friction, are considered as a lumped disturbance. For estimating the unknown states and the lumped disturbance, a non-linear bandwidth extended state observer (NLB-ESO) is developed. The NLB designed using the Gaussian function and the position observation error can deal with the “peaking value problem” caused by the high observer gains. Furthermore, a funnel error surface is proposed based on the non-smooth error transformation (NSET) and incorporated into the dynamic surface control design procedure, where the NSFC can prescribe the position tracking error in a funnel region with small steady-state error and overshoot and short adjustment time. The non-smooth funnel error surface also avoids the singular problem in controller design by selecting the non-smooth parameter. Moreover, the stability of the closed-loop control system with the NLB-ESO is guaranteed by the Lyapunov theory. Comparative simulations and experiments show that the proposed NSFC can prescribe the tracking error in a funnel and ensure better tracking performance. [ABSTRACT FROM AUTHOR]

This study investigates the long-term instability problem of periodic-feedback-loop-based control schemes such as repetitive control, periodic adaptive disturbance observer (PADOB), and iterative learning control. The long-term instability problem is the one wherein a closed-loop system becomes unstable because a tracking error diverges with the increase in the number of iterations. A novel robust PADOB is proposed in this article to guarantee the long-term stability of the closed-loop system. The overall system eventually becomes stable because the proposed control scheme using an infinite impulse response (IIR) filter with an optimized lead time can stabilize the error propagation in the iteration domain. Compared to other methods such as zero-phase and IIR filters, the proposed control scheme is very practical because it allows selecting the cutoff frequency of the filter intuitively to stabilize the control system. The optimized lead time in the IIR filter is calculated considering the phase response of the IIR filter; it can improve adaptation speed using a high adaptation gain of the control system. Various simulation and experimental tests based on high-load motion systems that require high-precision positioning are performed to verify the theoretical analysis of the long-term instability problem and the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This article proposes a tracking controller for servomechanisms with a continuous friction model. The parameters of this model are estimated through a proposed two-step offline identification methodology that uses a linear extended state observer (LESO) based on the integral of position measurements, termed as ILESO. In the first step, the viscous and Coulomb coefficients of this friction model are estimated by the ordinary least squares method. The second step employs these estimates to obtain the initial guess for the nonlinear least squares method that identifies all the parameters of the nonlinearly parameterized friction model. Finally, a backstepping controller is designed for reference tracking, which uses the estimated offline friction model and online estimations of the servo position, velocity, and system uncertainty. These online estimations are provided by a modified ILESO, termed as FILESO, that has a similar structure to that of the ILESO but incorporates the identified offline friction model into its dynamics. The convergence and stability of the proposed observer and controller are established using contraction analysis. Experimental results show that the proposed approach exhibits satisfactory performance. [ABSTRACT FROM AUTHOR]

It is difficult to obtain linear output displacements for stepping piezoelectric platform due to their discontinuous outputs. Inspired by the theory that the maximum static friction force is greater than the sliding friction force, in this letter, we propose a bipedal alternating inertial actuation mode (BAIAM) to improve the displacement linearity of the stepping platform. The output displacements are measured, the linear fitting is carried out by the least square method, the correlation coefficient and linear fitting function are used to evaluate the displacement linearity, and the correlation coefficients of the forward and backward motions are calculated as 0.9998 and 0.9999 in BAIAM, respectively, which verifies the effectiveness of the proposed method. The closed-loop experiments in BAIAM are also carried out, and the steady-state errors for the target position of ±40 μm within ±0.2 μm in the point-to-point positioning control experiments are achieved. The experimental results confirm that the developed platform can be applied to precision fields requiring a large travel range, planar two-degree-of-freedom motion, and linear outputs. [ABSTRACT FROM AUTHOR]

This article proposes a global iterative sliding mode control approach for high-precision contouring tasks of a flexure-linked biaxial gantry system. For such high-precision contouring tasks, it is the typical situation that the involved multiaxis cooperation is one of the most challenging problems. As also would be inevitably encountered, various factors render the multiaxis cooperation rather difficult, such as the strong coupling (which naturally brings nonlinearity) between different axes due to its mechanical structure, the backlash and deadzone caused by the friction, and the difficulties in system identification. To overcome the abovementioned issues, this work investigates an intelligent model-free contouring control method for such a multiaxis motion stage. Essentially in the methodology developed here, it is first ensured that all the coupling, friction, nonlinearity, and disturbance (regarded as uncertain dynamics in each axis) are suitably posed as “uncertainties”. Then, a varying-gain sliding mode control method is proposed to adaptively compensate for the matched unknown dynamics in the time domain, while an iterative learning law is applied to suppress the undesirable effects (arising from the repetitive matched and unmatched uncertainties in the iteration domain). With this approach, the chattering that typically results from the overestimated control gains in the sliding mode control is thus suppressed during the iterations. To analyze the contouring performance and show the improved outcomes, rigorous proof is furnished on both the stability in the time domain and the convergence in the iteration domain; and the real-time experiments also illustrate that the requirements of precision motion control toward high-speed and complex-curvature references can be satisfied using the proposed method, without prior knowledge of the boundary to the unknown dynamics. [ABSTRACT FROM AUTHOR]

Two-speed or multiple-speed automatic transmissions can obviously improve the overall manipulating performance in terms of shifting quality and energy efficiency when equipped in electric vehicles (EVs). This study details the design of a two-speed clutchless automatic transmission (2AT) for EVs and the motor-controlled shifting mechanism. First, a novel two-speed clutch automatic transmission is devised with a motor-controlled shifting mechanism, which enables the shift motions and the speed control of the driving motor for synchronization during shifts. Second, a coordinated control strategy of the driving motor and controlling the motor for shifting is detailed during different shifting processes to achieve fast and smooth shifting. The torque trajectory optimization during the synchronizing process is attained by applying Pontryagin's minimum principle. The simulation and experimental results verify the shifting mechanism design and the shift control algorithm in terms of shift response and smoothness for the designed 2AT. [ABSTRACT FROM AUTHOR]

This article proposes a detailed nonlinear mathematical model of an antagonistic pneumatic artificial muscle (PAM) actuator system for estimating the joint angle and torque using an unscented Kalman filter (UKF). The proposed model is described in a hybrid state-space representation. It includes the contraction force of the PAM, joint dynamics, fluid dynamics of compressed air, mass flows of a valve, and friction models. A part of the friction models is modified to obtain a novel form of the Coulomb friction depending on the inner pressure of the PAM. For model validation, offline and online UKF estimations and sensorless tracking control of the joint angle and torque are conducted to evaluate the estimation accuracy and tracking control performance. The estimation error is less than 7.91 %, and the steady-state tracking control performance is more than 94.75 %. These results confirm that the proposed model is detailed and could be used as the state estimator of an antagonistic PAM system. [ABSTRACT FROM AUTHOR]

Objective: Considering the knee as a fluid-lubricated system, articulating surfaces undergo different lubrication modes and generate joint acoustic emissions (JAEs). The goal of this study is to compare knee biomechanical signals against synchronously recorded joint sounds and assess the hypothesis that JAEs are attributed to tribological origins. Methods: JAE, electromyography, ground reaction force signals, and motion capture markers were synchronously recorded from ten healthy subjects while performing two-leg and one-leg squat exercises. The biomechanical signals were processed to calculate a tribological parameter, lubrication coefficient, and JAEs were divided into short windows and processed to extract 64-time-frequency features. The lubrication coefficients and JAE features of two-leg squats were used to label the windows and train a classifier that discriminates the knee lubrication modes only based on JAE features. Results: The classifier was used to predict the label of one-leg squat JAE windows and it achieved a high test-accuracy of 84%. The Pearson correlation coefficient between the estimated friction coefficient and predicted JAE scores was 0.83 $\pm$ 0.08. Furthermore, the lubrication coefficient threshold, separating two lubrication modes, decreased by half from two-leg to one-leg squats. This result was consistent with tribological changes in the knee load as it was inversely doubled in one-leg squats. Significance: This study supports the potential use of JAEs as a quantitative biomarker to extract tribological information. Since arthritis and similar disease impact the roughness of the joint cartilage, the use of JAEs could have broad implications for studying joint frictions and monitoring joint structural changes with wearable devices. [ABSTRACT FROM AUTHOR]