Stiffness Actuator Research Articles

Retraction Note: Machine learning-based self-sensing of the stiffness of shape memory coil actuator

Retraction Note: Machine learning-based self-sensing of the stiffness of shape memory coil actuator

Nonlinear aerothermoelastic analysis of deployable control fin with actuator stiffness subjected to high-speed compressible flows

Nonlinear aerothermoelastic analysis of deployable control fin with actuator stiffness subjected to high-speed compressible flows

Design and Evaluation of Variable Stiffness Actuators with Predefined Stiffness Profiles

Design and Evaluation of Variable Stiffness Actuators with Predefined Stiffness Profiles

Design of a variable stiffness actuator based on a multi-pulley system with a spring

This paper presents a variable stiffness actuator (VSA) based on a multi-pulley system with a linear spring. In this design, twelve pairs of outer pulleys and six pairs of inner pulleys are evenly arranged around a center and are serially connected to a spring through a cable. When the inner pulleys rotate about the center point, the spring is extended to generate an elastic force exerted on the cable and then transmitted to the output link as an output torque, resulting in an output stiffness. The significance of the proposed design is that it can quickly vary the output stiffness by adjusting the positions of the inner pulleys using a cam disk. Also, all the components are adequately arranged, making the design compact. In this work, the design concept, analysis, and a numerical example are provided to illustrate the proposed VSA and its performance. It is shown that the VSA can offer a maximum output torque of 30 N-cm with a maximum deflection of 40 degrees. These parameters can demonstrate the wide application and high adaptability of the proposed actuator to various environments.

Robust super‐twisting sliding mode control of input‐delayed nonlinear systems using disturbance observers and predictor feedback

AbstractThis paper investigates prediction‐based robust super‐twisting sliding mode controller design for nonlinear systems with input delay and external disturbances. A novel predictor feedback is introduced based on state predictions of the original and transformed models. To cope with the external disturbances, a set of disturbance observers are utilized which estimate the future values of disturbances asymptotically. Super‐twisting sliding mode control is used to avoid chattering phenomenon which is also able to handle external disturbances. Proposed design can handle all external disturbances that their derivatives vanish at infinity. Stability proof of the closed‐loop is given in details ensuring the asymptotic stability of the tracking errors and finite time vanishing of the sliding surface. To illustrate effectiveness and applicability, the proposed design is applied to a two‐link robot and a serial variable stiffness actuator. Simulation results show that input delays of the robot and actuator are compensated, and external disturbances are correctly estimated and attenuated.

Variable stiffness performance analysis of layer jamming actuator based on bionic adhesive flaps

Soft actuators made of soft materials cannot generate precisely efficient output forces compared to rigid actuators. It is a promising strategy to equip soft actuators with variable stiffness modules of layer jamming mechanism, which could increase their stiffness as needed. Inspired by the gecko's the array of setae, bionic adhesive flaps with inclined micropillars are applied in layer jamming mechanism. In this paper, after the manufacturing process of the layer jamming actuator based on the bionic adhesive flaps is described, the equivalent stiffness models of the whole actuator are established in the unjammed and jammed states. And the shear adhesive force of a single micropillar is calculated based on the Kendall viscoelastic band model. The finite element simulation results of two bionic adhesive flaps show that the interlaminar shear stress and stiffness increase with the increase of pressure. The measurement of shear adhesive force show that the critical shear adhesive force of the bionic adhesive material is 3.2 times that of polyethylene terephthalate (PET) material, and exhibit the ability of anisotropic adhesion behavior. The variable stiffness performance of the layer jamming actuator based on bionic adhesive flaps is evaluated by three test methods, and the max stiffness reaches 8.027 N mm-1, which is 1.5 times higher than the stiffness of the layer jamming actuator based on the PET flaps. All results of simulation and experiment effectively verify the validity and superiority of applying the bionic adhesive flaps to the layer jamming mechanism to enhance the stiffness.

Active prediction compensation strategy: A new positioning compensation technique for improving the accuracy of the dual ball screw feed mechanism under load

The dual ball screw feed mechanism (DBSFM) is commonly employed in high-end machining applications. However, its accuracy is challenging to enhance due to variations in the axial stiffness of the dual actuators under load, making geometric error compensation (GEC) difficult. To address this, our research establishes a comprehensive error model that integrates geometric error and load-induced error (LIE) to improve feeding accuracy. The axial stiffness matrix of the DBSFM is identified using motor current information, and an active prediction error matrix is defined based on the geometric error model, milling force model, and axial stiffness matrix. We propose and analyze the active prediction compensation (APC) strategy as a new method to enhance accuracy under load. Experimental validation using a gantry-type machine tool demonstrates that the APC strategy can reduce the positioning error of the DBSFM to ±2 μm under load, representing significant improvements over the established GEC method. Specifically, the APC strategy achieves a 53.07% and 57.04% enhancement in accuracy along the two axes. This work illustrates the effectiveness of the APC strategy in reducing positioning errors and improving feeding accuracy in DBSFM machining processes.

Continuously Variable Transmission and Stiffness Actuator Based on Actively Variable Four-Bar Linkage for Highly Dynamic Robot Systems

Continuously Variable Transmission and Stiffness Actuator Based on Actively Variable Four-Bar Linkage for Highly Dynamic Robot Systems

A tendon-driven actuator with cantilever initiated variable stiffness used for robotic fingers

Variable stiffness actuators (VSAs) have emerged as a key actuation technology known for their bionic performance and task adaptability. However, current VSAs often exhibit relatively large sizes, making them possible for use in robotic arms and legs but less convenient for integrations into robotic hands. This paper introduces a compact design of a tendon-driven variable stiffness actuator (TVSA) based on an adjustable cantilever mechanism, which can be embedded into a robotic finger. This implementation endows the robotic finger with the independent regulation of joint position and stiffness. A concise and computationally efficient stiffness mapping model from the TVSA to the finger joints is then established, providing a theoretical foundation for the stiffness regulation of the tendon-driven fingers. A prototype of a robotic hand equipped with the presented TVSA demonstrates safe interactions with various objects of diverse shapes, weights and stiffness.

Modeling and analysis of hysteresis using the Maxwell-slip model for variable stiffness actuators

Hysteresis non-linearity in variable stiffness actuators (VSAs) causes significant torque errors and reduces the stability of the actuators, leading to poor human–computer interaction performance. At present, fewer hysteresis compensation models have been developed for compliant drives, so it is necessary to establish a suitable hysteresis model for compliant actuators. In this work, a new model with a combination of the Maxwell-slip model and virtual deformation is proposed and applied to an elbow compliant actuator. The method divides the periodic variation of the actuator into three parts: an ascending phase, a descending phase, and a transition phase. Based on the concept of virtual deformation, the nonlinear hysteresis curve is transformed into a polyline, and the output torque is estimated using the revised Maxwell-slip model. The simulation results are compared with the experimental data. Its torque error is controlled within 0.2Nm, which validates the model. An inverse model is finally established to calculate the deformation deflection angle for hysteresis compensation. The results show that the inverse model has high accuracy, and the deformation deflection is less than 0.15 rad.

Design and Analysis of a Symmetric Joint Module for a Modular Wire-Actuated Robotic Arm with Symmetric Variable-Stiffness Units

Collaborative robots are used in scenarios requiring interaction with humans. In order to improve the safety and adaptability of collaborative robots during human–robot interaction, this paper proposes a modular wire-actuated robotic arm with symmetric variable-stiffness units. The variable-stiffness unit is employed to extend the stiffness-adjustment range of the robotic arm. The variable-stiffness unit is designed based on flexure, featuring a compact and simple structure. The stiffness–force relationship of the variable-stiffness unit can be fitted by a quadratic function with an R-squared value of 0.99981, indicating weak nonlinearity. Based on the kinematics and stiffness analysis of the symmetric joint module of the robotic arm, the orientation of the joint module can be adjusted by regulating the length of the wires and the stiffness of the joint module can be adjusted by regulating the tension of the wires. Because of the actuation redundancy, the orientation and stiffness of the joint module can be adjusted synchronously. Furthermore, a direct method is proposed for the stiffness-oriented wire-tension-distribution problem of the 1-DOF joint module. A simulation is carried out to verify the proposed method. The simulation result shows that the deviation between the calculated stiffness and the desired stiffness was less than 0.005%.

Backstepping control based on adaptive neural network and disturbance observer for reconfigurable variable stiffness actuator

Reconfigurable variable stiffness actuator (RVSA) has attracted increasing attention in robotics due to its safety, compliance, and robustness. However, the control of the RVSA is challenging due to nonlinear factors such as high-order nonlinear dynamic, model uncertainties, time-varying model parameters, and disturbances. In this paper, firstly, a lightweight RVSA structure with both passive and active nonlinear variable stiffness characteristic is developed. Secondly, a dynamic surface backstepping control method based on a radial basis neural network and disturbance observer (DSBC-RBFNN-DOB) is proposed to achieve position control of the lightweight RVSA with matched and unmatched uncertainties. To address solve the “complexity explosion” and noise problems in traditional backstepping control, the dynamic surface backstepping control (DSBC) method is used to design the controller. Then, a method based on radial basis neural network (RBFNN) and disturbance observer (DOB) are used to compensate for the matched and unmatched uncertainties in the link and motor. In this method, the matched uncertainties are compensated using RBFNN, and the DOB is integrated to compensate RBFNN approximation errors and unmatched uncertainties. Through Lyapunov stability analysis, the semi-global boundedness of the controller is proven. Finally, the proposed method is simulated and actually implemented, verifying the effectiveness of the method. Simulation and experimental results show that the root mean square error (RMSE) of the proposed method is only 0.97277° and 0.6418°, respectively. Compared with PID, DSBC, and DSBC-RBFNN, the error reduction percentages in simulation (experiment) are 85.6 % (88.9 %), 49.4 % (88.4 %) and 36.1 % (80.0 %) respectively.

A Review of Somatic Design for Soft Robotic Grippers: From Parts Integration to Functional Synergy

Somatic design is crucial for soft grippers to emulate the embodied intelligence of their biological counterparts, due to the blurry boundaries among material, structure, and function. There are five critical parts in somatic design, including morphology, material, fabrication, actuation, and variable stiffness. The strong nonlinear coupling among these factors often leads to mutual influence and functional compromise after integration. Herein, methods and strategies harnessed in these parts for performance improvement of soft grippers are systematically reviewed, particularly clarifying how to exert the coupling enhancement effects of the somatic parts for functional synergy. Finally, the remaining challenges and the future development directions of soft grippers for organism‐like intelligence and wide‐range applications are discussed.

Study of dynamic performance and adaptive control of the variable stiffness actuator with time-varying parameters

The study of dynamic performance and adaptive control of variable stiffness actuators with time-varying parameters is significant for the realization of stable and efficient human-computer interaction. In this paper, for the previously proposed variable stiffness actuator, the dynamics model of the variable stiffness actuator system is established according to the two-inertia-system theory, and the effects of time-varying parameters on the dynamic performance of the variable stiffness actuator system are analyzed. Then the adaptive control strategy of the variable stiffness actuator system with time-varying parameters is studied, and the correctness and effectiveness of the control strategy are verified experimentally. The results show that the time-varying parameters have a more obvious effect on the dynamic performance of the variable stiffness actuator system, and the difficulty in designing the system control strategy, which is caused by the complex dynamics modeling of variable stiffness actuator systems with time-varying parameters, can be effectively solved by using the proposed adaptive control strategy. Moreover, the control strategy has good stability and generalization ability.

Design and control of a novel variable stiffness actuator based on antagonistic variable radius principle

Variable stiffness actuators (VSAs) are essential for ensuring safe human–robot interactions in robotic applications. This paper proposes a novel rotary VSA using an antagonistic Hoberman linkage mechanism (AHLM), which offers a large stiffness range and a compact structure. The VSA-AHLM consists of two sets of antagonistic-type quadratic springs based on spiral cams connected to the Hoberman linkage mechanism (HLM) through four cables. By simultaneously adjusting both the radius of the HLM and the spring preload, the stiffness of the VSA-AHLM can be varied within a large range. Furthermore, the position and stiffness of the VSA-AHLM can be controlled independently by two rotary motors. The geometric parameters of the spiral cam are determined to achieve the desired linear stiffness–elongation behavior of a quadratic spring, and detailed models of the actuator’s stiffness, elastic energy, and torque are established. An actuator prototype is fabricated to demonstrate the proposed variable stiffness approach. Experiments show that the developed actuator can achieve significant stiffness changes and exhibits excellent positioning and trajectory tracking performance.

Robotic Skins With Integrated Actuation, Sensing, and Variable Stiffness

Robotic Skins With Integrated Actuation, Sensing, and Variable Stiffness

Design, Modeling, and Control of a Compact and Reconfigurable Variable Stiffness Actuator Using Disc Spring

Abstract This paper proposes a compact and reconfigurable variable stiffness actuator (VSA) using disc spring which is named as SDS-VSA (symmetrical disc spring variable stiffness actuator). To enhance the actuator’s torque density, symmetric compression springs are integrated into the cam-roller-spring mechanism, and a disc spring combination design is employed instead of conventional springs. The disc spring configuration is tailored to achieve a broader stiffness range within a limited size, aligned with stiffness and dimensional requirements. Subsequently, the dynamics of the cam-roller-spring mechanism are derived. To tackle the challenge of strong coupling dynamics, a decoupled modeling method by introducing mismatched and matched disturbances is proposed. A back-stepping tracking controller and proportional-derivative (PD) controller with feedforward are proposed to track the link-side and stiffness motor-side trajectories, respectively. Tracking experiments under significant stiffness alteration are conduced to verify the performance of the prototype SDS-VSA.

A Variable Stiffness Actuation Based Robotic Hand Designed for Interactions

A Variable Stiffness Actuation Based Robotic Hand Designed for Interactions

Cartesian Stiffness Shaping of Compliant Robots—Incremental Learning and Optimization Based on Sequential Quadratic Programming

Emerging robotic systems with compliant characteristics, incorporating nonrigid links and/or elastic actuators, are opening new applications with advanced safety features, as well as improved performance and energy efficiency in contact tasks. However, the complexity of such systems poses challenges in modeling and control due to their nonlinear nature and model variations over time. To address these challenges, the paper introduces Locally Weighted Projection Regression (LWPR) and its online learning capabilities to keep the model of compliant actuators accurate and enable the model-based controls to be more robust. The approach is experimentally validated in Cartesian position and stiffness control for a 4 DoF planar robot driven by Variable Stiffness Actuators (VSA), whose real-time implementation is supported by the Sequential Least Squares Programming (SLSQP) optimization approach.

A Continuously Variable Transmission-Based Variable Stiffness Actuator for pHRI: Design Optimization and Performance Verification

Abstract Physical human–robot interfaces (pHRIs) enabled the robots to work alongside the human workers complying with the regulations set for physical human–robot interaction systems. A variety of actuation systems named variable stiffness/impedance actuators (VSAs) are configured to be used in these systems’ design. Recently, we introduced a new continuously variable transmission (CVT) mechanism as an alternative solution in configuring VSAs for pHRI. The optimization of this CVT has significant importance to enhance its application area and to detect the limitations of the system. Thus, in this paper, we present a design optimization approach (an adjustment strategy) for this system based on the design goals, desired force, and minimization of the size of the system. To implement such design goals, the static force analysis of the CVT is performed and validated. Furthermore, the fabrication of the optimized prototype is presented, and the experimental verification is performed considering the requirements of VSAs: independent position and stiffness variation, and shock absorbing. Finally, the system is calibrated to display 6 N continuous output force throughout its transmission variation range.