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This paper studies the working principles of antagonistic magneto-rheological (MR) actuators, i.e., a combination of an electric motor and a pair of MR clutches in an antagonistic configuration, for compliant actuation in robotics. The study focuses on the unique boundedness property exhibited by MR actuators, which limits the output torques delivered to the load, independent of the received input torque and/or control commands. This inherent property is of significant importance for ensuring human safety in human–robot interaction applications. Through a comprehensive analysis, we provide analytical proof of the inherent output boundedness of antagonistic MR actuators and validate our findings through experimental results. Our research demonstrates that these actuators are well-suited for safe operations in robotic applications, eliminating the need for additional sensor measurements or complex control strategies. This promising capability enables the avoidance of trade-offs between actuator performance, complexity, and cost. The insights gained from this study contribute to advancing compliant actuation technology, paving the way for high-performance and human-safe robotic systems. [ABSTRACT FROM AUTHOR]

This paper studies the working principles of antagonistic magneto-rheological (MR) actuators, i.e., a combination of an electric motor and a pair of MR clutches in an antagonistic configuration, for compliant actuation in robotics. The study focuses on the unique boundedness property exhibited by MR actuators, which limits the output torques delivered to the load, independent of the received input torque and/or control commands. This inherent property is of significant importance for ensuring human safety in human–robot interaction applications. Through a comprehensive analysis, we provide analytical proof of the inherent output boundedness of antagonistic MR actuators and validate our findings through experimental results. Our research demonstrates that these actuators are well-suited for safe operations in robotic applications, eliminating the need for additional sensor measurements or complex control strategies. This promising capability enables the avoidance of trade-offs between actuator performance, complexity, and cost. The insights gained from this study contribute to advancing compliant actuation technology, paving the way for high-performance and human-safe robotic systems.

A cascade control structure for the simultaneous position and stiffness control of antagonistic tendon-driven variable stiffness actuators (VSAs) implemented in a laboratory setup is presented in the paper. Cascade control has the ability to accelerate, additionally stabilize, and reduce oscillations, which are all extremely important in systems such as a tendon-driven compliant actuators with elastic transmission. Inner-loop controllers are closed in terms of motor positions, and outer-loop controllers in terms of actuator position and estimated stiffness. The dominant dynamics of the system (position and stiffness), composed of the mechanical part and inner loops, are identified by a closed-loop auto-regressive with exogenous input (ARX) model. The outer-loop controllers are tuned on the basis of experimentally identified transfer functions of the system in several nominal operating points for different stiffness values. After the system is identified, a controller bank is generated in which a pair of actuator position and stiffness controllers correspond to a nominal operating point and covers the area surrounding the nominal point for which it is designed. The controllers used are integral-proportional differential (I-PD) and integral-proportional (I-P) controllers, which are a variation of the PID and PI controllers with dislocated proportional and derivative gains from a direct to feedback branch that result to no overshoot for even fast reference changes (i.e., step signal), which is essential for preventing tendon slackening (meeting the pulling constraint). Analytical formulas for controller tuning based on only one parameter, λ, are also presented. Since position and stiffness loops are decoupled, it is possible to change λ for both loops independently and adjust their performance separately according to the needs. Also, the controller structure secures the smooth response without overshooting step reference or step disturbance signal, which make practical implementation possible. After all the controllers were designed, the cascade control structure for simultaneous position and stiffness control was successfully evaluated in a laboratory setup. Thus, the presented control approach is simple to implement, but with a performance that ensures a pulling constraint for tendon-driven actuators as a foundation for bioinspired antagonistic VSAs.

A cascade control structure for the simultaneous position and stiffness control of antagonistic tendon-driven variable stiffness actuators (VSAs) implemented in a laboratory setup is presented in the paper. Cascade control has the ability to accelerate, additionally stabilize, and reduce oscillations, which are all extremely important in systems such as a tendon-driven compliant actuators with elastic transmission. Inner-loop controllers are closed in terms of motor positions, and outer-loop controllers in terms of actuator position and estimated stiffness. The dominant dynamics of the system (position and stiffness), composed of the mechanical part and inner loops, are identified by a closed-loop auto-regressive with exogenous input (ARX) model. The outer-loop controllers are tuned on the basis of experimentally identified transfer functions of the system in several nominal operating points for different stiffness values. After the system is identified, a controller bank is generated in which a pair of actuator position and stiffness controllers correspond to a nominal operating point and covers the area surrounding the nominal point for which it is designed. The controllers used are integral-proportional differential (I-PD) and integral-proportional (I-P) controllers, which are a variation of the PID and PI controllers with dislocated proportional and derivative gains from a direct to feedback branch that result to no overshoot for even fast reference changes (i.e., step signal), which is essential for preventing tendon slackening (meeting the pulling constraint). Analytical formulas for controller tuning based on only one parameter, λ, are also presented. Since position and stiffness loops are decoupled, it is possible to change λ for both loops independently and adjust their performance separately according to the needs. Also, the controller structure secures the smooth response without overshooting step reference or step disturbance signal, which make practical implementation possible. After all the controllers were designed, the cascade control structure for simultaneous position and stiffness control was successfully evaluated in a laboratory setup. Thus, the presented control approach is simple to implement, but with a performance that ensures a pulling constraint for tendon-driven actuators as a foundation for bioinspired antagonistic VSAs. [ABSTRACT FROM AUTHOR]

Recently, pneumatic artificial muscles (PAMs), a lightweight and high-compliant actuator, have been increasingly used in assistive rehabilitation robots. PAM-based applications must overcome two inherent drawbacks. The first is the nonlinearity due to the compressibility of the air, and the second is the hysteresis due to its geometric construction. Because of these drawbacks, it is difficult to construct not only an accurate mathematical model but also a high-performance control scheme. In this paper, the discrete-time fractional order integral sliding mode control approach is investigated to deal with the drawbacks of PAMs. First, a discrete-time second order plus dead time mathematical model is chosen to approximate the characteristics of PAMs in the antagonistic configuration. Then, the fractional order integral sliding mode control approach is employed together with a disturbance observer to improve the trajectory tracking performance. The effectiveness of the proposed control method is verified in multi-scenario experiments using a physical actuator. [ABSTRACT FROM AUTHOR]

Recently, pneumatic artificial muscles (PAMs), a lightweight and high-compliant actuator, have been increasingly used in assistive rehabilitation robots. PAM-based applications must overcome two inherent drawbacks. The first is the nonlinearity due to the compressibility of the air, and the second is the hysteresis due to its geometric construction. Because of these drawbacks, it is difficult to construct not only an accurate mathematical model but also a high-performance control scheme. In this paper, the discrete-time fractional order integral sliding mode control approach is investigated to deal with the drawbacks of PAMs. First, a discrete-time second order plus dead time mathematical model is chosen to approximate the characteristics of PAMs in the antagonistic configuration. Then, the fractional order integral sliding mode control approach is employed together with a disturbance observer to improve the trajectory tracking performance. The effectiveness of the proposed control method is verified in multi-scenario experiments using a physical actuator.

This paper presents the development and control of a novel asymmetric antagonistic actuation scheme characterized by large energy storage capacity that enables efficient execution of motions. The asymmetric design consists of two actuation branches that transfer their power to a single joint through two compliant elements with different stiffness and storage capacity properties. The guideline for selecting the stiffness of both elements is elaborated, given the design parameters and control requirements. We propose a novel control strategy that distributes the effort required to generate the motion using the two actuation branches of this novel hardware, to drive the prototype joint in an energy efficient manner. As a proof of concept, a single degree-of-freedom knee-actuated hopping robot is designed for experimental validation. The dynamics of the leg and actuators are rigorously modeled and formulated. The data from simulation and experimental studies demonstrate a significant improvement in electrical energy efficiency and reduction in torque requirements. [ABSTRACT FROM PUBLISHER]

Novel anthropomorphic robotic systems increasingly employ variable impedance actuation with a view to achieving robustness against uncertainty, superior agility and improved efficiency that are hallmarks of biological systems. Controlling and modulating impedance profiles such that they are optimally tuned to the controlled plant is crucial in realizing these benefits. In this work, we propose a methodology to generate optimal control commands for variable impedance actuators under a prescribed tradeoff of task accuracy and energy cost. We employ a supervised learning paradigm to acquire both the plant dynamics and its stochastic properties. This enables us to prescribe an optimal impedance and command profile (i) tuned to the hard-to-model plant noise characteristics and (ii) adaptable to systematic changes. To evaluate the scalability of our framework to real hardware, we designed and built a novel antagonistic series elastic actuator (SEA) characterized by a simple mechanical architecture and we ran several evaluations on a variety of reach and hold tasks. These results highlight, for the first time on real hardware, how impedance modulation profiles tuned to the plant dynamics emerge from the first principles of stochastic optimization, achieving clear performance gains over classical methods that ignore or are incapable of incorporating stochastic information. [ABSTRACT FROM AUTHOR]