Active lower limb exoskeletons are increasingly used in rehabilitation therapy. An important aspect and ongoing research topic in developing such assistive devices is safe human–machine interaction. Another major challenge in the control of exoskeletons is determining the subject's intention to move for providing cooperative assistance. To address both challenges, we first present the design of a new lower limb exoskeleton with variable stiffness actuators for compliant coupling between human and robot. The exoskeleton's actuated hip, and knee joints are controlled via a stiffness-dependent torque control. In a second step, we derive a detailed model for the swing phase using the Lagrange formalism. We utilize the model and an interaction torque measurement based on the deflection of the serial elasticity to estimate the subject's motion intention. This estimation is realized by nonlinear state estimation using an unscented Kalman filter (UKF). The UKF is able to track the hip and knee torque contributed by the subject during normal gait in real time and provides more robust results than the inverse dynamics approach.

A Variable Stiffness Actuator (VSA) is an inherently parameter-dependent system due to the controllable stiffness element. Within the torque-controlled framework, the VSA is distinguished from the classical Series Elastic Actuator (SEA). A frozen torque controller can directly determine the SEA performance with a fixed-stiffness spring selection. However, since the VSA operates at a set of operating points, the aim is to achieve an adaptive control approach. For this, we propose a gain-scheduled torque controller. The control performance is expected to recover robustness when stiffness values are varied from smaller to larger ones. Simultaneously the bandwidth is maximized, taking into account hardware limitations. In this way, a good trade-off between stability and performance can be achieved. A key step in the gain-scheduled controller design is to implement the linear controllers, where the Linear Quadratic Gaussian (LQG) technique was applied to deal with the multiloop feedback (a cascade control scheme) in the VSA plant. A lever-arm based VSA (i.e. a mechanical-rotary variable impedance actuator (MeRIA)) was used to verify this new controller design approach by the simulations and experiments. The resulting gain-scheduled controller was also evaluated by taking into account the impedance control testing on a motion-supported platform for the knee joint.

This paper investigates a closed-loop torque-controlled variable stiffness actuator (VSA) combined with a disturbance observer for enhancing low output impedance. We implement the generalized extended state observer (GESO) for conveniently testing the stability of the time-varying VSA system. In our application, the GESO is also required to serve the operation of the low and high impedance task. Here, the most important aspect is to consider the influence of the physical stiffness on the output impedance, because the VSA has been regulated with the closed-loop torque control. Through the interaction-torque experiments, we verify that using the fast dynamics GESO with the low-stiffness actuator can achieve low output impedance and stable interaction under the reachable frequency of a human. These properties contribute to perform the low-impedance task. When performing the high-impedance task, where a large torque command is needed, the high-stiffness actuator and the slow dynamics GESO are implemented to achieve high bandwidth and proper tracking performance. The continuously variable observer responses in accordance with the stiffness values are achieved via the gain-scheduling control. Moreover, the present closed-loop linear parameter varying system can be verified to be quadratically stable. The VSA system is then implemented on a knee exoskeleton for a sit-to-stand application. The reference command of the exoskeleton is a joint torque, calculated from the inverse dynamics. This torque signal is also used as the reference command of the stiffness motor of the VSA. The effectiveness of the exoskeleton system is experimentally verified with one healthy volunteer. Subsequently, another two healthy volunteers also successfully experienced the system.

We present a framework for achieving a robust stability test of the variable stiffness actuator (VSA) exoskeleton programmed with the gain scheduling-based variable impedance control (GSVIC). In this brief, the focused impedance control framework involves the cascaded position torque control loop, in which both control loops are closed, and the index of the GSVIC is related to the joint torque of the human. However, there is a lack of research on the variation rate of such a biofeedback signal. This lack of information is necessary when performing the robust stability test of the linear parameter-varying (LPV) system. To acquire a bounded variation rate, the mechanical stiffness variation component of the VSA is used to transfer the biofeedback information into the GSVIC. In this case, the LPV system has only one variable parameter with the known and bounded variation rate, i.e., the physical stiffness of the VSA. The operating range of the impedance controller, determined from the test of robust stability via parameter-dependent Lyapunov functions, can meet our application requirements. The whole control system follows the paradigm of the variable impedance task in accordance with human intention. The effectiveness of the control scheme is experimentally verified on a VSA prototype and two subjects wearing the VSA exoskeleton.