Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements

Abstract

Background Currently, control of exoskeletons in rehabilitation focuses on imposing desired trajectories to promote relearning of motions. Furthermore, assistance is often provided by imposing these desired trajectories using impedance controllers. However, lower-limb exoskeletons are also a promising solution for mobility problems of individuals in daily life. To develop an assistive exoskeleton which allows the user to be autonomous, i.e. in control of his motions, remains a challenge. This paper presents a model-based control method to tackle this challenge. Methods The model-based control method utilizes a dynamic model of the exoskeleton to compensate for its own dynamics. After this compensation of the exoskeleton dynamics, the exoskeleton can provide a desired assistance to the user. While dynamic models of exoskeletons used in the literature focus on gravity compensation only, the need for modelling and monitoring of the ground contact impedes their widespread use. The control strategy proposed here relies on modelling of the full exoskeleton dynamics and of the contacts with the environment. A modelling strategy and general control scheme are introduced. Results Validation of the control method on 15 non-disabled adults performing sit-to-stand motions shows that muscle effort and joint torques are similar in the conditions with dynamically compensated exoskeleton and without exoskeleton. The condition with exoskeleton in which the compensating controller was not active showed a significant increase in human joint torques and muscle effort at the knee and hip. Motor saturation occurred during the assisted condition, which limited the assistance the exoskeleton could deliver. Conclusions This work presents the modelling steps and controller design to compensate the exoskeleton dynamics. The validation seems to indicate that the presented model-based controller is able to compensate the exoskeleton.

Simulation of Stand-to-Sit Biomechanics for Design of Lower-Limb Exoskeletons and Prostheses with Energy Regeneration

“…Using subject-specific inverse dynamics modelling, this research computed maximum hip, knee, and ankle joint torques during stand-to-sit movements of approximately 0.7 ± 0.1 Nm/kg, 1.1 ± 0.3 Nm/kg, and 0.4 ± 0.1 Nm/kg, respectively. In comparison, previous investigations involving the mechatronic design and evaluation of lower-limb exoskeletons and prostheses for sitting and standing movements reported maximum knee joint torques ranging from 0.8-1.0 Nm/kg [36,[38][39][40]. The relatively good quantitative agreement between the current (1.1 ± 0.3 Nm/kg) and previous (0.8-1.0 Nm/kg) [36,[38][39][40] maximum normalized knee joint torques for sitting and standing movements further supported the model validation.…”

“…The average human performs approximately 60 sitting and standing movements each day [36]. Several robotic lower-limb prostheses and exoskeletons have been designed and evaluated for sitting and standing movements (example shown in Figure 2) [7][8][9][36][37][38][39][40][41][42].…”

“…Sitting and standing movement durations were defined when the smoothed pelvis translational velocities exceeded some subject-specific percentage of their maximum values; optimal percentages were approximated through trial-and-error simulations for consistent results. Other investigations have used changes in vertical ground reaction forces [36,44] and knee and hip joint kinematics [40][41] for defining the sitting and standing movement durations. The force plate measurements were filtered using 10thorder low-pass Butterworth filters with 30 Hz cut-off frequencies and zero-phase digital filtering [12].…”

Feedback Control Design for Robust Comfortable Sit-to-Stand Motions of 3D Lower-Limb Exoskeletons

“…When formulating a sit-to-stand controller design, it is very important to determine whether the exoskeleton will be providing complete assistance or only assistance as needed. Trajectory tracking is generally employed to achieve standing motions for complete assistance, whereas, with assistance as needed, it is important to first estimate the user's intent and then complement the user's effort [16], [19], [24], [25]. This paper focuses on complete assistance.…”

“…To robustly perform the sit-to-stand motion, it is important that the chosen controller can track a desired trajectory in the presence of disturbances. There are several controllers that have been used in literature such as the computed-torque or input-output feedback linearization controller [10], [14], [22], [24], sliding mode controller [18], fuzzy controller [47], proportional-integral-derivative based controller [19], [27], [29], [48], impedance controller [15], and LQR [10], [31].…”