Abstract
This research work aims at realizing a new compliant robotic actuator for safe human-robotic interaction. In this paper, we present the modeling, control, and numerical simulations of a novel Binary-Controlled Variable Stiffness Actuator (BcVSA) aiming to be used for the development of a novel compliant robotic manipulator. BcVSA is the proof of concept of the active revolute joint with the variable recruitment of series-parallel elastic elements. We briefly recall the basic design principle which is based on a stiffness varying mechanism consisting of a motor, three inline clutches, and three torsional springs with stiffness values (K0, 2K0, 4K0) connected to the load shaft and the motor shaft through two planetary sun gear trains with ratios (4:1, 4:1 respectively). We present the design concept, stiffness and dynamic modeling, and control of our BcVSA. We implemented three kinds of Multiple Model Predictive Control (MPC) to control our actuator. The main motivation of choosing this controller lies in the fact that working principle of multiple MPC and multiple states space representation (stiffness level) of our actuator share similar interests. In particular, we implemented Multiple MPC, Multiple Explicit MPC, and Approximated Multiple Explicit MPC. Numerical simulations are performed in order to evaluate their effectiveness for the future experiments on the prototype of our actuator. The simulation results showed that the Multiple MPC, and the Multiple Explicit MPC have similar results from the robustness point of view. On the other hand, the robustness performance of Approximated Multiple Explicit MPC is not good as compared to other controllers but it works in the offline framework while having the capability to compute the sub-optimal results. We also performed the comparison of MPC based controllers with the Computed Torque Control (CTC), and Linear Quadratic Regulator (LQR). In future, we are planning to test the presented approach on the hardware prototype of our actuator.
Highlights
Several aspects and design requirement have been raised to enhance the quality of human-robot interaction and co-work collaborations in smart manufacturing and domestic scenarios (Bicchi et al, 2008; Tsagarakis et al, 2011; Gan et al, 2012; Asota et al, 2017)
We performed total six case studies, out of which, five case studies focused on the evaluation of the performance of each Multiple Model Predictive Control (MPC) controller under different applied conditions while the sixth case study compares the performance of the system under
The last case study focused on comparing the performance of the system when the following controllers are used: Multiple MPC, Multiple Explicit MPC, Approximated Explicit MPC, Computed Torque Control (CTC), and Linear Quadratic Regulator (LQR)
Summary
Several aspects and design requirement have been raised to enhance the quality of human-robot interaction and co-work collaborations in smart manufacturing and domestic scenarios (Bicchi et al, 2008; Tsagarakis et al, 2011; Gan et al, 2012; Asota et al, 2017). Bio-inspired robotics design results in compliant robotic systems with improvement natural dynamics and kinematics performance (Hogan, 1985; Migliore et al, 2005; Shin et al, 2010) These improvements have led to the development of variable impedance actuators (VIA), of which the actuator mechanical properties (inertia, damping, or stiffness) affect the system equilibrium position (Bicchi et al, 2008). This alters the interaction forces in order to adapt the different situations between the robots and the environment/users, leading to safer energy efficient operations (Bicchi et al, 2008)
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