Multi-Objective Optimization of Impedance Parameters in a Prosthesis Test Robot
Document Type
Conference Proceeding
Publication Date
2015
Publication Title
ASME 2015 Dynamic Systems and Control Conference
Abstract
We design a control system for a prosthesis test robot that was previously developed for transfemoral prosthesis design and test. The robot’s control system aims to mimic human walking in the sagittal plane. It has been seen in previous work that trajectory control alone fails to produce human-like forces. Therefore, we utilize an impedance controller to achieve reasonable tracking of motion and force simultaneously. However, these objectives conflict. Impedance control design can therefore be viewed as a multi-objective optimization problem. We use an evolutionary multi-objective strategy called Multi-Objective Invasive Weed Optimization (MOIWO) to design the impedance controller. The multi-objective optimization problem admits a set of equally valid alternative solutions known as the Pareto optimal set. We use a pseudo weight vector approach to select a single solution from the Pareto optimal set. Simulation results show that a solution that is selected for pure motion tracking performs very accurate motion tracking (RMS error of 0.06 cm) but fails to produce the desired forces (RMS error of 70% peak load). On the other hand, a solution that is selected for pure force tracking successfully tracks the desired force (RMS error of 12.7% peak load) at the expense of motion trajectory errors (RMS error of 4.5 cm).
Copyright © 2015 by ASME
Repository Citation
Khalaf, Poya; Richter, Hanz; van den Bogert, Antonie J.; and Simon, Daniel J., "Multi-Objective Optimization of Impedance Parameters in a Prosthesis Test Robot" (2015). Electrical and Computer Engineering Faculty Publications. 332.
https://engagedscholarship.csuohio.edu/enece_facpub/332
Original Citation
P. Khalaf, H. Richter, A. van den Bogert, and D. Simon, "Multi-Objective Optimization of Impedance Parameters in a Prosthesis Test Robot," ASME Dynamic Systems and Control Conference, Columbus, OH, October 2015.
DOI
10.1115/DSCC2015-9848
Volume
3
Comments
Paper No. DSCC2015-9848. Research supported by NSF Grant 1344954.