TY - JOUR
T1 - Multi-Objective Optimization of Impedance Parameters in a Prosthesis Test Robot
AU - Khalaf, Poya
AU - Richter, Hanz
AU - van den Bogert, Antonie J.
AU - Simon, Daniel J.
N1 - Khalaf, P., Richter, H., van den Bogert, A.J., 2016, "Multi-Objective Optimization of Impedance Parameters in a Prosthesis Test Robot," pp. V003T42A003.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - 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
AB - 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
UR - https://engagedscholarship.csuohio.edu/enme_facpub/319
UR - http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=2482039
UR - https://engagedscholarship.csuohio.edu/enece_facpub/332
U2 - 10.1115/DSCC2015-9848
DO - 10.1115/DSCC2015-9848
M3 - Article
VL - 3
JO - ASME 2015 Dynamic Systems and Control Conference
JF - ASME 2015 Dynamic Systems and Control Conference
ER -