Multi-objective optimization of tracking/impedance control for a prosthetic leg with energy regeneration

Daniel J. Simon, Cleveland State University


The focus of this research is to consider control and energy regeneration for a robotic manipulator with both actively and semi-actively controlled joints. The semi-active joints are powered by a regenerative scheme. The problem of designing an impedance controller to track a desired joint trajectory and regenerate energy in the storage element is considered here as a multi-objective optimization problem. Nondominated sorting biogeography-based optimization is used for this purpose. To validate the performance of system, a prosthetic leg which imitates able-bodied gait is considered. A Pareto front is obtained where a pseudo-weight scheme is used to select among solutions. A solution with minimum tracking error (0.0009 rad) fails to regenerate energy (loses 21.56 J), while a solution with poor tracking (0.0288 rad) regenerates energy (gains 167.3 J). A tradeoff results in fair tracking (0.0157 rad) and fair energy regeneration (52.9 J). Results verify that it is possible to regenerate energy at the semi-active joint while still obtaining acceptable tracking. The results indicate that ultracapacitor systems and advanced controls/optimization have the potential to significantly reduce external power requirements in powered prostheses.