Optimal fuzzy logic-based control strategy for lower limb rehabilitation exoskeleton

Abstract

In recent times, several control engineers have been working towards development of efficient rehabilitation exoskeletons for mobility impairments. This work aims at implementation of an optimal fuzzy logic-based control strategy for a lower limb exoskeleton application wherein the control parameters for the proposed control approach are obtained by a recently developed optimization technique named as dragon fly algorithm (DFA). For analysis of appropriately tuned closed-loop control, a comparative study between two optimization techniques namely DFA and genetic algorithm (GA) applied to a 2-degree of freedom (dof) nonlinear and coupled lower-limb exoskeleton, is presented. To see the practical aspects, a three-dimensional simscape model of the 4-dof lower limb exoskeleton is developed to observe the closed-loop performance of fuzzy logic proportional–integral–derivative (FLC-PID) controller for bipedal human walking. Experimental data for different speeds during treadmill walking is captured with electronic wireless goniometer, and is used to validate the bipedal walking control for the designed lower-limb exoskeleton. The results are further compared with traditional PID controllers in order to see the effectiveness of the proposed control approaches. Furthermore, the robustness testing of the proposed control schemes is also investigated for different speeds of human walking. This study presents a closed-loop control design for the development of a low-cost lower limb exoskeleton to restore normal gait for persons with mobility disorders, stroke or elderly persons.