Portable exoskeleton is directed at providing necessary support and help for loaded legged locomotion. The kernel of whole mechanical construction of the exoskeleton is lower extremities. The lower extremities consist of exoskeleton thigh, exoskeleton shank, hydraulic cylinder and corresponding joints. In order to find the optimal combination of design parameters of lower extremities, an improved particle swarm optimization algorithm based on simulated annealing is proposed. To improve global and local search ability of the proposed approach, the inertia weight is varied over time, and jumping probability of simulated annealing is adopted in updating the position vector of particles. Experimental results show that the improved algorithm can obtain the optimal design solutions stably and effectively with less iteration compared to the standard particle swarm optimization and simulated annealing; using ANSYS software build finite element model with the optimization result, then analyzes the strength of the model, these stress results verify the of accuracy of the improved particle swarm optimization.
Improved Particle Swarm Optimization Geomagnetic Matching Algorithm Based on Simulated Annealing
