  Lower limb exoskeleton robots hold great potential for rehabilitation,
movement assistance, and strength augmentation. Design control to guarantee
optimal needed assistance is still a challenge considering the pathological
variances between patients. In this paper, we proposed an optimal adaptive
control scheme based on Particle Swarm Optimization (PSO) Algorithm. The
proposed controller is based on a well-known dynamic model of the knee joint
exoskeleton, and the optimization algorithm is used to minimize a square error
fitness function, which quantifies tracking performances. Control parameters
are tuned respecting some nonlinear constraints for step response of the system
and boundaries constraints. Numerical simulation results are presented to show
the validity and the high performances of the proposed approach.
