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.

中文翻译：

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膝关节外骨骼下肢功能康复优化自适应控制

下肢外骨骼机器人在康复、运动辅助和力量增强方面具有巨大潜力。考虑到患者之间的病理差异，设计控制以保证所需的最佳援助仍然是一个挑战。在本文中，我们提出了一种基于粒子群优化（PSO）算法的最优自适应控制方案。所提出的控制器基于众所周知的膝关节外骨骼动态模型，并使用优化算法来最小化平方误差适应度函数，从而量化跟踪性能。控制参数根据系统阶跃响应的一些非线性约束和边界约束进行调整。数值模拟结果显示了所提出方法的有效性和高性能。