Handling subject arm uncertainties for upper limb rehabilitation robot using robust sliding mode control

摘要: Upper Limb Rehabilitation Robots (ULRR) for the patient having shoulder and elbow joint movement disorders, requires further study development. One aspect that must be fulfilled by such robots, is need to handle uncertainties due biomechanical variation of different patients, without significantly degrading performance. Currently, rehabilitation robots require re-tuning controller gain each individual. This time consuming process expert training. To overcome this problem, we propose robust sliding mode control algorithm, which uses very basic information subject like weight, height, age gender these model uncertainties. For analysis, have compared our proposed algorithm with Robust Computed Torque Control (RCTC) Boundary Augmented Sliding Mode (BASMC) algorithms diverse subjects. Results describe superiority in handling uncertain parameters human arm robot