Management of human-robot interaction in order to control of ankle knee during walking

Patients who have had a stroke or a traumatic brain injury are usually motor-impaired. Nerve damage can cause lower limb paralysis and impair walking. Survivors of stroke with varying degrees of motor dysfunction not only experience the discomfort of daily living, but also feel a great deal of stress along with the economic burden on the family and society. Many types of rehabilitation robots have been developing to aid rehabilitation in people with stroke. In this study, a new method for knee joint control using rehabilitation robots based on human-robot interaction process is present. The control process is based on quadriceps data when walking for a healthy human, using fuzzy rules designed to control the contribution of humans and robots to the walking process. The main purpose of this study was to present and simulate a smart solution to determine the amount of human and robot presence in knee motion correction in patients with stroke and cerebral palsy. Dynamic modeling using two-dimensional mapping of Hunan is use instead of humans and the robot model is a PID controller whose coefficients are determined using the Ziegler-Nigel's method. The results show that the proposed model has been able to follow the knee angle curve with fuzzy system. Moreover, our results show that using a fuzzy system can lift the pressure on a person and help him walk. The proposed PID system can also play a significant role in reducing the fuzzy system error. The proposed control system without the presence of fuzzy system has an RMS error of 181/3 and also the RMS error in the presence of fuzzy system is equal to 0.698 indicating that the proposed control system is functioning properly.