Development and Control of an upper Limb Rehabilitation Robot via Ant Colony Optimization -PID and Fuzzy-PID Controllers

The control of movement rehabilitation robots is necessary for the recovery of physically disabled patients and is an interesting open problem. This paper presents a mathematical model of the upper limb rehabilitation robot using Euler-Lagrange approach. Since the PID controller is one of the most popular feedback controllers in the control strategy due to its simplicity, we proposed an ACO-PID controller for an upper limb rehabilitation robot. The main part of designing the PID controller is determining the gains of the controller. For this purpose, we used Ant Colony Optimization Algorithm (ACO) to tune the coefficients. To evaluate the validity of the proposed controller, we have compared it to Fuzzy-PID controller and the PID controller adjusted with the Ziegler-Nichols method (ZN-PID). The results showed that the performance of the ACO-PID controller is better than the others. Also, the adaptive PID controllers (ACO-PID and Fuzzy-PID) ensure accurate tracking, finite-time convergence, and stability. The results showed that the mean absolute error and normalized root mean square (NRMS) of tracking error using the ACO-PID are less than that using the Fuzzy-PID and ZN-PID controller. © 2022 Materials and Energy Research Center. All rights reserved.