Optimal Design of a RISE Feedback Controller for a 3-DOF Robot Manipulator Using Particle Swarm Optimization

Abstract

Abstract-This paper presents an application of recently proposed robust integral of the sign of the error (RISE) feedback control scheme for a three degrees-of-freedom (DOF) robot manipulator tracking problem. This method compensates for nonlinear disturbances and uncertainties in the dynamic model, and results in asymptotic trajectory tracking. To avoid selecting parameters of the RISE controller by time-consuming trial and error method, particle swarm optimization (PSO) algorithm is employed. The objective of the PSO algorithm is to find a set of parameters that minimizes the mean of root squared error as the fitness function. The proposed method attains tracking goal, without any chattering in control input. Indeed, the existence of a unique integral sign term in the RISE controller avoids the occurrence of chattering phenomenon that usually happens in sliding mode controllers. Numerical simulations demonstrate the effectiveness of the proposed control scheme.Index Terms-Robust integral of the sign of the error (RISE), Asymptotic tracking, 3degrees-of-freedom robot manipulator, particle swarm optimization (PSO)

Direct adaptive fractional-order non-singular terminal sliding mode control strategy using extreme learning machine for position control of 5-DOF upper-limb exoskeleton robot systems

“…Different control approaches have been introduced to position control of upper-limb exoskeleton robots such as iterative learning (Tu et al, 2017), robust control (Yazdanzad et al, 2015), adaptive (Wang et al, 2020), adaptive neural backstepping (Aly et al, 2022), and fuzzy controller (Razzaghian, 2022). Sliding mode control (SMC) is a nonlinear robust conventional control strategy for position controlling of the upper-limb exoskeleton robots due to their robustness against external disturbance and uncertainty (Zhang et al, 2021).…”