Journal Article

Command filtered backstepping control of constrained flexible joint robotic manipulator

Vafamand, Navid, Homayoun, Behrouz, Arefi, Mohammad Mehdi, Davoodi, Mohammadreza

2023

Overview

Here, an adaptive radial basis function (RBF) neural network (NN) backstepping controller is proposed for a class of input‐constrained flexible joint robotic manipulators represented by strict‐feedback form with unknown terms, external stochastic disturbance, and output disturbance. The proposed approach is robust against both deterministic and stochastic uncertainties and disturbances and copes with the control input amplitude saturation. Moreover, by deploying the minimal learning parameter method and command filter technique, the computational burden of derivative terms and adaptive terms greatly decreases. Considering the mean‐value theorem assists us to avoid the need for having the input saturation bounds in prior. The suggested tracking control scheme mandates the closed‐loop system states to be semi‐globally bounded‐in‐probability. Also, a quartic Barrier Lyapunov function is utilized to force the tracking error to be confined within a pre‐chosen small region around the origin. Eventually, a numerical simulation of a flexible joint robot manipulator with a single link is performed to show the effectiveness and performance of the developed control method. An adaptive neural network backstepping controller is proposed for input‐constrained flexible joint robotic manipulators with unknown terms, external stochastic disturbance, and output disturbance. Deploying the minimal learning parameter and command filter techniques decreases the computational burden. Considering the mean‐value theorem avoids the pre‐need for input saturation bounds. The quartic Barrier Lyapunov function confines the tracking error and mandates semi‐globally bounded‐in‐probability.

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: adaptive neural tracking control / Closed loop systems / command filter / Constraints / Control methods / Controllers / flexible joint robotic manipulator / input saturation / Liapunov functions / Manipulators / minimal learning parameter / Neural networks / Parameter robustness / Parameter uncertainty / Radial basis function / Robot arms / Robot control / Robotics / Robots / Robust control / stochastic non‐linear systems / Tracking control / Tracking errors