Adaptive Fuzzy Sliding Mode and Robust Tracking Control for Manipulators with Uncertain Dynamics

Sanxiu Wang

doi:10.1155/2020/1492615

Abstract

In response to the issue of the trajectory tracking control problem of manipulators with uncertain parameters and external disturbance, an adaptive fuzzy sliding mode robust control algorithm is proposed. Sliding mode control (SMC) is adopted to perform robotic manipulator trajectory tracking control. Then, a fuzzy logic system is used for adaptive adjustment of switching gain of the SMC and to reduce the buffeting problem. Next, compensation is made by using the robust controller in consideration of the impacts of unmodeled dynamics and external disturbance. The simulation experiment on a two axes robotic manipulator shows that, with the proposed control method, the sliding mode control input signal is kept smooth, and the manipulator has high trajectory tracking precision.

Highlights

Sanxiu WangCollege of Electronic and Information Engineering, Taizhou University, Taizhou, Zhejiang 318000, China
Is method is simple; it cannot guarantee the output convergence. at is to say, there is a nonzero steadystate error in the output
Fuzzy control can approach any continuous function due to its characteristic of universal approximation and does not depend on the system model [14, 15]. It has gained wide applications in robot adaptive control. us, in this paper, a new adaptive fuzzy SMC algorithm is proposed for robotic manipulators. e adoption of the fuzzy logic system in adjusting the switching gain of SMC in an adaptive way can effectively eliminate the buffeting of the sliding mode control algorithm

Summary

Sanxiu Wang

College of Electronic and Information Engineering, Taizhou University, Taizhou, Zhejiang 318000, China. A series of achievements have been made in the research on the trajectory tracking of the manipulator’s joint space Control algorithms such as sliding mode control [1–3], adaptive control [4–6], robust control [7, 8], and iterative learning control [9] have been proposed. At is to say, there is a nonzero steadystate error in the output Another common method is to use a disturbance observer to estimate and compensate the external disturbance and uncertainty, so as to solve the chattering problem of sliding mode control [12, 13]. Its dynamic equation is described as follows [20]: M(q)q€ + C(q, q_)q_ + G(q) τ + d In this part, a control algorithm containing SMC, adaptive fuzzy control, and robust control is designed for robot trajectory tracking.

Robust τr controller q Robot

Taking ki ξ

Select the task space desired trajectory

Membership function

Expected velocity Actual velocity tracking