Variable structure fuzzy control using three input variables for reducing motion tracking errors

Conventional fuzzy controllers for motion tracking utilize generally two input variables (position error and velocity error) to deal with highly nonlinear and time-varying dynamics associated with complex mechanical motion with multi- DOF. This results in some tracking errors at steady state, in general, mainly due to friction existing in mechanical systems. To eliminate the steady-state tracking errors, a variable structure fuzzy control algorithm is proposed using three input variables (position error, velocity error, and integral of position errors) and a switching logic between two inputs and three inputs. Simulation and experimental studies have been conducted to show the validity of the proposed control logic using a direct-drive SCARA manipulator with two degree-of-freedom. It has been shown that the proposed fuzzy control logic has significantly improved motion-tracking performance of the mechanical system when it is applied to complex polygon-tracking in Cartesian space with inverse kinematics and path planning. This paper was recommended for publication in revised form by Associate Editor Kyongsu Yi Chul-Goo Kang received his B.S. and M.S. degree in Mechanical Design and Production Engineering from Seoul National University, Korea, in 1981 and 1985, respectively. He then received his Ph.D. degree from Univ. of California, Berkeley in 1989. Dr. Kang is currently a Professor at the Department of Mechanical Engineering, Konkuk University in Seoul, Korea. He serves as a board member of the Institute of Control, Robotics and Systems, and also Korea Robotics Society. His research interests include motion and force control, train brakes, and intelligent robots.