Nonlinear Identification on Feedback Linearizatin Control of a Two-link Robot Manipulator-Radial Basis Function Method and Kolmogorov-Gabor Method

• Main Authors: Chio, E.L., 邱奕郎
• Other Authors: Shiaw-Wu Chen
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/00066204874398313824

碩士 === 逢甲大學 === 自動控制工程研究所 === 84 === This thesis studies two nonlinear identification methods, the radial basisfunction method and the Kolmogorov-Gabor polynomial method, applied on thecontrol of atwo-link robot manipulator. It is well known that two-link robotmanipulators are highly nonlinear systems. A feedback linearization method isapplied to linearize the system. After that, a PID controller is employed tocontrol the linearized system. In the linearization loop, nonlinear functionmust be given. Usually, these nonlinear functions are obtained by thederivation of the system model. In contrast, this thesis uses two nonlinearidentification methods to get these nonlinear functions without knowing thesystem parameters. Simulation results show that both nonlinear identificationmethods work well for the set-point control of robot manipulators. However, asimple decoupling test is performed and shows that the Kolmogorov-Gaborpolynomial method is better than the radial basis function method. This mayhint that, in many nonlinear identification methods, whether one can select amethod whose bases' functions are close to the nonlinear system is veryimportant.