Design and Analysis of an Adaptive Fuzzy Iterative Learning Controller with Feedback Structure

• Main Authors: Hen-Li Lin, 林恆立
• Other Authors: Chiang-Ju Chien
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/86838839145363099384

碩士 === 華梵大學 === 電子工程學系碩士班 === 98 === This thesis discusses the design, analysis and simulation of iterative learning controller for discrete time nonlinear system with input disturbance and output measurement noise. The main structure of the iterative learning controller is designed under a feedback control loop. The learning gain of the iterative learning controller is constructed by using a fuzzy logic system such that the learning speed can be increased and the learning performance can be improved. In this thesis, we prove that the learning error of the proposed iterative learning controller can be guaranteed to converge to a residue set if the learning gain satisfies some certain condition. Furthermore, the residual set will depend on the magnitude of input disturbance and output measurement noise. If the input disturbance and output measurement noise disappear, then the learning error will converge to zero. In addition to the theoretical analysis, a lot of computer simulation examples are given to prove the feasibility and correctness of the proposed adaptive fuzzy iterative learning controller with feedback structure. In the first example, we choose a single input single output discrete time nonlinear system to discuss the differences of learning performance among the traditional iterative learning controller, the adaptive fuzzy iterative learning controller and the adaptive fuzzy iterative learning controller with feedback structure. The second example is a two link robot manipulator. The dynamic model is transformed into a sampled data formulation. The learning performance is also studied extensively among the three kind of iterative learning controllers. According to the simulation results, it is shown that the proposed adaptive fuzzy iterative learning controller with feedback structure is feasible with better learning performance.