Abstract: In this paper, a hybrid fuzzy modeling technique is described for an unknown system with a given set of numerical data. Nonlinear systems are difficult to model by conventional fuzzy systems because of problems such as the conflict between overfitting and underfitting, and low reliability. To overcome these problems, a great number of fuzzy rules and very complicated learning algorithms must be used. We propose the hybrid fuzzy modeling technique, which the combination of the fuzzy system and self-organizing approximators (polynomial neural networks: PNN). Fuzzy systems have been used successfully for imprecise data or not well-defined concepts. PNN is an…analysis technique used to identify nonlinear relations between system inputs and outputs and build hierarchical polynomial regressions of required complexity. Comparative studies of the proposed approach are presented for both Box-Jenkin data identification system and three-input nonlinear function to show the performance. The proposed method was efficient and much more accurate than previous other models because it used fewer fuzzy rules and had better generalization ability.
Show more
Keywords: Hybrid fuzzy model, fuzzy systems, self-organizing approximator, nonlinear system modeling, overfitting and underfitting
Abstract: Practical biped walking robot is presented in this paper. The biped walking robot is a popular research area in robotics because of the high adaptability of a walking robot in an unstructured environment. However, lots of circumstances which have to be taken into account make the biped robot control a challenging task. For the stability of the biped walking robot, the zero moment point (ZMP) trajectory in the robot foot support area is a significant criterion. If the ZMP during walking can be measured, it is possible to realize stable walking and to stably control the biped robot by the…use of the measured ZMP. So actual ZMP data are measured in real time situations from practical biped walking robot and the obtained ZMP data are modeled by fuzzy system to explain empirical laws of the robot. By the simulation results, the fuzzy system can be effectively used to model practical biped walking robot.
Show more