Two new and efficient approaches are presented to improve the local and global estimation of the Takagi‐Sugeno (T‐S) fuzzy model. The main aim is to obtain high function approximation accuracy and fast convergence. The main problem is that the T‐S identification method can not be applied when the membership functions are overlapped by pairs. The approaches developed here can be considered as generalized versions of T‐S method with optimized performance. The first uses the minimum norm approach to search for an exact optimum solution at the expense of increasing complexity and computational cost. The second is a simple and less computational method, based on weighting of parameters. Illustrative examples are chosen to evaluate the potential, simplicity and remarkable performance of the proposed methods and the high accuracy obtained in comparison with the original T‐S model. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

This paper presents an online C compiler designed so that students can program their practical assignments in Programming courses. What is really innovative is the self‐assessment of the exercises based on black‐box tests and train students’ skill to test software. Moreover, this tool lets instructors, not only proposing and classifying practical exercises, but also evaluating automatically the efforts dedicated and the results obtained by the students. The system has been applied to the 1st‐year students at the Industrial Engineering specialization at the Universidad Politecnica de Madrid. Results show that the students obtained better academic performance, reducing the failure rate in the practical exam considerably with respect to previous years, in addition that an anonymous survey proved that students are satisfied with the system because they get instant feedback about their programs. © 2015 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:887–896, 2015; View this article online atwileyonlinelibrary.com/journal/cae; DOI10.1002/cae.21660.