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EN
The paper deals with an inference system with probabilistic-fuzzy knowledge base as a tool which can help users in analyzing complete uncertainty of real problems in the company using fuzzy sets and probability. In the mentioned system, knowledge is saved in the weighted IFTHEN fuzzy rules, where the weights constitute marginal probabilities of the fuzzy events in the antecedents and conditional probabilities of the fuzzy events in the consequents. Moreover, the paper presents a proposal of the use of fuzzy association rules as a method of automatic knowledge base extraction in the inference system. For this purpose a modification of the PF-Growth algorithm is described. A numerical example is analyzed by using wind speed prediction process. The correct estimation of wind speed, as the potential energy resource, is necessary for control of the wind turbine work and it is important for the localization process of wind turbines, production planning and estimating cost-effectiveness of such investments.
PL
The development and realization of mobile robots and their control system presents a major challenge to engineers of the three disciplines mechanical engineering, electrical engineering and software engineering. In this paper the successful realization of a mobile robot for production logistics at the Hochschule Ravensburg-Weingarten is described. The unique characteristic of this mobile robot is its steering principle. This patented steering principle is based on the usage of torque differences between individually driven wheels, which can align into the direction of the desired robot path. This steering principle leads to excellent maneuverability but requires an elaborate control system. The first feedback of the industrial partner was very positive.
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