In order to take full advantage of the multisensor information, a MIMO fuzzy control system based on semitensor product (STP) is set up for mobile robot odor source localization (OSL). Multisensor information, such as vision, olfaction, laser, wind speed, and direction, is the input of the fuzzy control system and the relative searching strategies, such as random searching (RS), nearest distance-based vision searching (NDVS), and odor source declaration (OSD), are the outputs. Fuzzy control rules with algebraic equations are given according to the multisensor information via STP. Any output can be updated in the proposed fuzzy control system and has no influence on the other searching strategies. The proposed MIMO fuzzy control scheme based on STP can reach the theoretical system of the mobile robot OSL. Experimental results show the efficiency of the proposed method.

Abstract. Traditionally, potential evaluation methods for farmland consolidation have depended mainly on the experts' experiences, statistical computations or subjective adjustments. Some biases usually exist in the results. Thus, computer-aided technology has become essential. In this study, an intelligent evaluation system based on a fuzzy decision tree was established, and this system can deal with numerical data, discrete data and symbolic data. When the original land data are input, the level of potential of the agricultural land for development will be output by this new model. The provision of objective proof for decision-making by authorities in rural management is helpful. Agricultural land data characteristically comprise large volumes, complex varieties and more indexes. In land consolidation, it is very important to construct an effective index system. A group of indexes need to be selected for land consolidation. In this article, a fuzzy measure was adopted to accomplish the selection of specific features. A fuzzy integral based on a fuzzy measure is a type of fusion tool. The optimal solution with the fewest non-zero elements was obtained for the fuzzy measure by solving a fuzzy integral. This algorithm provides a quick and optimal way to identify the land-index system when preparing to conduct land consolidation. This new research was applied to Shunde's "Three Old" consolidation project which provides the data. Our estimation system was compared with a conventional evaluation system that is still accepted by the public. Our results prove to be consistent, and the new model is more automatic and intelligent. The results of this estimation system are significant for informing decision-making in land consolidation.

In order to make full use of the multiple sensor information, the different behavior strategies with different priorities are set up. Behaviors with higher-priorities can subsume or inhibit the behavior with lower priority by suppressing their outputs, which makes the robot generate an optimization strategy to deal with the dynamic, complex and unstructured environments. However, the behavior of lower priority continues to function as higher priority behaviors are added. Experimental results show the efficiency of the proposed method.

A new kind of scheme is proposed to obtain hierarchical fuzzy control of multivariable systems. It is based on algebraic fuzzy reasoning equations of fuzzy system using semi-tensor product framework recently described. First, the bi-decomposition of multivariable fuzzy systems is considered, and some new results are obtained. Using these results, the algorithm of hierarchical fuzzy systems realization is developed such that one can easily design the middle layers of the hierarchical structure. The resulting hierarchical system is totally equivalent to the conventional single layer fuzzy logic system. At last, an example is given to demonstrate that the algorithm is effective and feasible.

No abstract