RESUMO A lógica fuzzy pode simular a produtividade do trigo auxiliando na previsibilidade de safras. Objetivou-se no estudo o uso de lógica fuzzy para simulação da produtividade do trigo nas condições de uso do nitrogênio junto aos efeitos de temperatura do ar e precipitação pluviométrica, nos principais sistemas de sucessão do cereal no sul do Brasil. O estudo foi conduzido nos anos de 2014, 2015 e 2016, em Augusto Pestana, RS, Brasil. O delineamento experimental foi o de blocos casualizados com quatro repetições em fatorial 4 x 3, para doses de N-fertilizante (0, 30, 60, 120 kg ha-1) e formas de fornecimento do nutriente [condição única (100%) no estádio fenológico V3 (terceira folha expandida); fracionada (70%/30%) no estádio fenológico V3/V6 (terceira e sexta folha expandida) e; fracionada (70%/30%) no estádio fenológico V3/E (terceira folha expandida e início do enchimento de grãos)], respectivamente, no sistema soja/trigo e milho/trigo. As funções de pertinências e os valores linguísticos estabelecidos para as variáveis de entrada e de saída se mostram adequados para o uso da lógica fuzzy. A lógica fuzzy simula com eficiência a produtividade de grãos de trigo nas condições de uso do nitrogênio com temperatura do ar e precipitação pluviométrica nos sistemas de cultivo.

ABSTRACT Fuzzy logic can simulate wheat productivity by assisting crop predictability. The objective of the study is the use of fuzzy logic to simulate wheat yield in the conditions of nitrogen use, together with the effects of air temperature and rainfall, in the main cereal succession systems in Southern Brazil. The study was conducted in the years 2014, 2015 and 2016, in Augusto Pestana, RS, Brazil. The experimental design was a randomized block design with four repetitions in a 4 x 3 factorial scheme for N-fertilizer doses (0, 30, 60, 120 kg ha-1) and nutrient supply forms [100% in phenological stage V3 (third expanded leaf); (70%/30%) in the phenological stage V3/V6 (third and sixth expanded leaf) and; fractionated (70%/30%) at the phenological stage V3/E (third expanded leaf and beginning of grain filling)], respectively, in the soybean/wheat and corn/wheat systems. The pertinence functions and the linguistic values established for the input and output variables are adequate for the use of fuzzy logic. Fuzzy logic simulates wheat grain yield efficiently in the conditions of nitrogen use with air temperature and rainfall in crop systems.

ABSTRACT This research aims to improve the study about the stability of truss structures used in pivot irrigation, widely used due to the growing demand for food production, when submitted to wind effects. Specifically, it aims to verify the maximum wind speed supported by an irrigation center pivot structure when submitted to the load effects caused by wind gusts perpendicular to the equipment. In order to determine these forces and their effects on the irrigation equipment, computational numerical investigations were carried out using finite element bar models validated by measuring the natural frequency of the equipment in the field. A span was designed based on the existing standards in Brazil and the dynamic response of the structure was examined under the effects of wind gusts. Models of the Brazilian standard NBR 6123/88 for structures submitted to wind effects were used in this study. The studied irrigation equipment supports wind gusts of up to 115 km/h applied perpendicularly, with a duration of 3 s, before generating toppling.

This paper proposes a cascade controller with friction compensation based on the LuGre model. This control is applied to a pneumatic positioning system. The cascade methodology consists of dividing the pneumatic positioning system model into two subsystems: a mechanical subsystem and a pneumatic subsystem. This division allows the introduction of friction compensation at force level in the pneumatic positioning system. Using Lyapunov's direct method, the convergence of the tracking errors is shown under the assumption that the system parameters are known. Experimental results illustrate the main characteristics of the proposed controller.