Controle em cascata de um atuador hidráulico utilizando redes neurais

No presente trabalho, é realizada a modelagem e identificação de um serovoposicionador hidráulico de uma bancada de testes. As expressões analíticas tradicionalmente utilizadas em uma estratégia em cascata aplicada ao controle de trajetória de posição são obtidas. A estratégia em questão utiliza, conjuntamente, a linearização por realimentação como lei de controle do subsistema hidráulico e a lei de controle de Slotine e Li no subsistema mecânico. Com base na mesma estratégia, um controlador em cascata neural é proposto. Em tal controlador, a função analítica que representa o mapa inverso, presente na linearização por realimentação, e a função de compensação de atrito utilizada na lei de Slotine e Li são substituídas por funções constituidas por meio de redes neurais de perceptrons de múltiplas camadas. Essas redes neurais têm como entradas os estados do sistema e também a temperatura do fluido hidráulico. O novo controlador é apresentado em uma versão onde as redes neurais são aplicadas sem modificações on-line e em outra, onde são apresentadas leis de controle adaptativo para as mesmas. A prova de estabilidade do sistema em malha fechada é apresentada em ambos os casos. Resultados experimentais do controle de seguimento de trajetórias de posição em diferentes temperaturas do fluido hidráulico são apresentados. Esses resultados demonstram a maior efetividade do controlador proposto em relação aos controladores clássicos PID e PID+feefforward e ao controlador em cascata com funções analíticas fixas. Os experimentos são realizados em duas situações: quando não ocorrem variações paramétricas importantes no sistema, onde é utilizado o controlador em cascata neural fixo e quando ocorrem essas variações, onde se utiliza o controlador em cascata neural adaptativo.In this work, the modeling and identification of a hydraulic actuator testing setup are performed and the analytical expressions that are used in a cascade control strategy applyied in a position trajectory tracking control are designed. Such cascade strategy uses the feedback linearization control law in the hydraulical subsystem and the Slotine and Li control law in the mechanical one. Based on this cascade strategy, a neural cascade controller is proposed, for which the analytical function used as inversion set in the feedback linearization control law and the friction function compensation of the Slotine and Li control law are replaced by multi layer perceptrons neural networks where the inputs are the states of the system and the hydraulic fluid temperature. The novel controller is introduced in two different aproachs: the first one where the neural networks do not have on-line modifications and the second one where adaptive control laws are proposed. For both of them the stability proof of the closed-loop system is presented. Experimental results about some position tracking controls performed in different fluid temperature are showed. The results show that the novel controller is more efective than the classical PID, PID+feedforward and the traditional analytical cascade controller. The experiments are performed in two different setups: considering the system without importants parametric variations where is applied the non adaptive cascade neural controller and in the presence of parametric variations where is applied the adaptive cascade neural controller

Um estudo de controladores robóticos utilizando redes neurais /

Dissertação (Mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico

A neural network-based inversion method of a feedback linearization controller applied to a hydraulic actuator

In this work, we use a neural network as a substitute for the traditional analytic functions employed as an inversion set in feedback linearization control algorithms applied to hydraulic actuators. Although very efective and with strong stability guarantees, feedback linearization control depends on parameters that are difcult to determine, requiring large amounts of experimental efort to be identifed accurately. On the other hands, neural networks require little efort regarding parameter identifcation, but pose signifcant hindrances to the development of solid stability analyses and/or to the processing capabilities of the control hardware. Here, we combine these techniques to control the positioning of a hydraulic actuator, without requiring extensive identifcation procedures nor losing stability guarantees for the closed-loop system, at reasonable computing demands. The efectiveness of the proposed method is verifed both theoretically and by means of experimental results

Indolbutyric Acid (IBA) in the african mahogany (Khaya grandifoliola C. DC.) cuttings and mini-cuttings development

The current expansion of the forest sector in the Cerrado (Brazilian Savannah), especially of the species of genus Khaya sp. (African Mahogany), requires several silvicultural and technical studies of various natures. Seed and clonal propagation enable noble and vigorous seedlings, which will future compose commercial plantations aiming timber production. The species Khaya grandifoliola C. DC is considered of distinct wood characteristics and with great economic potential. The objective of this work was to evaluate the effect of different indolbultyric acid (IBA) concentrations – between 0 and 12 g.L-1– on the rooting of K. grandifoliola cuttings and mini-cuttings. The experiment was carried out at the "Mudas Nobres" private nursery, located in Goiânia (Goiás State, Brazil). The experiment was conducted in a completely randomized design in a 5 × 2 factorial scheme. Each treatment consisted of four replications with 20 cuttings (clonal origin) or mini-cuttings (seed origin) per repetition. Models were also applied to estimate the number of shoots in clonal cuttings, according to the data observed in seed mini-cuttings. The results indicate that IBA has the opposite effect on the two evaluated types of propagule origin, being more suitable for seed mini-cuttings (should apply 8 g.L-1of IBA) and less for clonal cuttings (should not apply IBA). If a standard application must be recommended (to cuttings either mini-cuttings), the most appropriate concentration is 6 g.L-1of IBA

Agronomic and qualitative performance of common bean cultivars of carioca and special commercial groups in the winter season

No Brasil, existe uma ampla disponibilidade de cultivares de feijoeiro de vários grupos comerciais. Nesse sentido, estudos para avaliar o potencial produtivo dos genótipos são necessários para a indicação das melhores cultivares aos produtores. Objetivou-se avaliar o desempenho agronômico e qualitativo de cultivares de feijoeiro dos grupos comerciais carioca e especial e indicar os melhores genótipos dentro de cada grupo. O experimento de campo foi conduzido na Unesp, Jaboticabal, SP, na safra de inverno de 2017. Foram utilizadas dez cultivares de feijoeiro comum, sendo cinco do grupo comercial carioca: BRS Estilo, BRS MG Majestoso, BRS Ametista, BRS Notável e BRS Cometa e cinco do grupo comercial especial: BRS MG Realce, BRS Embaixador, BRS FC 305, BRS Executivo e BRS Ártico. O delineamento experimental foi o de blocos casualizados, com quatro repetições. Os resultados foram submetidos à análise de variância (Teste F) e as médias comparadas pelo teste de agrupamento de Scott-Knott a 5% de probabilidade. Para as características de desempenho agronômico, a cultivar BRS MG Majestoso se destacou dentro do grupo comercial carioca e as cultivares BRS Embaixador e BRS Executivo dentro do grupo comercial especial. Na qualidade dos grãos, se destacaram as cultivares BRS Estilo no grupo comercial carioca e a BRS Embaixador no grupo comercial especial.In Brazil, there is a wide availability of bean cultivars of various commercial groups. In this sense, studies to evaluate the productive potential of genotypes are necessary to indicate of the best cultivars to the producers. The objective was to evaluate the agronomic and qualitative performance of bean cultivars of the carioca and special commercial groups and indicate the best genotypes within each group. The field experiment was conducted at Unesp, Jaboticabal, SP, in 2017 winter crop season. Ten common bean cultivars were used, five of them from the carioca commercial group: BRS Estilo, BRS MG Majestoso, BRS Ametista, BRS Notável e BRS Cometa and five from the special business group: BRS MG Realce, BRS Embaixador, BRS FC 305, BRS Executivo e BRS Ártico. The experimental design was randomized blocks with four replications. Results were subjected to analysis of variance (F-Test) and the means compared by Scott-Knott cluster test at 5% probability. For the agronomic performance characteristics, the cultivar BRSMG Majestoso stood out within the carioca commercial group and the BRS Embaixador and BRS Executivo cultivars within the special commercial group. In terms of grain quality, the cultivars BRS Estilo stood out in the commercial group and BRS Embaixador in the special commercial group.Facultad de Ciencias Agrarias y Forestale

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Controle em cascata de um atuador hidráulico utilizando redes neurais

No presente trabalho, é realizada a modelagem e identificação de um serovoposicionador hidráulico de uma bancada de testes. As expressões analíticas tradicionalmente utilizadas em uma estratégia em cascata aplicada ao controle de trajetória de posição são obtidas. A estratégia em questão utiliza, conjuntamente, a linearização por realimentação como lei de controle do subsistema hidráulico e a lei de controle de Slotine e Li no subsistema mecânico. Com base na mesma estratégia, um controlador em cascata neural é proposto. Em tal controlador, a função analítica que representa o mapa inverso, presente na linearização por realimentação, e a função de compensação de atrito utilizada na lei de Slotine e Li são substituídas por funções constituidas por meio de redes neurais de perceptrons de múltiplas camadas. Essas redes neurais têm como entradas os estados do sistema e também a temperatura do fluido hidráulico. O novo controlador é apresentado em uma versão onde as redes neurais são aplicadas sem modificações on-line e em outra, onde são apresentadas leis de controle adaptativo para as mesmas. A prova de estabilidade do sistema em malha fechada é apresentada em ambos os casos. Resultados experimentais do controle de seguimento de trajetórias de posição em diferentes temperaturas do fluido hidráulico são apresentados. Esses resultados demonstram a maior efetividade do controlador proposto em relação aos controladores clássicos PID e PID+feefforward e ao controlador em cascata com funções analíticas fixas. Os experimentos são realizados em duas situações: quando não ocorrem variações paramétricas importantes no sistema, onde é utilizado o controlador em cascata neural fixo e quando ocorrem essas variações, onde se utiliza o controlador em cascata neural adaptativo.In this work, the modeling and identification of a hydraulic actuator testing setup are performed and the analytical expressions that are used in a cascade control strategy applyied in a position trajectory tracking control are designed. Such cascade strategy uses the feedback linearization control law in the hydraulical subsystem and the Slotine and Li control law in the mechanical one. Based on this cascade strategy, a neural cascade controller is proposed, for which the analytical function used as inversion set in the feedback linearization control law and the friction function compensation of the Slotine and Li control law are replaced by multi layer perceptrons neural networks where the inputs are the states of the system and the hydraulic fluid temperature. The novel controller is introduced in two different aproachs: the first one where the neural networks do not have on-line modifications and the second one where adaptive control laws are proposed. For both of them the stability proof of the closed-loop system is presented. Experimental results about some position tracking controls performed in different fluid temperature are showed. The results show that the novel controller is more efective than the classical PID, PID+feedforward and the traditional analytical cascade controller. The experiments are performed in two different setups: considering the system without importants parametric variations where is applied the non adaptive cascade neural controller and in the presence of parametric variations where is applied the adaptive cascade neural controller

Indolbutyric Acid (IBA) in the african mahogany (Khaya grandifoliola C. DC.) cuttings and mini-cuttings development

The current expansion of the forest sector in the Cerrado (Brazilian Savannah), especially of the species of genus Khaya sp. (African Mahogany), requires several silvicultural and technical studies of various natures. Seed and clonal propagation enable noble and vigorous seedlings, which will future compose commercial plantations aiming timber production. The species Khaya grandifoliola C. DC is considered of distinct wood characteristics and with great economic potential. The objective of this work was to evaluate the effect of different indolbultyric acid (IBA) concentrations – between 0 and 12 g.L-1– on the rooting of K. grandifoliola cuttings and mini-cuttings. The experiment was carried out at the "Mudas Nobres" private nursery, located in Goiânia (Goiás State, Brazil). The experiment was conducted in a completely randomized design in a 5 × 2 factorial scheme. Each treatment consisted of four replications with 20 cuttings (clonal origin) or mini-cuttings (seed origin) per repetition. Models were also applied to estimate the number of shoots in clonal cuttings, according to the data observed in seed mini-cuttings. The results indicate that IBA has the opposite effect on the two evaluated types of propagule origin, being more suitable for seed mini-cuttings (should apply 8 g.L-1of IBA) and less for clonal cuttings (should not apply IBA). If a standard application must be recommended (to cuttings either mini-cuttings), the most appropriate concentration is 6 g.L-1of IBA