Fuzzy Control of a Large Crane Structure

The usage of tower cranes, one type of rotary cranes, is common in many industrial structures, e.g., shipyards, factories, etc.  With the size of these cranes becoming larger and the motion expected to be faster and has no prescribed path, their manual operation becomes difficult and hence, automatic closed-loop control schemes are very important in the operation of rotary crane.  In this paper, the plant of concern is a tower crane consists of a rotatable jib that carries a trolley which is capable of traveling over the length of the jib.  There is a pendulum-like end line attached to the trolley through a cable of variable length.  A fuzzy logic controller with various types of membership functions is implemented for controlling the position of the trolley and damping the load oscillations.  It consists of two main types of controllers radial and rotational each of two fuzzy inference engines (FIEs).  The radial controller is used to control the trolley position and the rotational is used for damping the load oscillations.  Computer simulations are used to verify the performance of the controller.  The results from the simulations show the effectiveness of the method in the control of tower crane keeping load swings small at the end of motion

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

ANN Based Power System Stabilizers for Large Synchronous Generators

This paper presents an artificial neural network based power system stabilizer (ANNPSS) for excitation control for a large synchronous generator. The generator operates over a wide range of operating conditions and is subjected to different types of disturbances and emergency states. A 300 MW turbogenerator is used to generate appropriate training data for the ANN controller. Off-line simulations using a suitable conventional PSS to control the generator for different working conditions are used to generate training input-output pairs. A multi-layered back propagation (BP) ANN is utilised to design the ANN based controller where speed error deviation and the incremental change in machine terminal voltage are fed to the ANNPSS controller. The proposed ANNPSS and conventional PSS are compared and test results indicate that the ANN based controller is more adaptive and flexible than conventional stabilizers and show a good performance over a wide range of operating conditions and disturbances

Fuzzy Control of a Large Crane Structure

The usage of tower cranes, one type of rotary cranes, is common in many industrial structures, e.g., shipyards, factories, etc. With the size of these cranes becoming larger and the motion expected to be faster and has no prescribed path, their manual operation becomes difficult and hence, automatic closed-loop control schemes are very important in the operation of rotary crane. In this paper, the plant of concern is a tower crane consists of a rotatable jib that carries a trolley which is capable of traveling over the length of the jib. There is a pendulum-like end line attached to the trolley through a cable of variable length. A fuzzy logic controller with various types of membership functions is implemented for controlling the position of the trolley and damping the load oscillations. It consists of two main types of controllers radial and rotational each of two fuzzy inference engines (FIEs). The radial controller is used to control the trolley position and the rotational is used for damping the load oscillations. Computer simulations are used to verify the performance of the controller. The results from the simulations show the effectiveness of the method in the control of tower crane keeping load swings small at the end of motion

Characterization of two thermostable inulinases from Rhizopus oligosporus NRRL 2710

Two inulinases (Inu2 and Inu3) were purified from Rhizopus oligosporus NRRL 2710 by chromatography on DEAE-Sepharose and Sephacryl S-200 columns. The molecular weight of Inu2 and Inu3 were determined to be 76 and 30 kDa, respectively. Inu2 and Inu3 had the same pH optimum at 5.0, temperature optimum at 50 and 60 °C, and thermal stability up to 60 and 70 °C for 1 h, respectively. Inu2 and Inu3 had low km values (0.93 and 0.70 mM, respectively) indicating the high affinity toward inulin. Mg2+, Ca2+, Zn2+ and EDTA did not significantly influence the enzyme activity. Ni2+, Cu2+, Fe2+ and Co2+ showed a partial inhibitory effect, and Hg2+ had a strong inhibitory effect. p-Chloromercuribenzoate had a partial inhibitory effect on Inu2. From these findings, R. oligosporus inulinases can be beneficial enzymes for industrial enzymatic production of high fructose syrup