Controller Design for the Rotational Dynamics of a Quadcopter

Researchers have shown their interests in establishing miniature flying robots to be utilized for, both, commercial and research applications. This is due to that fact that there appears to be a huge advancement in miniature actuators and sensors which depend on the MEMS (Micro Electro-Mechanical Systems) NEMS (Nano-Electro Mechanical Systems). This research underlines a detailed mathematical model and controller design for a quadcopter. The nonlinear dynamic model of the quadcopter is derived from the Newton-Euler method and Euler Lagrange method. The motion of a quadcopter can be classified into two subsystems: a rotational subsystem (attitude and heading) and translational subsystem (altitude and x and y motion). The rotational system is fully actuated whereas translational subsystem is under actuated. However, a quadcopter is 6 DOF (Degrees of Freedom) under actuated system. The controller design of a quadcopter is difficult due to its complex and highly nonlinear mathematical model where the state variables are strongly coupled and contain under actuated property. Nonlinear controller such as SMC (Sliding Mode Controller) is used to control altitude, yaw, pitch, and roll angles.Simulation results show that the robustness of the SMC design gives a better way to design a controller with autonomous stability flight with good tracking performance and improved accuracy without any chattering effect. The system states are following the desired trajectory as expected

Enhanced methane production from anaerobic co-digestion of wheat straw rice straw and sugarcane bagasse: A kinetic analysis

Future energy and environmental issues are the major driving force towards increased global utilization of biomass, especially in developing countries like Pakistan. Lignocellulosic residues are abundant in Pakistan. The present study investigated the best-mixed proportion of mechanically pretreated lignocellulosic residues i.e., wheat straw and rice straw (WSRS), bagasse and wheat straw (BAWS), bagasse, and rice straw (BARS), bagasse, wheat straw, and rice straw (BAWSRS) through anaerobic co-digestion. Anaerobic batch mode bioreactors comprising of lignocellulosic proportions and control bioreactors were run in parallel at mesophilic temperature (35 degrees C) for the substrate to inoculum (S/I) ratio of 1.5 and 2.5. Maximum and stable biomethane production was observed at the substrate to inoculum (S/I) ratio of 1.5, and the highest biomethane yield 339.0089123 NmLCH4/gVS was achieved by co-digestion of wheat straw and rice straw (WSRS) and lowest 15.74 NmLCH4/gVS from bagasse and rice straw (BARS) at 2.5 substrates to inoculum ratio. Furthermore, anaerobic reactor performance was determined by using bio-kinetic parameters i.e., production rate (Rm), lag phase (lambda), and coefficient of determination (R2). The bio-kinetic parameters were evaluated by using kinetic models; first-order kinetics, Logistic function model, Modified Gompertz Model, and Transference function model. Among all kinetic models, the Logistic function model provided the best fit with experimental data followed by Modified Gompertz Model. The study suggests that a decrease in methane production was due to lower hydrolysis rate and higher lignin content of the co-digested substrates, and mechanical pretreatment leads to the breakage of complex lignocellulosic structure. The organic matter degradation evidence will be utilized by the biogas digesters developed in rural areas of Pakistan, where these agricultural residues are ample waste and need a technological solution to manage and produce renewable energy.Web of Science1113art. no. 606

Methane decomposition for hydrogen production over biomass fly ash-based CeO2 nanowires promoted cobalt catalyst

In this work, the biomass fly ash (BFA) was investigated as a potential catalyst for the thermo-catalytic decomposition of methane and attractive approach for hydrogen (H-2) production. The BFA based CeO2 nanowires promoted cobalt catalyst was synthesized for catalytic methane (CH4) decomposition and was tested in a fixed bed reactor. The physicochemical properties of the catalyst were investigated using various techniques such as X-ray powder diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, thermal gravimetric analysis, and Fourier transformed infrared. The pure crystalline micro-flake BFA was modified using synthesized CeO2 nanowires and the resulted micro flakes cross-linked with nanowires shown thermal stability up to 900 degrees C. The high stability of the catalyst makes it suitable for the thermal catalytic decomposition of methane. The activity of the catalyst was tested at 850 degrees C to analyze the H-2 production and CH4 conversion. The obtained results revealed that support and promoter exhibit a strong impact on the CH4 conversion and H-2 yield in catalyst screening tests. A maximum conversion of 71% for CH4 with 44.9% H-2 yield was recorded for 34 h on stream activity while using 5% Co/CeO2-BFA as the catalyst. While BFA and Co-BFA as catalyst showed 36% and 47% conversion of CH4, respectively which indicates that the addition of promoter shows an increase in values of both conversion of CH4 and H-2 yield. Compared to traditional catalyst support, the use of waste-sourced catalyst support for CH4 decomposition provides a greener and more economical route for H-2 production

A Robust Controller of a Reactor Electromicrobial System Based on a Structured Fractional Transformation for Renewable Energy

The focus on renewable energy is increasing globally to lessen reliance on conventional sources and fossil fuels. For renewable energy systems to work at their best and produce the desired results, precise feedback control is required. Microbial electrochemical cells (MEC) are a relatively new technology for renewable energy. In this study, we design and implement a model-based robust controller for a continuous MEC reactor. We compare its performance with those of traditional methods involving a proportional integral derivative (PID), H-infinity (H∞) controller and PID controller tuned by intelligent genetic algorithms. Recently, a dynamic model of a MEC continuous reactor was proposed, which describes the complex dynamics of MEC through a set of nonlinear differential equations. Until now, no model-based control approaches for MEC have been proposed. For optimal and robust output control of a continuous-reactor MEC system, we linearize the model to state a linear time-invariant (LTI) state-space representation at the nominal operating point. The LTI model is used to design four different types of controllers. The designed controllers and systems are simulated, and their performances are evaluated and compared for various operating conditions. Our findings show that a structured linear fractional transformation (LFT)-based H∞ control approach is much better than the other approaches against various performance parameters. The study provides numerous possibilities for control applications of continuous MEC reactor processes

A Robust Controller of a Reactor Electromicrobial System Based on a Structured Fractional Transformation for Renewable Energy

The focus on renewable energy is increasing globally to lessen reliance on conventional sources and fossil fuels. For renewable energy systems to work at their best and produce the desired results, precise feedback control is required. Microbial electrochemical cells (MEC) are a relatively new technology for renewable energy. In this study, we design and implement a model-based robust controller for a continuous MEC reactor. We compare its performance with those of traditional methods involving a proportional integral derivative (PID), H-infinity (H∞) controller and PID controller tuned by intelligent genetic algorithms. Recently, a dynamic model of a MEC continuous reactor was proposed, which describes the complex dynamics of MEC through a set of nonlinear differential equations. Until now, no model-based control approaches for MEC have been proposed. For optimal and robust output control of a continuous-reactor MEC system, we linearize the model to state a linear time-invariant (LTI) state-space representation at the nominal operating point. The LTI model is used to design four different types of controllers. The designed controllers and systems are simulated, and their performances are evaluated and compared for various operating conditions. Our findings show that a structured linear fractional transformation (LFT)-based H∞ control approach is much better than the other approaches against various performance parameters. The study provides numerous possibilities for control applications of continuous MEC reactor processes

Mixotrophic cultivation of microalgae for carotenoid production

The intrinsic ability of microalgae to accumulate high amounts of carotenoids has made them the preferred aquatic organisms of biotechnological exploration for carotenoid production. To continuously innovate and modify microalgal bioprocesses, aquaculture scientists have been working hard for the past decades in a forwardlooking way, and mixotrophic cultivation of microalgae is deemed as a promising strategy to decrease production cost. This review is intended to summarise the recent research advancement of carotenoids production from mixotrophically cultivated microalgae, starting from the structure, biosynthesis, physiological roles and applications of carotenoids and followed by the production processes both currently established and under development. Most importantly, the microalgal physiology of mixotrophic cultivation is reviewed in depth both in general and specifically for the most studied species, and the prospects of commercially viable mixotrophic microalgal processes for carotenoid production along with the insight of future research are of course discussed. Finally, we conclude that mixotrophy might be a promising strategy for large-scale cultivation of microalgae to produce carotenoids although some technical obstacles need to be overcome

Thermocatalytic partial oxidation of methane to syngas (H2, CO) production using Ni/La2O3 modified biomass fly ash supported catalyst

In this work, the biomass fly ash (BFA) supported Ni/La2O3 catalyst was synthesized for the first time to produce syngas, a mixture of CO and H2 via the partial oxidation of methane (POM). The BFA support was modified using laboratory synthesized Ni/La2O3 through the wetness impregnation technique. The Ni/La2O3-BFA catalyst was characterized by several techniques to investigate its suitability for the POM reaction. The characterization results showed that the crystalline structure, better metal support interaction and enhanced thermal stability of Ni/La2O3-BFA make it suitable for the POM. The synthesized Ni/La2O3-BFA catalyst remained stable for 30 h on stream during POM at 850 °C. The addition of La2O3 promoter and active metal Ni to the BFA improved the CH4 conversion from 55% to 85% and enhanced the H2/CO ratio from 1.4 to 2.0 while maintaining a reactants stoichiometric ratio of (CH4:O2 = 2:1). The study of spent catalyst by using various techniques confirmed that the stable catalyst exhibited coke resistance in the POM even after 30 h time on stream. Thus, the performance of BFA supported Ni/La2O3 catalyst shows more potential for catalytic applications due to its suitable physiochemical properties as it is a combination of multiple oxides that synergistically participate in the reaction steps and increases syngas production. It also provides low-cost, abundant, greener, and waste based alternative to expensive metal oxide as supports for catalytic applications

Copper and calcium-based metal organic framework (MOF) catalyst for biodiesel production from waste cooking oil: A process optimization study

Due to the diminution of conventional fuels, biodiesel has attracted acute attention due to its renewable and zero-emission features. However, cleaner production of biodiesel on an industrial scale requires a stable heterogeneous, low cost and recyclable catalyst. This study presents the preparation and application of copper and calcium-based metal organic frameworks (MOFs) as catalysts in the esterification and transesterification reactions for biodiesel production from waste cooking oil (WCO). The synthesized catalysts are characterized using XRD, SEM, TGA, FTIR and BET. The catalyst characterization indicates the formations of the cubical structure of MOFs with a crystallite size of <50 nm and thermal stability below 600 °C. The catalyst has been tested for WCO to biodiesel production and the biodiesel samples comply with the ASTM standards. Furthermore, the process parameters i.e catalyst loading (X1), reaction temperature (X2) and alcohol-oil ratio (X3) are optimized employing response surface methodology (RSM) via central composite design (CCD). The second-order regression model is employed to investigate the dynamic interaction between the process parameters and biodiesel yield (YBD %). The optimum process values are determined i.e catalyst loading = 1.0 g/100 mL, reaction temperature = 60 °C and alcohol-oil ratio = 20 with optimum biodiesel yield of 84.5 (vol%). The experimental results and predicted results are in good agreement with percentage error less than ± 5%. The regenerated catalyst demonstrates a significant biodiesel yield up to 7% reduction for 3 cycles

Performance Analysis of TiO2-Modified Co/MgAl2O4 Catalyst for Dry Reforming of Methane in a Fixed Bed Reactor for Syngas (H2, CO) Production

Co/TiO2–MgAl2O4 was investigated in a fixed bed reactor for the dry reforming of methane (DRM) process. Co/TiO2–MgAl2O4 was prepared by modified co-precipitation, followed by the hydrothermal method. The active metal Co was loaded via the wetness impregnation method. The prepared catalyst was characterized by XRD, SEM, TGA, and FTIR. The performance of Co/TiO2–MgAl2O4 for the DRM process was investigated in a reactor with a temperature of 750 °C, a feed ratio (CO2/CH4) of 1, a catalyst loading of 0.5 g, and a feed flow rate of 20 mL min−1. The effect of support interaction with metal and the composite were studied for catalytic activity, the composite showing significantly improved results. Moreover, among the tested Co loadings, 5 wt% Co over the TiO2–MgAl2O4 composite shows the best catalytic performance. The 5%Co/TiO2–MgAl2O4 improved the CH4 and CO2 conversion by up to 70% and 80%, respectively, while the selectivity of H2 and CO improved to 43% and 46.5%, respectively. The achieved H2/CO ratio of 0.9 was due to the excess amount of CO produced because of the higher conversion rate of CO2 and the surface carbon reaction with oxygen species. Furthermore, in a time on stream (TOS) test, the catalyst exhibited 75 h of stability with significant catalytic activity. Catalyst potential lies in catalyst stability and performance results, thus encouraging the further investigation and use of the catalyst for the long-run DRM process

Investigation of combustion performance of tannery sewage sludge using thermokinetic analysis and prediction by artificial neural network

The disposal and the management of sewage sludge from tanneries is a challenging issue for the leather industries because of their adverse effect on the environment. In this study the detailed characterization and assessment using kinetic and thermodynamic parameters of the tannery sewage sludge in combustion environment was employed. Isoconversional model-free methods like Ozawa-Flynn-Wall (OFW), Friedman and Kissinger-Akahira-Sunose (KAS) were employed to investigate the kinetics and the thermodynamic parameters in the air environment. Activation energies (Ea) for the Friedman, KAS and OFW were reported. The DTG curves at the heating rate of 5, 10, 20 and 40 °C/min show the diversified conversions in three major stages. The Ea values for the model ranges are Friedman (148.96 kJ/mol-395.23 kJ/mol), KAS (169.65 kJ/mol-383.75 kJ/mol) and OFW (176.44 kJ/mol-377.85 kJ/mol). The average Ea for the Friedman is 226.04 kJ/mol while for KAS and OFW the average Ea is 230.71 kJ/mol and 230.11 kJ/mol. Moreover, the values of ΔH, ΔG, and ΔS were analysed. Furthermore, the frequency distribution by applying the DAEM model is investigated, and there are six pseudo-components involved in the frequency distribution for combustion. For the thermal degradation prediction of the sewage sludge from the tannery, an artificial neural network (ANN) of the MLP-3-7-1 model was used. This model shows that there is good agreement between the experimental and the predicted values. Overall, this study highlights the importance of the ANN for the prediction of combustion behaviour of biomass with more accuracy