Solar-activated and hydrothermally synthesized effective rGO/Ag2S composites for the destruction of naphthol green B dye and antibacterial applications.

Graphene-based nanocomposites are developing as a new class of materials with several uses. The varied weight percentages of rGO on Ag2S catalysts were synthesized using a simple hydrothermal process and employed for the decomposition of anionic dye naphthol green B (NGB) under solar light. The reduced graphene oxide-based silver sulfide (rGO/Ag2S) nanoparticles were then examined using XRD, SEM, EDS, HR-TEM, XPS, UV-DRS, and PL analysis. Using solar light, the photocatalytic activity of the produced catalyst was examined for the degradation of naphthol green B (NGB) in an aqueous solution. At pH 9, rGO/Ag2S is discovered to be more effective than the other catalysts for the NGB dye mineralization. Analyses have been conducted on the influence of operational parameters on the photo-mineralization of NGB, including the initial pH, initial dye concentration, and catalyst dosage. The dye concentration increased; the efficiency of photocatalytic degradation tended to decrease. Chemical oxygen demand (COD) studies have verified the NGB dye mineralization. Active species trapping revealed that holes, hydroxyl radicals, and superoxide radicals all played major roles in the photocatalytic deterioration of NGB processes. Additionally, a potential mechanism of NGB dye degradation by rGO/Ag2S catalyst is presented. The synthesized compound was further evaluated for antibacterial activity, and the results indicated that rGO/Ag2S were potentially effective antibacterial agents.

Physico-chemical and extraction properties on alkali-treated Acacia pennata fiber.

The production of reinforced composite materials can generally benefit greatly from the use of natural cellulosic woody fibers as good sustainable resources. Natural plants like hemp, cotton, and bamboo are great options for knitters and crocheters looking to make eco-friendly goods. The current study examines the properties of natural fiber obtained from the stem of the Acacia pennata (AP) plant, as well as its basic physico-chemical, structural, thermal, and mechanical characteristics. The key goal of this work was to investigate how alkali treatment affected the AP fibers' morphology, chemical composition, tensile capabilities, morphological changes, structural changes, and thermal degradation (APFs). The SEM image and pXRD analyses support the improved surface roughness of the fiber, and that was seen after the alkaline treatment. From XRD analysis, the fiber crystallinity index (54.65%) was improved and it was connected to their SEM pictograms in comparison to untreated APF. Alkali-treated AP fibers include a higher percentage of chemical components including cellulose (51.38%) and ash (5.13%). Alkali-treated AP fibers have a lower amount of hemi-cellulose (30.30%), lignin (20.96%), pectin (8.77%), wax (0.12%), and moisture (13.44%) than untreated APF. Their low density and high cellulosic content will improve their ability to fiber matrices. The thermal behavior of AP fiber at various temperatures was demonstrated by TG-DTA analysis, and tensile strength was also investigated.

Methanol production and purification via membrane-based technology: Recent advancements, challenges and the way forward.

Industrial revolution on the back of fossil fuels has costed humanity higher temperatures on the planet due to ever-growing concentration of carbon dioxide emissions in Earth's atmosphere. To tackle global warming demand for renewable energy sources continues to increase. Along renewables, there has been a growing interest in converting carbon dioxide to methanol, which can be used as a fuel or a feedstock for producing chemicals. The current review study provides a comprehensive overview of the recent advancements, challenges and future prospects of methanol production and purification via membrane-based technology. Traditional downstream processes for methanol production such as distillation and absorption have several drawbacks, including high energy consumption and environmental concerns. In comparison to conventional technologies, membrane-based separation techniques have emerged as a promising alternative for producing and purifying methanol. The review highlights recent developments in membrane-based methanol production and purification technology, including using novel membrane materials such as ceramic, polymeric and mixed matrix membranes. Integrating photocatalytic processes with membrane separation has been investigated to improve the conversion of carbon dioxide to methanol. Despite the potential benefits of membrane-based systems, several challenges need to be addressed. Membrane fouling and scaling are significant issues that can reduce the efficiency and lifespan of the membranes. The cost-effectiveness of membrane-based systems compared to traditional methods is a critical consideration that must be evaluated. In conclusion, the review provides insights into the current state of membrane-based technology for methanol production and purification and identifies areas for future research. The development of high-performance membranes and the optimization of membrane-based processes are crucial for improving the efficiency and cost-effectiveness of this technology and for advancing the goal of sustainable energy production.

Integration of geothermal-driven organic Rankine cycle with a proton exchange membrane electrolyzer for the production of green hydrogen and electricity.

Engineers and scientists are increasingly interested in clean energy options to replace fossil fuels in response to rising environmental concerns and dwindling fossil fuel resources. There has been an increase in the installation of renewable energy resources, and at the same time, conventional energy conversion systems have improved in efficiency. In this paper, several multi-generation systems based on geothermal energy are modeled, assessed, and optimized which employ an organic Rankine cycle and a proton-exchange membrane electrolyzer subsystem in five different configurations. Based on the results, the evaporator mass flow rate and inlet temperature, turbine efficiency, and inlet temperature are the most influential parameters on system outputs, namely, net output work, hydrogen production, energy efficiency, and cost rate. In this study, the city of Zanjan (Iran) is selected for a case study, and the results of system energy efficiency for changes in ambient temperature are examined during the four seasons of the year. To determine the optimal values of the objective functions, energy efficiency, and cost rate, NSGA-II multi-objective genetic algorithm is employed, and a Pareto chart is derived. The system's irreversibility and performance are gauged by energy and exergy analyses. At the optimum state, the best configuration yields an energy efficiency and cost rate of 0.65% and 17.40 $/h, respectively.

Silicon nanoparticles as a fluorometric probe for sensitive detection of cyanide ion and its application in C. elegans bio-imaging.

In recent years, silicon nanoparticles (Si NPs) have been explored as a promising alternative to traditional organic fluorophores in optical sensing and bioimaging applications owing to their exceptional optical properties and negligible toxicity. In this study, water-dispersible Si NPs were prepared from a 3-aminopropyl trimethoxysilane precursor using a facile one-pot process. The as-prepared Si NPs exhibited excitation-wavelength-dependent fluorescence properties and bright green fluorescence at 530 nm upon excitation at 420 nm. The fluorescence properties of Si NPs remained unperturbed under various physiological conditions, such as varying pH, ionic strength, and incubation time. A sensitive fluorometric turn-off sensor for cyanide ion (CN-) detection was devised based on the unique fluorescence properties of Si NPs. The Si NPs-based detection assay showed a good linear response toward CN- ranging between 0 and 33 µM, with a limit of detection as low as 0.90 nM. Caenorhabditis elegans is used as a model organism to evaluate the in vivo toxicity and molecular imaging capability of Si NPs.

Separation and purification of syngas-derived hydrogen: A comparative evaluation of membrane- and cryogenic-assisted approaches.

Hydrogen (H2) separation and purification is challenging because of the high purity and recovery requirements in particular applications, as well as the critical properties of H2 and its associated components. Unlike pressure swing adsorption, cryogenic- and membrane-based technologies are currently employed for H2 separation. Membrane-assisted (case-I) and cryogenic-assisted (case-II) separation and purification of H2 were evaluated in this study in terms of the energy, exergy, and economic aspects of the processes. In case-I and case-II, H2 was first produced from synthesis gas via the water-gas shift reaction and was then separated from other components using membrane and cryogenic systems, respectively. Additionally, an organic Rankine cycle was integrated with the water-gas shift reactors to recover the waste heat. A well-known commercial process simulation software, Aspen Hysys® v11, was employed to simulate both processes. Energy analysis revealed that case-I has a lower energy consumption (0.50 kWh/kg) than case-II (2.01 kWh/kg). However, low H2 purity and recovery rates are the main limitations of case-I. In terms of exergy, the H2 separation section in case-I exhibited a higher efficiency (28.4%) than case-II (14.7%). Furthermore, the economic evaluation showed that case-I was more expensive ($17.7 M) than case-II ($10.2 M) because of the high cost of the compressors required. In conclusion, this study could assist industry practitioners and academic researchers in selecting optimal H2 separation and purification technologies for improving the overall H2 economy.

Preparation and Characterization of Salsalate-Loaded Chitosan Nanoparticles: In Vitro Release and Antibacterial and Antibiofilm Activity.

The controlled-release characteristic of drug delivery systems is utilized to increase the residence time of therapeutic agents in the human body. This study aimed to formulate and characterize salsalate (SSL)-loaded chitosan nanoparticles (CSNPs) prepared using the ionic gelation method and to assess their in vitro release and antibacterial and antibiofilm activities. The optimized CSNPs and CSNP-SSL formulation were characterized for particle size (156.4 ± 12.7 nm and 132.8 ± 17.4 nm), polydispersity index (0.489 ± 0.011 and 0.236 ± 132 0.021), zeta potential (68 ± 16 mV and 37 ± 11 mV), and entrapment efficiency (68.9 ± 2.14%). Physicochemical features of these nanoparticles were characterized using UV-visible and Fourier transform infrared spectroscopy and X-ray diffraction pattern. Scanning electron microscopy studies indicated that CSNPs and CSNP-SSL were spherical in shape with a smooth surface and their particle size ranged between 200 and 500 nm. In vitro release profiles of the optimized formulations showed an initial burst followed by slow and sustained drug release after 18 h (64.2 ± 3.2%) and 48 h (84.6 ± 4.23%), respectively. Additionally, the CSNPs and CSNP-SSL nanoparticles showed a sustained antibacterial action against Staphylococcus aureus (15.7 ± 0.1 and 19.1 ± 1.2 mm) and Escherichia coli (17.5 ± 0.8 and 21.6 ± 1.7 243 mm). Interestingly, CSNP-SSL showed better capability (89.4 ± 1.2% and 95.8 ± 0.7%) than did CSNPs in inhibiting antibiofilm production by Enterobacter tabaci (E2) and Klebsiella quasipneumoniae (SC3). Therefore, CSNPs are a promising dosage form for sustained drug delivery and enhanced antibacterial and antibiofilm activity of SSL; these results could be translated into increased patient compliance.

Membrane-assisted natural gas liquids recovery: Process systems engineering aspects, challenges, and prospects.

Membrane-based natural gas liquid (NGL) recovery processes are still far from their large-scale applications owing to communication gaps among academic researchers and industry practitioners. A comprehensive process systems engineering (PSE) assessment of membrane-based NGL recovery processes is required to determine their commercial suitability. This PSE-based review presents the technical and economic aspects of standalone and integrated membrane processes. Literature review shows that polymeric membranes (e.g., cellulose acetate) are primarily evaluated in NGL recovery processes despite their low separation efficiencies. So far, multiple multistage membrane models with standalone and integrated designs have been suggested by analyzing different configurations to improve separation efficiency. In standalone processes, cellulose acetate membrane modules with high selectivity ratio can improve methane recovery by up to 100%. Absorption or cryogenic integrated processes exhibit high methane recovery (up to 99%) but demonstrate high energy consumption. The integrated absorption-membrane process is more capital cost intensive (i.e., 0.41 m$) than the cryogenic-membrane process (0.39 m$). Furthermore, in this review, the key challenges encountered by membrane processes and related issues are identified to improve their commercial viability by capitalizing on their maximum potential benefits. The major challenges associated with membrane processes constitute the lack of rigorous multistage membrane models and inflexibility in product purity and recovery. The policy implications and future directions suggest that owing to the growing demand for NGLs, membranes that can sustain varying natural gas compositions and conditions may be required. This PSE assessment will help process engineers and policymakers to improve natural gas supply chain economics.

Electro-oxidation of heavy metals contaminated water using banana waste-derived activated carbon and Fe3O4 nanocomposites.

The main objective of this study was to banana waste-derived activated carbon (BWAC) make a high pore surface area was prepared and composited with Fe3O4 via a facile hydrothermal method. Various physiochemical characteristics of the prepared samples were evaluated using XRD, FTIR, FESEM, Raman Spectroscopy and XPS analysis. In addition, cyclic voltammetry and electrochemical impedance spectroscopy analyses were performed to determine the electrochemical properties of the prepared samples. The Fe3O4/BWAC sample showed a higher capacitance (285 F g-1) than BWAC at the same scan rate of 10 mV s-1. The capacitive deionization (CDI) cell configuration was varied, and its electro-sorption and defluoridization efficiencies were analyzed during the lead (Pb2+) removal 90%. An asymmetric combination of electrodes in the CDI cell exhibited better heavy metal removal performance, possibly due to the synergistic effect of the high surface area and the balance between the active adsorption site and the overlapping effect of the EDL. As a result, Fe3O4/BWAC could be a potential resource for supercapacitors and CDI electrodes, and the novel Fe3O4/BWAC nanocomposites outstanding performance suggests that they could be helpful for future energy storage and environmental applications.

A cohesive effort to assess the suitability and disparity of carbon nanotubes for water treatment.

Population growth, industrialization, and the extensive use of chemicals in daily life have all contributed to an increase in waste generation and an intensified release of organic pollutants into the aquatic environment. To ensure the quality of water (including natural resources), the removal of these pollutants from wastewater has become a challenging task for scientific community. Conventional physical, chemical, and biological treatment methods are commonly used in combinations and are not very effective. Recently, carbon nanotubes (CNTs) emerged as the most reliable and adaptable choice for efficient water treatment due to their extraordinary material properties appearing as a single-step solution for water treatment. High surface area, exceptional porosities, hollow and layered structures, and ease of chemical activation and functionalization are some properties which makes it excellent adsorption material. Hence, this review paper discusses the recent advances in the synthesis, purification, and functionalization of CNTs for water and wastewater treatment. In addition, this study also also provides a quick overview of CNTs-based advance technologies employed in water treatment and carefully assesses the benefits versus risks during large-scale water treatment. Furthermore, it concludes that identified risks to the environment and human health cannot be easily ignored and strict regulatory requirements are a must for producing low-cost innoxious CNTs.

Exploitation of distillation for energy-efficient and cost-effective environmentally benign process of waste solvents recovery from semiconductor industry.

The waste solvent is unavoidably generated from the high solvent dependable processes. One of them is the semiconductor industry. The waste solvent is frequently incinerated to eliminate hazardous waste and this practice raises the issue of environmental and treatment costs. Thus, recovery of waste solvent is a substantial environmental mitigation option. This study explores the recovery of multicomponent waste solvents from the semiconductor industry. To achieve a greener and energy-efficient process, the recovery process is proposed through investigation of mixture thermodynamic behavior, process design, optimization, economics, and integration of renewable energy for environmental advantages. Herein, Distillation, a practical technology option for solvent recovery, with green solvent for extractive distillation and a new approach using renewable energy in waste solvent recovery are explored. As the result, waste solvent recovery by distillation with conventional energy exhibits bold advantages to cost and lower carbon process compared to waste disposal. The integration of renewable energy with about 37 % share of conventional energy as the backup indicates the highest annual cost-saving and reduces about 89.4 % of annual carbon emission compared to carbon emission from waste disposal.

Developing machine learning models for relative humidity prediction in air-based energy systems and environmental management applications.

The prediction of relative humidity is a challenging task because of its nonlinear nature. The machine learning-based prediction strategies have attained significant attention in tackling a broad class of challenging nonlinear and complex problems. The random forest algorithm is a well-proven machine learning algorithm due to its ease of training and implementation, as it requires minimal preprocessing. The random forest algorithm has hitherto not been employed for estimating air quality parameters, such as relative humidity. In this study, the random forest approach is implemented to estimate the relative humidity as a function of dry- and wet-bulb temperatures. A well-known commercial process simulator called Aspen HYSYS® V10 is linked with MATLAB® version 2019a to establish a data mining environment. The robustness of the prediction model is evaluated against varying wet-bulb depressions. There is high absolute deviation that indicates a lower prediction performance of the model against the higher wet-bulb depression i.e., ~20.0 °C. The random forest model can predict relative humidity with a 1.1% mean absolute deviation compared to the values obtained through Aspen HYSYS. The performance of the RF estimation model is also compared with a well-known support vector regression model. The random forest model demonstrates 74.4% better performance than the support vector machine model for the problem of interest, i.e., relative humidity estimation. This study will significantly help the practitioners in efficient designing of air-dependent energy systems as well as in better environmental management through rigorous prediction of relative humidity.

Synthesis of biodiesel from non-edible (Brachychiton populneus) oil in the presence of nickel oxide nanocatalyst: Parametric and optimisation studies.

The present study defines a novel green method for the synthesis of the nickel oxide nanocatalyst by using an aqueous latex extract of the Ficus elastic. The catalyst was examined for the conversion of novel Brachychiton populneus seed oil (BPSO) into biodiesel. The Brachychiton populneus seeds have a higher oil content (41 wt%) and free fatty acid value (3.8 mg KOH/g). The synthesised green nanocatalyst was examined by the Fourier transform infrared (FT-IR) spectroscopy, energy dispersive X-Ray (EDX) spectroscopy, X-Ray diffraction (XRD) spectroscopy and scanning electron microscopy (SEM). The obtained results show that the synthesised green nanocatalyst was 22-26 nm in diameter and spherical-cubic in shape with a higher rate of catalytic efficiency. It was utilised further for the conversion of BPSO into biofuel. Due to the high free fatty acid value, the biodiesel was synthesised by the two-step process, i.e., pretreatment of the BPSO by means of acid esterification and then followed by the transesterification reaction. The acidic catalyst (H2SO4) was used for the pretreatment of BPSO. The optimum condition for the transesterification of the pretreated BPSO was 1:9 of oil-methanol molar ratio, 2.5 wt % of prepared nanocatalyst concentration and 85 °C of reaction temperature corresponding to the highest biodiesel yield of 97.5 wt%. The synthesised biodiesel was analysed by the FT-IR and GC-MS technique to determine the chemical composition of fatty acid methyl esters. Fuel properties of Brachychiton populneus seed oil biodiesel (BPSOB) were also examined, compared, and it falls in the prescribed range of ASTM standards.

Purification of 2,3-butanediol from fermentation broth: process development and techno-economic analysis.

BACKGROUND: 2,3-Butanediol (2,3-BDO) is a synthetic chemical compound that also can be produced by biomass fermentation, which is gaining share in the global market as an intermediate product for numerous applications, i.e. as liquid fuel or fuel additive. Several metabolic engineering fermentation strategies to enhance the production of 2,3-BDO were developed. However, the recovery of 2,3-BDO from its fermentation broth remains a challenge due to its low concentration and its solubility in water and other components. Thus, a cost-effective recovery process is required to deliver the required purity of 2,3-BDO. This paper presents a new process development and techno-economic analysis for 2,3-BDO purification from a fermentation broth. RESULTS: Conventional distillation and hybrid extraction-distillation (HED) processes are proposed in this study with detailed optimization and economic analysis. Particularly, a systematic solvent selection method was successfully implemented to determine a good solvent for the proposed HED configuration based on numerous experimental data obtained with each solvent candidate. NRTL and UNIQUAC property methods were evaluated to obtain binary interaction parameters of 2,3-BDO through rigorous Aspen Plus regression and validated using experimental data. Total annual cost (TAC)-based optimization was performed for each proposed configuration. Even though the HED configuration required 9.5% higher capital cost than conventional distillation, placing an extraction column before the distillation column was effective in removing water from the fermentation broth and significantly improved the overall process economics. CONCLUSIONS: Oleyl alcohol was found to be the most suitable solvent for the HED of 2,3-BDO due to its high distribution coefficient and high selectivity. The proposed HED drastically reduced reboiler duty consumption and TAC by up to 54.8 and 25.8%, respectively. The proposed design is expected to be used for the commercial scale of 2,3-BDO production from fermentation process.

Recrystallization techniques for the synthesis of ZnO nanorods: an in situ process for carbon doping and enhancing the dispersion concentration of ZnO nanorods.

Zinc acetate is recrystallized as lumber-shaped tetragonal rods by a novel recrystallization technique. Subsequently, the recrystallized zinc acetate is converted into ZnO nanorods in a glass vial by the simplest and cheapest method without utilizing any expensive instrumentation. Carbon is doped in ZnO nanorods during the preparation ZnO nanorods without any extra steps, chemicals, or effort. The carbon-doped ZnO nanorods can be dispersed in a solvent at very high concentrations and are also stable for a very long time, which are comparatively higher than those of the other existing ZnO nanoparticles. The higher dispersion concentration and higher stability of ZnO nanoparticles are explained by a scheme that demonstrates the suspending mechanism of the ZnO nanoparticles at higher concentrations with higher stabilities in a solvent through the anchoring groups of carbon. No materials are used for surface modification; no surface coatings, ionic materials, or pH controlling materials are used to increase the dispersion concentration and stability. This is the first observation of the doped carbon playing a significant role in the dispersion of ZnO nanoparticles at higher concentrations by withholding them in the solvent. Therefore, doped carbon at the surface of ZnO nanoparticles prevents the self-aggregation of ZnO nanoparticles in the solution phase by interfacial barrier layers among ZnO nanorods and interfacial interactive layer between ZnO nanorod and solvent.

Analytical design of an industrial two-term controller for optimal regulatory control of open-loop unstable processes under operational constraints.

This paper proposes a novel optimization-based approach for the design of an industrial two-term proportional-integral (PI) controller for the optimal regulatory control of unstable processes subjected to three common operational constraints related to the process variable, manipulated variable and its rate of change. To derive analytical design relations, the constrained optimal control problem in the time domain was transformed into an unconstrained optimization problem in a new parameter space via an effective parameterization. The resulting optimal PI controller has been verified to yield optimal performance and stability of an open-loop unstable first-order process under operational constraints. The proposed analytical design method explicitly takes into account the operational constraints in the controller design stage and also provides useful insights into the optimal controller design. Practical procedures for designing optimal PI parameters and a feasible constraint set exclusive of complex optimization steps are also proposed. The proposed controller was compared with several other PI controllers to illustrate its performance. The robustness of the proposed controller against plant-model mismatch has also been investigated.

Techno-economic assessment of hybrid extraction and distillation processes for furfural production from lignocellulosic biomass.

BACKGROUND: Lignocellulosic biomass is one of the most promising alternatives for replacing mineral resources to overcome global warming, which has become the most important environmental issue in recent years. Furfural was listed by the National Renewable Energy Laboratory as one of the top 30 potential chemicals arising from biomass. However, the current production of furfural is energy intensive and uses inefficient technology. Thus, a hybrid purification process that combines extraction and distillation to produce furfural from lignocellulosic biomass was considered and investigated in detail to improve the process efficiency. This effective hybrid process depends on the extracting solvent, which was selected based on a comprehensive procedure that ranged from solvent screening to complete process design. RESULTS: Various solvents were first evaluated in terms of their extraction ability. Then, the most promising solvents were selected to study the separation feasibility. Eventually, processes that used the three best solvents (toluene, benzene, and butyl chloride) were designed and optimized in detail using Aspen Plus. Sustainability analysis was performed to evaluate these processes in terms of their energy requirements, total annual costs (TAC), and carbon dioxide (CO2) emissions. The results showed that butyl chloride was the most suitable solvent for the hybrid furfural process because it could save 44.7% of the TAC while reducing the CO2 emissions by 45.5% compared to the toluene process. In comparison with the traditional purification process using distillation, this suggested hybrid extraction/distillation process can save up to 19.2% of the TAC and reduce 58.3% total annual CO2 emissions. Furthermore, a sensitivity analysis of the feed composition and its effect on the performance of the proposed hybrid system was conducted. CONCLUSIONS: Butyl chloride was found to be the most suitable solvent for the hybrid extraction/distillation process of furfural production. The proposed hybrid sequence was more favorable than the traditional distillation process when the methanol fraction of the feed stream was <3% and more benefit could be obtained when that fraction decreased.

Alignment of Carbon Nanotubes in Carbon Nanotube Fibers Through Nanoparticles: A Route for Controlling Mechanical and Electrical Properties.

This is the first study that describes how semiconducting ZnO can act as an alignment agent in carbon nanotubes (CNTs) fibers. Because of the alignment of CNTs through the ZnO nanoparticles linking groups, the CNTs inside the fibers were equally distributed by the attraction of bonding forces into sheetlike bunches, such that any applied mechanical breaking load was equally distributed to each CNT inside the fiber, making them mechanically robust against breaking loads. Although semiconductive ZnO nanoparticles were used here, the electrical conductivity of the aligned CNT fiber was comparable to bare CNT fibers, suggesting that the total electron movement through the CNTs inside the aligned CNT fiber is not disrupted by the insulating behavior of ZnO nanoparticles. A high degree of control over the electrical conductivity was also demonstrated by the ZnO nanoparticles, working as electron movement bridges between CNTs in the longitudinal and crosswise directions. Well-organized surface interface chemistry was also observed, which supports the notion of CNT alignment inside the fibers. This research represents a new area of surface interface chemistry for interfacially linked CNTs and ZnO nanomaterials with improved mechanical properties and electrical conductivity within aligned CNT fibers.

Analytical design of fractional-order proportional-integral controllers for time-delay processes.

A new design method of fractional-order proportional-integral controllers is proposed based on fractional calculus and Bode's ideal transfer function for a first-order-plus-dead-time process model. It can be extended to be applied to various dynamic models. Tuning rules were analytically derived to cope with both set-point tracking and disturbance rejection problems. Simulations of a broad range of processes are reported, with each simulated controller being tuned to have a similar degree of robustness in terms of resonant peak to other reported controllers. The proposed controller consistently showed improved performance over other similar controllers and established integer PI controllers.

Multi-loop PI controller design based on the direct synthesis for interacting multi-time delay processes.

In this article, a new analytical method based on the direct synthesis approach is proposed for the design of a multi-loop proportional-integral (PI) controller. The proposed design method is aimed at achieving the desired closed-loop response for multiple-input, multiple-output (MIMO) processes with multiple time delays. The ideal multi-loop controller is firstly designed in terms of the relative gain and desired closed-loop transfer function. Then, the standard multi-loop PI controller is obtained by approximating the ideal multi-loop controller using the Maclaurin series expansion. The simulation study demonstrates the effectiveness of the proposed method for the design of multi-loop PI controllers. The multi-loop PI controller designed by the proposed method shows a fast, well-balanced, and robust response with the minimum integral absolute error (IAE).