Composition Disturbances Research Articles

Fixed-time event-triggered sliding mode cooperative path-following control with prescribed performance for USVs based on lumped disturbance observer

In order to solve the problem of Unmanned Surface Vehicles being unable to accurately cooperative path-following under the parameter uncertainties, actuator faults, and external disturbances, this paper mainly combines the fixed-time and sliding mode theory to design the control strategy. Firstly, a fixed-time disturbance observer is adopted to estimate composite disturbances. Then, a fixed-time heading-surge guidance law that satisfies the fixed-time stability of the position error system is designed, and the synchronization of the formation on the full paths is realized by the fixed-time path parameter consensus. On this basis, a fixed-time dynamic event-triggered sliding mode controller with prescribed performance is proposed to ensure that the velocity error system is stable in fixed time and the tracking error is strictly within the specified range. Due to the application of fixed-time theory in cooperative path-following, the whole closed-loop system is proved to be fixed-time stable. Moreover, the dynamic event-triggered mechanism is introduced to reduce the energy consumption. Finally, the effectiveness and superiority of the proposed control method are verified by simulations.

The closed-loop control method based on dual-port adaptive internal model control for fine image stabilization of space telescopes.

In view of the complex working environment of space astronomical telescopes, the influence of various disturbance sources on the imaging quality cannot be ignored. This paper focuses on compensating for the space telescope line-of-sight (LOS) deviation and suppressing the low-frequency disturbance problem in astronomical observation. A closed-loop control method based on dual-port adaptive internal model control (AIMC) for the fine image stabilization system (FISS) was proposed. To be specific, the fine guidance sensor (FGS) as the high-precision detection unit of the FISS calculates the telescope LOS deviation and sends it to the controller unit in real time. The controller unit drives the large-aperture fast steering mirror (FSM), which performs high-precision two-dimensional rotation to compensate for the telescope LOS deviation, according to the dual-port AIMC control algorithm. Moreover, the dual-port AIMC control method adds an AIMC loop on the basis of the feedback loop and adjusts the filter parameters adaptively according to the target angular velocity of the FSM, achieving higher disturbance suppression capability. The experimental results verify that the control method proposed can effectively compensate for the LOS deviation and suppress the composite frequency disturbance. In the 0-8Hz frequency band, the power spectral density integral values of the star centroid deviation in the X and Y directions of the FGS are, respectively, suppressed by 97.38% and 98.38%.

A novel voltage sag detection method for analyzing charging quality of electric vehicle

Electric car charging quality is severely impacted by voltage sag in the distribution network. Voltage sag events frequently occur in conjunction with other power quality disturbances, which leads to signal waveform distortion, making it difficult to identify voltage sag characteristics in composite power quality disturbance signals. The voltage sag amplitude, phase angle jump, and duration are all accurately detected in the composite power quality disturbance signal thanks to the method's two-stage waveform decomposition model, which eliminates the interference of the transition segment by pinpointing the beginning and ending points of the voltage sag using DQ transform. Moreover, the designed simulation experiments further verify that our proposed method outperforms other mainstream approaches, and it can be well used to effectively detect voltage sags of different causes under various signals that disturb the composite power quality, with an average accuracy rate of over 98.86 %.

Gut Microbiota and (Neuro)Inflammation: Involvement of Endotoxin in the Pathogenesis of Endogenous Psychoses

Background: there is a two-way relationship between the gut microbiota (GM) and the brain, both in normal and pathological conditions. It has been suggested that disturbances in GM composition and function can lead to the activation of (neuro) inflammation or its maintenance in mental disorders. Objective: analysis of scientific publications, including the results of our own research on the gut microbiota, its role in the modulation of brain functions and involvement in the maintenance of (neuro)inflammation in endogenous mental disorders. Material and method: using the keywords “gut–microbiota” and “microbiota–gut–brain axis/mental disorders”, “inflammation”, “neuroinflammation”, articles and reviews were searched in databases and electronic libraries of scientific publications Medline/PubMed, Scopus, Google Scholar, RSCI, and other sources. Results: on the basis of the analysis of literature sources, general information about GM, its composition, functions and main ways of interaction with the brain is given. The role of GM in the development and maintenance of (neuro)inflammation, currently considered as one of the pathogenetic mechanisms of mental disorders, is discussed. Particular attention is paid to the results of own studies on the role of endotoxin (ET) (lipopolysaccharide — LPS) and inflammation in the development of endogenous psychoses and the relationship of these indicators with the effectiveness of pharmacotherapy. Conclusion: it has been established that GM is an important participant and regulator of neuro-immune interactions. The possible role of GM in the maintenance of (neuro)inflammation in endogenous mental disorders and the participation of endotoxin aggression (EA) in the formation of therapeutic resistance in endogenous psychoses were revealed.

Dynamic control of an energy-saving process with two extractive dividing-wall columns for separation of acetone/methanol/butanone/tert-butyl alcohol mixtures

In the chemical and petrochemical industries, an azeotropic mixture of acetone/methanol/butanone/tert-butanol needs to be separated for high-purity products. Following a previous work in which an energy-saving process composed of two extractive dividing-wall columns (EDWCs) was developed for the quaternary system, this paper focuses on the issue of dynamic control for this process. Several control strategies in combined with temperature control, temperature-difference control and composition control are established to maintain the purity of all products in the face of disturbances in feed flow and feed composition. Dynamic simulations demonstrate that a conventional temperature control structure provides very poor control while a control strategy that used three-temperature-difference control for both EDWCs is the most effective.

Ecological Safety of Application of Nanotechnologies on the Example of Vegetables

The modern issue of environmental safety of using nanotechnologies to increase the yield of vegetables was studied. The technology was developed for incorporating nanoparticles (NPs) of metal microelements into the composition of the nutrient medium to obtain planting material with improved morphophysiological properties, due to which the yield of crops when planted in the soil almost doubles. It was confirmed that the absence of disturbances in microelement composition of plant and fruit tissues, the unchanged content of mobile phases in the soil after harvesting testifies to the environmental safety of nanotechnologies in biocultivation of vegetables under aseptic conditions.

SAT151 Assessments Of Body Composition In Women With Reactive Hypoglycemia

Abstract Disclosure: A. Adamska: None. A. Buczyńska: None. K. Łuka: None. A. Wiatr: None. K. Siewko: None. E. Duraj: None. A. Krętowski: None. A. Popławska-Kita: None. Introduction: Reactive hypoglycemia is characterized by low blood glucose level in non-diabetic patients. It manifests as a syndrome of adrenergic and neuroglycopenic symptoms in the postprandial period, and their resolution occurs after consuming carbohydrates. Reactive hypoglycaemia can also be seen in patients with insulin resistance and hyperinsulinism. In patients with reactive hypoglycemia can be observed disturbances in body composition. The aim of this study was to asses of body composition in women with reactive hypoglycaemia vs control group. Subjects and Methods: We examined 103 women: 49 subjects with RH and 54 control women matched for age and BMI. Four hours oral glucose tolerance test (OGTT) with 75 grams of glucose with estimation of serum glucose and insulin was performed. Body composition was analysed by dual-energy X-ray absorptiometry (DXA). Results: We did not observe differences in fat mass, fat free mass, android fat mass and fat free mass, gynoid fat mass and fat free mass and visceral adipose tissue estimated with DXA method between studied groups (all p>0.05). However, we have found positive relationship between fat mass and serum glucose concentration at 3rd hour of OGTT (r=0.29, p= 0.03) in the group of reactive hypoglycaemia. In the control group be observe relationships between android fat-free mass and serum glucose concentration at 3rd hour of OGTT (r=-0.3, p=0.02) and gynoid fat-free mass and serum glucose concentration at 3rd hour of OGTT (r=-0.27, p=0.04). Conclusions: Women with reactive hypoglycaemia is not differ in body composition estimated with DXA methods. However RH is connected in different manner with glucose homeostasis and fat and lean mass in comparison to control group. Presentation: Saturday, June 17, 2023

Composite-Disturbances-Observer-Based Finite-Time Fuzzy Adaptive Dynamic Surface Control of Nonlinear Systems With Preassigned Performance

This paper studies a nonlinear disturbance observer (NDO) based finite-time fuzzy adaptive dynamic surface control (DSC) of nonlinear systems (NSs) with external disturbances and preassigned performance indices. By constructing a type of finite-time preassigned-performance function (FTPF), the tracking error variable is confined within the boundaries of the FTPF such that the performance metrics, for instance, steady state error, and convergence time, could be satisfied. Incorporating fuzzy adaptive control with the NDO technique, an effective composite NDO (CNDO) scheme is built to reckon the unknown composite disturbances, including unknown external disturbances and fuzzy approximation errors, which implies that fuzzy approaching errors can be further cut down. It is confirmed that the closed-loop system is semi-globally practically finite-time stable (SPFTS), as well as the tracking error and convergence time satisfies the predefined performance indices. In the end, the validity of the CNDO-based finite-time adaptive DSC scheme has been evidenced by a practical example model.

Variation in abundance and habitat use of the critically endangered Microcebus gerpi across its fragmented range.

A link between the abundance of species and their degree of ecological specialization has previously been suggested within the primate order. Many species of lemurs were only recently described and even basic ecological data are not yet available for them. We investigated the habitat use, abundance, and habitat characteristics of the critically endangered Microcebus gerpi and evaluated potential impacts of vegetation structure and human disturbances on variations in its abundance. We determined abundance by systematic nocturnal surveys along 13 transects that were also used for characterizing the vegetation structure in seven study sites that were widely distributed within its range. Although M. gerpi occurred in all studied lowland rainforest and littoral forest fragments in central eastern Madagascar and therefore has a higher ecological plasticity and wider distribution than previously thought, its actual Area of Occupancy is very small (339.78 km2 ) due to an extreme degree of habitat fragmentation throughout its range. M. gerpi occurred with a mean encounter rate of 3.04 individuals/km but abundance varied substantially between sites (0.75-4.5 individuals/km). Statistical modeling revealed that the cover of small- to medium-sized trees had a positive impact on the abundance of M. gerpi, whereas a composite disturbance score (CDS), formed on the basis of information on the prominence of fires, cattle, charcoal production and wood extraction inside and around the forest, had a negative impact on abundance. These results suggest that M. gerpi is slightly less threatened than expected because of its larger geographic range, but also that it responds negatively to human disturbances. These findings raise strong conservation concerns and question the long-term viability of the remaining small and isolated populations of this arboreal solitary forager.

Rigorous simulation and comprehensive analysis for the novel glycerol carbonate (GC) production process via indirect conversion of CO2

Aiming to achieve net-zero and negative carbon emissions, an innovative process that converts CO2 into glycerol carbonate (GC) through an indirect pathway was rigorously investigated for the first time. The study began with a thorough consideration of the thermodynamic properties and reaction kinetics. Subsequently, alternative processes varying in reactor configurations were proposed. Fuzzy optimization was performed on the proposed processes to consider the competing objectives of minimizing production costs and reducing CO2 emissions. With thorough analysis, we have concluded that the process employing two reactors in a cascade (the “2R-process”) is the most attractive. This process shows promise in both economic and decarbonization aspects. Under a targeted internal rate of return (IRR) of 15%, the minimum required selling price (MRSP) for GC is 0.628 USD/kg. Additionally, the entire process fixes 0.238 kg of CO2 per kg of GC produced (CO2-e = −0.238). These indices are superior to those of the previously proposed process based on reactive distillation (MRSP = 1.328 USD/kg, CO2-e = +0.209), and to many cost data for GC available in the literature (2.4 to 6.0 USD/kg). Finally, a control structure was established for the proposed process to manage the specified feed disturbances in flowrate and composition, without the need for any composition measurements. The control strategy involves the use of selective temperature control for the reactor, and two temperature difference controllers for the extractive distillation column (i.e. control scheme 2). In summary, the proposed process reveals significant potential to serve as an essential component in a future decarbonized economy.

Control structure selection of increased‐pressure extractive distillation process for DMC‐MeOH azeotropic mixture

AbstractProducing dimethyl carbonate (DMC) as a green chemical with the desired purity is important in the industry. Although studies on the steady‐state design of energy‐efficient extractive distillation processes are important for the purification of DMC‐methanol (DMC‐MeOH) azeotropic mixtures, the dynamic controllability of these processes is also critical in the case of feed condition changes, and it should be investigated carefully. Results of the limited studies in the literature show that changing the operating pressures in extractive distillation processes might have different effects on the dynamic controllability of different systems. Thus, in this study, alternative control strategies are developed for a recently proposed increased‐pressure extractive distillation process to separate DMC‐MeOH mixture. All control structures are designed using inferential temperature controllers, which have a general acceptance in industrial applications. Effects of different ratio controllers are investigated by evaluating the dynamic responses of control structures for disturbances in feed flowrate and composition. Two metrics including integral absolute error and steady‐state deviation of purities are used in the evaluation of alternatives. Results of dynamic simulations show that a control structure including reflux ratio controller is not a suitable strategy for this process. It is demonstrated that a control structure including reflux to feed ratio controller for both distillation columns is necessary for the robust and efficient control of a pressure‐increased extractive distillation process. These efficient dynamic results support the economic advantage of increased‐pressure extractive distillation process separating DMC‐MeOH azeotropic mixtures.

Resveratrol alleviates perinatal methylmercury-induced neurobehavioral impairments by modulating the gut microbiota composition and neurotransmitter disturbances.

Methylmercury (MeHg), a potent neurotoxic substance, causes adverse health outcomes by modulating metabolites through altered gut microbiota patterns. Among the many metabolites, neurotransmitters play a particularly important role in the nervous system and behavior. Resveratrol (RSV) has been investigated as an antiaging, antioxidant, anti-inflammatory, and neuroprotective agent. The current study evaluated that RSV is protective of neurodevelopmental toxicity induced by MeHg and further explored the underlying mechanisms. Sprague-Dawley rats were treated with 1.2 mg/kg/d of MeHg, and the effects were evaluated after supplementation with RSV (20 mg/kg/d). The results indicated that MeHg had adverse effects on early neurodevelopmental indicators in the experimental group offspring as compared to control pups. Interestingly, RSV significantly improved the MeHg-induced delays in the neurobehavioral reflexes and reduced the total mercury (THg) concentration in the colons of the offspring rats. In agreement, RSV administration improved the gut microbiota diversity and structure by increasing the abundance of probiotics and upregulating the expression of tight junction proteins. It also ameliorated the MeHg-induced abnormalities in the expression profiles of neurotransmitters. Furthermore, eight key bacteria that were strongly linked with the neurotransmitters and neuroreflex parameters were identified. Taken together, these results demonstrate that RSV treatment effectively reduces the occurrence of neurodevelopmental toxicity caused by perinatal MeHg exposure by modulating the intestinal flora and neurotransmitter metabolism. These findings provide a new therapeutic approach for treating MeHg-induced neurotoxicity. The cover image is based on the Research Article Resveratrol alleviates perinatal methylmercury-induced neurobehavioral impairments by modulating the gut microbiota composition and neurotransmitter disturbances by Fang Chen et al., https://doi.org/10.1002/tox.23973.

Dynamic real-time energy saving control of pressure-swing distillation based on artificial neural networks

Parameter variation can increase economic costs and energy consumption in distillation process when disturbances occur. In this work, a dynamic optimization control model based on ANNs was developed. Composition disturbances in pressure-swing distillation with and without heat integration to separate isoamyl alcohol and toluene were regarded as the research object. The economic cost and energy consumption were effectively reduced by predicting the most optimal operating parameters during the disturbance process and controlling the process in real time. In the absence of heat integration, the energy consumption of the control structure based on ANNs (CS2) is reduced by 1.68% and 1.70% respectively compared to traditional control structure (CS1) during ± 20% composition disturbance. In partial heat integration, the energy consumption of the control structure based on ANNs (CS4) is reduced by 3.24% and 2.68% compared to traditional control structure (CS3). TAC is saved by 3.51% and 3.31% when reaching stability.

Effect of PLA2G6 and SMPD1 Variants on the Lipid Metabolism in the Cerebrospinal Fluid of Patients with Parkinson's Disease: A Non-targeted Lipidomics Study.

Sleep patterns are more frequently interrupted in patients with Parkinson's disease (PD), and it is still unclear whether genetic factors are involved in PD-related sleep disorders. In this study, we hypothesize that PD-associated genetic risk affects lipid metabolism, which in turn contributes to different types of sleep disorders. We used a non-targeted lipidomics to explore the lipid composition of cerebrospinal fluid (CSF) exosomes derived from patients with PD carrying phospholipase A2 Group VI (PLA2G6) and sphingomyelin phosphodiesterase 1 (SMPD1) mutations. PLA2G6 mutations (c.1966C>G, Leu656Val; c.2077C>G, Leu693Val; c.1791delC, His597fx69) significantly increase the exosomal content of glycerophospholipids and lysophospholipids, specifically phosphatidylcholine (PC) and lysophosphatidylcholine (LPC). Exosome surface presence of melatomin receptor 1A (MTNR1A) was detectable only in patients with PLA2G6 mutations. We have further shown that, in patients with PD carrying PLA2G6 mutations, sleep latency was significantly longer compared to those carrying WT PLA2G6, and we speculate that functional PLA2G6 mutations lead to structural changes and lipid deregulation of exosomes, which in turn alters exosomal cargo and affects PD-related sleep disorders. In SMPD1, G508R variant-carrying patients with PD abundance of sphingomyelins was significantly higher and had significantly shorter rapid eye movement sleep. Our study demonstrated that the disturbed composition and function of CSF-derived exosome lipidome during the pathological stage of PD may affect different types of sleep disorder in PD.

Design and control of an energy-efficient intensified process for biobutanol purification from isopropanol-butanol-ethanol (IBE) fermentation broth

Biobutanol is one of the most preferable alternative fuels because of its superior fuel properties compared to other biofuels. In recent years, biobutanol production through isopropanol (IPA)-butanol-ethanol (IBE) fermentation has gotten more attention than acetone-butanol-ethanol (ABE) fermentation. However, the downstream separation process of this production is very energy intensive due to the several azeotropes. In this study, an energy-efficient process configuration including a reactive distillation column is proposed to break the azeotropes. In the proposed configuration, water present in the azeotropic mixture is consumed by a water-ethylene oxide (EO) reaction. Steady-state results show that the proposed configuration provides a 30% decrease in energy consumption and a 26.7% reduction in total annual cost (TAC) compared to the configurations in the literature, while ethylene glycol is obtained as a by-product besides the biobutanol of 99.5% purity. Additionally, two plantwide control structures are developed, and the dynamic controllability of the configuration is examined. Dynamic results illustrate that a robust control is provided with the proposed control structure 2 (CS2) when it is tested against disturbances in feed flowrate and feed composition.

Multi-objective optimization and composition control of Sargent dividing-wall distillation columns

Sargent dividing-wall distillation columns (DWDCs) can significantly reduce the energy consumption required for separating quaternary mixtures. However, their effective design and strict product purity control can be challenging to achieve, which severely limits their development and application in the industry. To address this problem, a systematic study on their design and control was conducted in this article based on the case of separating a quaternary mixture of methanol, ethanol, 1-propanol, and n-butanol. Firstly, a multi-objective optimization framework was proposed, in which the total annual cost (TAC), CO2 emission, and condition number (CN) were taken as objective functions, and NSGA-III and TOPSIS algorithms were employed to search for the optimal design of the Sargent DWDC. To avoid the convergence difficulty issue of the rigorous model of the Sargent DWDC, a Random Forest surrogate model was used in the optimization process to predict its steady-state and dynamic performance accurately and rapidly. Secondly, a novel composition control structure, consisting of seven control loops, was proposed to achieve strict product purity control of the Sargent DWDC. Three composition difference control loops, located at the prefractionator and the middle column, are responsible for maintaining their composition profile shapes and thus mitigating the impact of feed disturbances on the main column. Additionally, four composition control loops, located at the main column, are responsible for strictly controlling the purities of the distillate, upper sidestream, lower sidestream, and bottom products. Dynamic simulation results showed that the Sargent DWDC can be operated stably under the proposed composition control structure for various feed composition and feed flow rate disturbances. These results not only confirmed the capability of the proposed composition control structure to strictly maintain product purities in the Sargent DWDC but also validated the effectiveness of the proposed multi-objective framework in achieving an energy-efficient and controllable Sargent DWDC.

Line loss calculation model of low-voltage distribution network under harmonic and three-phase unbalance disturbances and its experimental validation

With the grid integration of distributed power sources and traction loads, the power quality problem of the power system has become more and more serious, aggravating the distribution network line losses, so it is important to study the calculation model of distribution network line loss under power quality disturbance in order to find loss reduction measures. This paper first theoretically derives the calculation model of line loss of low-voltage distribution network under separate disturbance of 2 common power quality problems, namely, harmonics and three-phase unbalance. Then, using the composite power quality disturbance decoupling method, the calculation model of line loss of low-voltage distribution network under the disturbance of harmonics and three-phase unbalance is derived, which improves the accuracy of line loss calculations. Finally, experiments are conducted for each part by Matlab/Simulink simulation tool to verify the correctness of the theoretical derivation.

Composite resilient state tracking and disturbance rejection control for periodic piecewise polynomial delay systems with multiform disturbances

In this study, we scrutinize the problems of resilient state tracking control (RSTC) and disturbance rejection (DR) for periodic piecewise polynomial delay systems in the presence of multiform disturbances and gain fluctuations. Specifically, we address both exosystem-induced disturbances and norm-bounded disturbances. Firstly, to tackle effectively the disturbances that are produced by exosystems, the disturbance observers are tailored, which estimates the disturbance in a precise manner. Secondly, the repercussions of norm-bounded disturbances can be lessened by accounting an extended dissipative performance. Moreover, by amalgamating the outcomes of the disturbance observer with the feedback-based tracking control, a DR-based RSTC is constructed. In addition, some parameter variations in the controller gain are taken into consideration in order to guarantee resiliency against unexpected flaws. Besides, the adequate conditions are derived in the form of linear matrix inequalities by making use of Lyapunov stability theory, new double integral inequality and extended Wirtinger’s inequality. Furthermore, the relation for acquiring the controller and observer gain matrices is formulated based on the established criteria. Finally, a numerical example with simulation depiction is presented to show the favour performance and capability of the designed controller.

Spacecraft Attitude Stabilization Control with Fault-Tolerant Capability via a Mixed Learning Algorithm

The issue of active attitude fault-tolerant stabilization control for spacecrafts subject to actuator faults, inertia uncertainty, and external disturbances is investigated in this paper. To robustly and accurately reconstruct actuator faults, a novel mixed learning observer (MLO) is explored by combining the iterative learning algorithm and the repetitive learning algorithm. Moreover, to guarantee robust spacecraft attitude fault-tolerant stabilization, by synthesizing the mixed learning algorithm with the sliding mode controller, a novel mixed learning sliding-mode controller (MLSMC) is designed based on the separation principle, in which the mixed learning algorithm is used to update composite disturbances online, including fault errors, inertia uncertainty, and external disturbances. Finally, a numerical example is provided to demonstrate the effectiveness and superiority of our proposed spacecraft attitude fault-tolerant stabilization control approach.

Design of a multiproduct reactive distillation system for DEC and EMC production

Multiproduct processes are gaining interest as part of the development of intensified structures. In this work, an optimal design of a flexible diethyl carbonate (DEC) and ethyl methyl carbonate (EMC) multiproduct process is developed. DEC is a main product that is commonly produced through multi-reaction dimethyl carbonate (DMC) transesterification. However, EMC, an intermediate product, also has a significant market interest. This work explores the use of a multiproduct process that integrates a reactive and a separation column to produce either DEC or EMC. The design was obtained aided by a process optimization task with genetic algorithms tied to Aspen Plus rigorous simulations. The results show that a common design for the production of both products can be obtained, with total annual cost savings of 22% with respect to a base design taken from the literature. Additionally, an initial dynamic analysis shows that the multiproduct process can be controlled in the face of feed flow and composition disturbances.