Effect of sampling time on PID controller design for a heat exchanger system

Closed-loop identification with routine operating data: Effect of time delay and sampling time

Closed-Loop Identification using Routine Operating Data: the Effect of Time Delay

The objective of this paper is to design a controller for servo motor in discrete-time systems. The effect of sampling time on the proposed design will further discussed. Real-time data gained from the experimental is used to obtain the transfer function to design the PID controller. In order to get the optimal value of PID controller, ARX model structure was implemented. The effectiveness of the design is validated using MATLAB/Simulink. From the results obtained, it shows that the output for PID controller will gives the best performance of 87.79% at 55 ms sampling time.

Effects of time and sampling location on concentrations of β-hydroxybutyric acid in dairy cows

Shell and tube heat exchanger system is widely used in chemical plants because it can sustain wide range of temperature and pressure. The main purpose of a heat exchanger system is to transfer heat from a hot fluid to a cooler fluid, so temperature control of outlet fluid is of prime importance. To control the temperature of outlet fluid of the shell and tube heat exchanger system a conventional PID controller can be used, for better disturbance rejection and more optimal control a feed forward controller can also be employed. Due to inherent disadvantages of conventional control techniques, model based control technique is employed and an internal model based PID controller is developed to control the temperature of outlet fluid of the shell and tube heat exchanger system. The designed controller regulates the temperature of the outgoing fluid to a desired set point in the shortest possible time irrespective of load and process disturbances, equipment saturation and nonlinearity. The internal model based PID controller provides a satisfactory performance in both steady state and transient state. The developed internal model based PID controller has demonstrated 84% improvement in the overshoot and 44.6% improvement in settling time as compared to the classical controller.

Variability of biofouling communities on fish cage nets: A 1-year field study at a Norwegian salmon farm

Research into the impacts of climate change on lakes requires novel experimental methods that enable realistic tests of the effects of increased water temperatures on communities. This article describes the design of a heating system that has been used in situ to study the effects of an increase in lake surface temperatures on littoral communities. Water within four 700‐L enclosures was heated using a propane‐fuelled heat exchange system. Hot water was circulated through a network of heat exchange pipes nested in the bottom of enclosures and temperature within the enclosures was controlled electronically by regulating water flow through a series of valves. The system performed well, with temperatures within warmed enclosures paralleling diurnal fluctuations within control enclosures. The average temperature difference between warm and control enclosures of 4.5°C was close to our target temperature difference of 5°C. Strengths of the experimental system are discussed and potential improvements, including improved heat retention and a design adjustment to facilitate repair in the event of lightning damage are noted. The system is adaptable to larger and smaller volumes, different temperature regimes, and can be adapted for use in pelagic systems.

The hardware used for software implementation on a physical system introduces uncertainty into the controller. If neglected during design, this uncertainty can lead to poor controller performance, resulting in significant design and verification iterations. In this work, the effect of sampling time, quantization, and fixed-point computation are directly accounted for in the control design. Sampling time is compensated for by a discrete-time controller. A generic methodology is developed for modeling the worst-case scenario effect of quantization and fixed-point computation on the control commands. The cold-start emission control problem is used as a case study, and a discrete-time sliding surface controller is developed. Verification is performed to ensure the estimated worst-case scenario uncertainty bounds are accurate. The bounds are incorporated into a modified version of the control laws. During simulation the modified controller demonstrates significant reduction in tracking error in the presence of hardware imprecisions.

Seasonal variation in testis size, gonadotrophin secretion and pituitary responsiveness to GnRH in rams of two breeds differing in time of onset of the breeding season

Steam jet large-temperature-drop heat exchange system (SJHE) is presented to improve the heat exchange effect between exothermic and endothermic media in the heat exchange process. In this paper, with the higher efficient CRMC ejector, the mathematical model of the SJHE system is constructed. We compared the application scopes of two system constructions with 10 different working fluids and select the more feasible system construction as the optimal system. Based on the real properties of 10 environment-friendly dry pure fluid, R141b is screened as the best cycle working fluid for the system, using which the exothermic medium can be reduced to 33.7 °C in the district heating situation (primary water supply temperature: 130 °C, and the temperature lift range of secondary water is 45–60 °C). Moreover, the thermodynamic characteristics of the SJHE system are evaluated to achieve a better understanding of the thermal performance of this new heat exchanger system.

Evaluation of bioaerosol sampling techniques for Legionella pneumophila coupled with culture assay and quantitative PCR

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTEffect of ventilation and sampling time on environmental tobacco smoke component ratiosPaul R. Nelson, David L. Heavner, Barbara B. Collie, Katherine C. Maiolo, and Michael W. OgdenCite this: Environ. Sci. Technol. 1992, 26, 10, 1909–1915Publication Date (Print):October 1, 1992Publication History Published online1 May 2002Published inissue 1 October 1992https://pubs.acs.org/doi/10.1021/es00034a005https://doi.org/10.1021/es00034a005research-articleACS PublicationsRequest reuse permissionsArticle Views162Altmetric-Citations42LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts

Arbuscular mycorrhizal fungal communities in buffelgrass pasture under intercropping and shading systems in Brazilian semiarid conditions

ObjectiveSevere pneumonia is a common infectious disease with high morbidity and mortality. Early etiological diagnosis is crucial for improving the prognosis. The aim of this study is to evaluate the clinical value of sampling time of mNGS in patients with severe pneumonia.MethodsThis retrospective study enrolled 105 patients with severe pneumonia. mNGS was performed on bronchoalveolar lavage fluid (BALF). Patients were divided into the sampling time ≤ 72h vs sampling time >72h groups and survivors vs non-survivors groups according to their sampling time and prognosis. Clinical characteristics, the adjustment of antibiotics and clinical prognostic value were evaluated.ResultsOur study showed that, early sampling of mNGS can significantly shorten the mechanical ventilation time (p = 0.007) and hospitalization time (p = 0.004). In the non-survivors group, CURB-65, SOFA, and APACHE II scores were higher. Age (OR: 1.051, 95% CI: 1.004–1.100, p = 0.034), chronic respiratory diseases (OR: 4.639, 95% CI: 1.260–17.082, p = 0.021), immunosuppression (OR: 5.008, 95% CI: 1.617–15.510, p = 0.005) and SOFA score on the day of mNGS sampling (OR: 1.492, 95% CI: 1.212–1.837, p < 0.001) were independent risk factors of in-hospital mortality. The most common pathogens were Klebsiella pneumoniae and Human gammaherpesvirus 4. The proportion of appropriate and targeted antibiotics adjusted was significantly higher than that in the sampling time > 72h group, and the proportion of antifungal and antiviral agents adjusted was lower. In the early sampling group, it was significantly decreased in the CRP, PCT level and NEU% at discharge.ConclusionThis study demonstrated that early sampling of mNGS could shorten the time of mechanical ventilation and hospitalization of patients with severe pneumonia. Patients with higher SOFA score on the day of sampling had a poorer prognosis. It emphasizes that early sampling of mNGS has a positive value.

Heat exchanger system is widely used in chemical plants because it can sustain wide range of temperature and pressure. The main purpose of a heat exchanger system is to transfer heat from a hot fluid to a cooler fluid, so temperature control of outlet fluid is of prime importance. To control the temperature of outlet fluid of the heat exchanger system a conventional PID controller can be used. Due to inherent disadvantages of conventional control techniques, Fuzzy logic controller is employed to control the temperature of outlet fluid of the heat exchanger system. The designed controller regulates the temperature of the outgoing fluid to a desired set point in the shortest possible time irrespective of load and process disturbances, equipment saturation and nonlinearity.