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The effects of mechanical vibrations on control system stability could be significant in control systems designed on the assumption of rigid-body dynamics, such as launch vehicles. Vibrational loads can also cause damage to launch vehicles due to fatigue or excitation of structural resonances. This paper investigates a method to control structural vibrations in real time using a finite number of strain measurements from a fiber Bragg grating (FBG) sensor array. A scaled test article representative of the structural dynamics associated with an actual launch vehicle was designed and built. The main modal frequencies of the test specimen are extracted from finite element analysis. A model of the test article is developed, including frequency response, thruster dynamics, and sensor conversion matrices. A model-based robust controller is presented to minimize vibrations in the test article by using FBG measurements to calculate the required thrust in two cold gas actuators. Controller performance is validated both in simulation and on experiments with the proposed test article. The proposed controller achieves a 94% reduction in peak–peak vibration in the first mode, and 80% reduction in peak–peak vibration in the second mode, compared to the open loop response under continuously excited base motion. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) connected to combined sewer systems must cope with high flows during wet-weather conditions, often leading to bypass and thus pollution of water bodies. Radar rainfall forecasts coupled with a rainfall-runoff model provides flow and volume forecasts that can be used for deciding when to switch from normal to wet-weather operation, which temporarily allows for higher inflow. However, forecasts are by definition uncertain and may lead to potential mismanagement, e.g., false alarms and misses. Our study focused on two years of operational data from the Damhuså sewer catchment and WWTP. We used the Relative Economic Value (REV) framework to optimize the control parameters of a baseline control strategy (thresholds on flow measurements and radar flow prognosis) and to test new control strategies based on volume instead of flow thresholds. We investigated two situations with different objective functions, considering higher negative impact from misses than false alarms and vice versa, and obtained in both cases a reduction of the rate of false alarms, higher flow thresholds and lower bypass compared to the baseline control. We also assess a new control strategy that employs thresholds of predicted accumulated volume instead of predicted flow and achieved even better results. [ABSTRACT FROM AUTHOR]

Conventionally, neutral beam injection (NBI) in tokamaks is controlled via engineering parameters such as injection voltage and power. Recently, the high-fidelity real-time NBI code RABBIT has been coupled to the discharge control system of ASDEX Upgrade. It allows to calculate the NBI fast-ion distribution and hence the properties of NBI in real-time, making it possible to control them directly. We successfully demonstrate control of driven current, ion heating and stored fast-ion energy by modifying the injected beam power. A combined ECRH and NBI controller is also successfully tested, which is able to adjust the heating mix between ECRH and NBI to match a certain desired ion heating fraction at given total power. Further experiments have been carried out towards control of the ion heat flux (i.e. ion heating plus collisional heat transfer between ions and electrons). They show good initial success, but also leave room for future improvements as the controller runs into instabilities at too high requests. [ABSTRACT FROM AUTHOR]

The hybridization of multiple energy sources is crucial for electric vehicles to deliver the same performance as modern fossil fuel-based automobiles. This paper presents a torque and speed control strategy for an electric vehicle DC traction motor by regulating the power flow from two energy sources, namely battery and supercapacitor systems, to resist unpredictable disturbances. A control system with three control loops is applied to regulate the speed of the traction motor. The outer speed control loop is a nonlinear state feedback controller with a disturbance observer, which is capable of handling non-linear systems with unpredictable disturbances. The inner voltage and current control loop are precisely tuned PI controllers. Using an adaptive energy management method that varies depending on the state of charge of the source, the total reference current needed to support the load demand is split between two sources. A laboratory prototype system model is generated, and the performance is analyzed under motoring and regenerative braking conditions. For monitoring and controlling the system, the dSPACE DS1202 real-time simulator is employed. The performance of the proposed control system is evaluated and it is found that the settling time to settle within a tolerance band of 1% is 0.75 s. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Model Predictive Control (MPC) of Urban Drainage Systems (UDS) has been established as a cost‐effective method to reduce pollution. However, the operation of large UDS (containing over 20 actuators) can only be optimized by oversimplifying the UDS dynamics, potentially leading to a decrease in performance and reduction in users' trust, thus inhibiting widespread implementation of MPC procedures. A Heuristic And Predictive Policy (HAPPy) was set up, relying on the dynamic selection of the actuators with the highest impact on the UDS functioning and optimizing those in real‐time. The remaining actuators follow a pre‐set heuristic procedure. The HAPPy procedure was applied to two separate UDS in Rotterdam with the control objective being the minimization of overflow volume in each of the two cases. Results obtained show that the level of impact of the actuators on the UDS functioning changes during an event and can be predicted using a Random Forest algorithm. These predictions can be used to provide near‐global optimal actuator settings resulting in the performance of the HAPPy procedure that is comparable to a full‐MPC control and outperforming heuristic control procedures. The number of actuators selected to obtain near‐global optimal settings depends on the UDS and rainfall characteristics showing an asymptotic real‐time control (RTC) performance as the number of actuators increases. The HAPPy procedure showed different RTC dynamics for medium and large rainfall events, with the former showing a higher level of controllability than the latter. For medium events, a relatively small number of actuators suffices to achieve the potential performance improvement. Key Points: The relative impact of actuators on the performance of real‐time control strategies changes during and in‐between eventsDynamically selecting actuators for optimization can ensure near‐global optimal control for urban drainage systemsUsing random forest algorithms, the most influential actuators can be selected in real‐time [ABSTRACT FROM AUTHOR]

Urban areas are constantly developing and thereby affect the local water cycle. Real‐time control (RTC) strategies are used to operate urban drainage systems optimally during these transitions. This paper aims to develop a methodology to study the impacts of common gradual changes occurring in the urban environment (densification of the urban area and implementation of blue‐green infrastructure), forming cumulative transitions, on the functioning of real‐time optimization procedures. A new generic methodology, relying on a comprehensive evaluation strategy based on three indicators assessing the continued optimal performance of RTC was proposed. This methodology was applied to two urban drainage catchments in Eindhoven and Rotterdam using both probabilistic and projected transitional paths. Based on the results obtained it can be noted that the performances of the RTC procedures were not strongly affected by the modeled transitions although the relative performance compared to the maximum performance potential decreases significantly with the large‐scale implementation of blue‐green infrastructure, indicating that the revision of RTC procedures could improve the sewer system functioning further. The relative performance loss associated with the modeled transitions was higher for model predictive control compared to heuristic RTC procedures for one case study and vice versa for the other. Continuous re‐evaluation of the RTC strategy is, therefore, an important but overlooked part of the implementation of RTC procedures. Key Points: Urban transitions are modeled to assess the effect on optimal control (RTC) efficacyStrong divergence from optimality was associated with SUDS implementationLong‐term implementation of RTC should include a regular re‐evaluation of the strategy [ABSTRACT FROM AUTHOR]

• Five real time control (RTC) strategies were developed and tested. • Ten organic chemicals were tested, covering various physicochemical properties. • Effective RTC strategies could improve the removal of many organic chemicals. • Effective RTC strategies alleviated performance variations upon various operations. • RTC biofilters maintained comparable accumulation levels of chemicals in media. Biofilters are among the most popular nature-based systems for treating stormwater and delivering multiple environmental benefits. However, as a passive system, their performance tends to be inconsistent in removing emerging organic contaminants produced by anthropogenic activities that can be persistent, mobile, and toxic. Thus, in this study, real time control (RTC) of stormwater biofilters is introduced to enhance the removal of a diverse range of organic chemicals. Laboratory columns were employed to investigate the performance of five RTC strategies, i.e., dynamic soil moisture control (RTC-Moisture), infiltration rate control (RTC-IR), pre-drain (RTC-PreDrain), fully unsaturated (RTC-UnSat), and fully saturated (RTC-FulSat). These RTC strategies were tested under varying rainfall sizes, as well as dry and wet conditions. Additionally, the study examined the accumulation of organic chemicals in the media. The results revealed that RTC-Moisture, RTC-IR, and RTC-PreDrain were the top three performing strategies, which achieved a significantly higher removal rate than Non-RTC biofilters for the majority of tested organic chemicals (p -value < 0.05). The best RTC strategy, RTC-Moisture, not only had the highest overall performance (average removal rate of 76.1 %) but was also least affected by various rainfall events. Despite a better chemical removal found in RTC-Moisture and RTC-PreDrain , there was no significant overall increase in the accumulation of organic chemicals within the media (p -value > 0.05) when compared to Non-RTC biofilters. This may indicate that the biodegradation process could be promoted in the well-performing RTC biofilters. This study confirms the possibility of using RTC strategies to enhance organic chemical removal in stormwater biofilters. [Display omitted] [ABSTRACT FROM AUTHOR]

Wastewater utilities face competing priorities as they work to protect human health and water quality, and to maintain infrastructure in their communities. Budgetary constraints can be especially pronounced among small to medium-sized utilities. Utilities are increasingly turning to so-called intelligent water approaches as a cost-effective alternative to upgrading aging infrastructure. Intelligent water encompasses automated control and real-time decision support technologies and can be applied at scale to large and small utilities alike accommodating differences in needs, capabilities, and funds. Intelligent water upgrades can be designed to optimize existing conveyance, storage, and treatment during storms to help mitigate flooding and combined sewer overflows. The most promising real-time control algorithms coordinate control of upstream and downstream assets and are designed using urban hydrologic and hydraulic modeling software. The capabilities of legacy software, however, can sometimes inhibit the creation of sophisticated control algorithms. In this paper, we present PySWMM — an open-source Python wrapper developed for the EPA Storm Water Management Model (SWMM). PySWMM enables runtime interactions with the SWMM computational engine to flexibly read, modify system parameters, and control digital infrastructure during a simulation. Crucially, it allows modelers to easily combine SWMM with the rich set of scientific computing, big data, and machine learning modules found in the Python ecosystem. We highlight two real-world intelligent water case studies utilizing PySWMM in the cities of Cincinnati and Columbus, Ohio where it has helped to eliminate tens of millions of gallons of combined sewer overflows annually. • PySWMM is an open-source Python wrapper for EPA SWMM. • Embedding SWMM into Python's scientific computing ecosystem expands its capabilities. • Two utility CSO management applications leveraging PySWMM for real-time control and decision support are described. • Application results demonstrate how intelligent control can help reduce CSOs by tens of millions of gallons annually. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Polytechnic is the property of Journal of Polytechnic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Reducing transportation-related energy consumption and greenhouse gas (GHG) emissions have been a common goal of public agencies and research institutes for years. In 2013, the total energy consumed by the transportation sector in the United States was as high as 24.90 Quadrillion BTU. U.S. Environmental Protection Agency (EPA) reported that nearly 27% GHG emissions resulted from fossil fuel combustion for transportation activities in 2013. From a vehicle perspective, innovative powertrain technologies, such as hybrid electric vehicles (HEVs), are very promising in improving fossil fuel efficiency and reducing exhaust emissions. Plug-in hybrid electric vehicles (PHEVs) attracted most of the attention due to their ability to also use energy off of the electricity grid, through charging their batteries, thereby achieving even higher overall energy efficiency. At the heart of the PHEV technologies, the energy management system whose functionality is to control the power streams from both the internal combustion engine (ICE) and the battery pack based on vehicle and engine operating conditions, has been studied extensively. In the past decade, a large variety of EMS implementations have been developed for HEVs and PHEVs, whose control strategies may be well categorized into two major classes: a) rule-based strategies which rely on a set of simple rules without a priori knowledge of driving conditions. Such strategies make control decisions based on instant conditions only and are easily implemented, but their solutions are often far from being optimal due to the lack of consideration of variations in trip characteristics and prevailing traffic conditions; and b) optimization-based strategies which are aimed at optimizing some predefined cost function according to the driving conditions and vehicle’s dynamics. The selected cost function is usually related to the fuel consumption or tailpipe emissions. Based on how the optimization is implemented, such strategies can be further divided into two groups: 1) off-line optimization which requires a full knowledge of the entire trip to achieve the global optimal solution; and 2) short-term prediction-based optimization which takes into account the predicted driving conditions in the near future and achieves local optimal solutions segment by segment within an entire trip. However, major drawbacks of these strategies include: 1) heavy dependence on the a priori knowledge of future driving conditions; and 2) high computational costs that are difficult to implement in real-time.View the NCST Project Webpage

Nowadays, in the management of water distribution networks (WDNs), particular attention is paid to digital transition and the improvement of the energy efficiency of these systems. New technologies have been developed in the recent years and their implementation can be crucial to achieve a sustainable level of water networks, namely, in water and energy losses. In particular, Digital Twins (DT) represents a very innovative technology, which relies on the integration of virtual network models, optimization algorithms, real time data collection, and smart actuators information with Geographic Information System (GIS) data. This research defines a new methodology for an efficient application of DT expertise within water distribution networks. Assuming a DMA of a real water distribution network as a case study, it was demonstrated that a fast detection of leakage along with an optimal setting of pressure control valves by means of DT together with an optimization procedure can ensure up to 28% of water savings, contributing to significantly increase the efficiency of the whole system. [ABSTRACT FROM AUTHOR]

The topic of this paper is the recovery of energy from urban waters, which can be performed in water distribution networks (WDNs) through hydraulically and electrically regulated pumps operating as turbines (PATs). The time-varying operating conditions make real time control (RTC) techniques necessary for adjusting both hydropower generation and service pressure regulation. An unsteady flow model allows simulating the skeletonized layout of a real WDN, and assessing the effectiveness of the RTC. Two control schemes, operating at small and large-time steps, respectively, are presented and compared. The numerical simulations prove the application of the prototype feasible in real WDNs, providing effective hydropower generation and service pressure regulation. While the hydropower produced by the two controllers is similar, the first prevails in terms of closeness of the controlled pressure-head at the critical node to the desired set-point, whereas the second performs better in terms of control cost. [ABSTRACT FROM AUTHOR]

This paper introduces PLC (programmable logic controller)-based real-time motion control of 2D galvanometer scanners under consideration of different sensor information. The Fraunhofer IWS developed ESL2-100 module works as a locally separated client of a higher-level machine control to drive the scanner. The EtherCAT field bus supports extensive and constant exchange of information between the control levels. An application example, therefore, is the spatially resolved surface structuring of large areas using a continuous wave laser. In this application, the scanner must move the laser beam to predefined positions, stop there during the processing time, and jump to the next position. Frequencies up to 2 kHz are applicable depending on the scanner performance. The working area of a scanner can be extended by moving the scanner head with Cartesian machine axes. In the presented solution, the scanner control records these movements via encoder signals and captures the geometrical boundaries of the workpiece, i.e., previous operated areas, via cameras. The obtained data are included in the real-time calculation of scanner position data and laser emission signals. These measures maintain precision in positioning the patterns for surface structuring and adapt them to existing contours. The processing of the control data, the 2D-on-the-fly correction, and the correction of the target positions are done on the PLC level. Then, within one control cycle, multiple position data are sent in blocks from the PLC to the ESL2-100 module within one control cycle. At the end, the ESL2-100 module converts the field bus data into the scanner control protocol (here SL2-100 protocol). The approach described enables the deterministic calculation of the scan movement and responds dynamically to changing conditions by linking all necessary sensor information on one control platform. [ABSTRACT FROM AUTHOR]

The aim of this article is design, fabricate, and control a conceptual prototype of a flexible wearable robot to increase fingers' force using a novel cable mechanism. In this robot, force and position are controlled in separate phases by a fuzzy system equipped with emotional learning. A Flexible structure has been chosen for this robot, because flexible gloves are lighter and much more suitable for use in daily tasks compared to rigid structures. Since this system is supposed to be substituted for weak or damaged limb, it should have a behavior similar to the body organs as much as possible. Therefore, a novel mechanism, inspired by the natural movement mechanism of the human hand, has been designed and tried to use a control method similar to the human brain. In order to control the glove, a proportional linear and a fuzzy controller were selected and designed. Then they were implemented through the Simulink environment of MATLAB software and applied to the glove using a real-time interface system. Finally, through some experiments, the performance of the glove and controllers have been evaluated and compared in the case of using linear and emotional learning fuzzy controllers. As expected, using the fuzzy controller with an emotional learning system makes low tracking errors result and represents appropriate performance. Compared to the linear controller, the overshoot decreased up to the one-third, and the settling time declined to one-fifth. [ABSTRACT FROM AUTHOR]

Extreme weather and the proliferation of impervious areas in urban watersheds increases the frequency of flood events and deepens water quality concerns. Bioretention is a type of green infrastructure practice developed to mitigate these impacts by reducing peak flows, runoff volume, and nutrient loads in stormwater. However, studies have shown inconsistency in the ability of bioretention to manage some pollutants, particularly some forms of nitrogen. Innovative sensor and control technologies are being tested to actively manage urban stormwater, primarily in open water stormwater systems such as wet ponds. Through these cyber-physical controls, it may be possible to optimize storage time and/or soil moisture dynamics within bioretention cells to create more favorable conditions for water quality improvements. A column study testing the influence of active control on bioretention system performance was conducted over a 9-week period. Active control columns were regulated based on either maintaining a specific water level or soil moisture content and were compared to free draining (FD) and internal water storage standards. Actively controlled bioretention columns performed similarly, with the soil moisture-based control showing the best performance with over 86% removal of metals and total suspended solids (TSS) while also exhibiting the highest ammonium removal (43%) and second highest nitrate removal (74%). While all column types showed mostly similar TSS and metal removal trends (median 94 and 98%, respectively), traditionally FD and internal water storage configurations promoted aerobic and anaerobic processes, respectively, which suggests that actively controlled systems have greater potential for targeting both processes. The results suggest that active controls can improve upon standard bioretention designs, but further optimization is required to balance the water quality benefits gained by retention time against storage needs for impending storms.

This paper is concerned with the modeling framework based on power and control for a mechanical system that has nonlinear, unstable, and under-actuated characteristic features, based on an analogy, which is developed by using the Brayton and Moser’s (BM) equations between mechanical and electrical systems. The analogy is based on a mixed-potential function generalized for BM. The mixed-potential function for a cart - pole double inverted pendulum (CPDIP) system is used as a new building block for modeling, analysis, and controller design. The analogy allows for the exact transfer of results from electrical circuit synthesis and analysis to the mechanical domain. This paper focuses mainly on the development of the electrical equivalent circuit of CPDIP inspired by the power-based modeling framework. In this brief, a real time CPDIP experimental setup was modeled by using this framework and a linear quadratic regulator (LQR) controller was designed for the stabilization of the system. Experimental results validated that this framework can be used as a new and advantageous modeling method and is a convenient and practical alternative to the Lagrangian framework. [ABSTRACT FROM AUTHOR]

A concept for reducing stormwater peak run-off from existing small urban catchments is developed. Stormwater inflow from the ground to the pipeline is managed by smart gullies. The gullies are real-time controlled and therefore capable of predicting the weather conditions. Drainage facilities are usually unable to cope with excessive flows that exceed their design limits. This results in pluvial floods and activation of combined sewer overflows, both of which have negative consequences. Northern Europe is expecting to receive more intense rainstorms in the future; therefore, innovative solutions are needed for flow management. The inlet control presented in our work is financially feasible and efficient to be applied to small catchments with substantial permeable surfaces to reduce the peak run-off. The control system is autonomous; therefore, it is suitable for sites scattered around the urban catchment. The concept was successfully tested in a 12 ha catchment area in Tallinn, Estonia. [ABSTRACT FROM AUTHOR]

In the present work, a novel cloud-based remote and real time monitoring and control scheme has been developed for a manufacturing process named friction stir welding (FSW) to avoid occurrence of weld defects. This model acquires data from multiple sensors associated with the FSW machine and transmits them to the cloud. The signals are analyzed and processed in the cloud in real time through various signal processing and machine learning techniques. The model provides a feedback to the machine regarding the desired controlled parameters to achieve an improved weld quality. This is an example of Industry 4.0 where a manufacturing process can be controlled in real time from any location. [ABSTRACT FROM AUTHOR]

Image noise has a serious impact on image transmission, image data collection and image processing. Image noise is mainly denoised by additive noise and multiplicative noise. Firstly, based on the analysis that random noise has a direct impact on image recognition accuracy and registration performance, aiming at capturing and controlling the interaction between reinforcement learning agents and noise environment, an image recognition model based on noise stimulation is proposed, which will help capture and analyze random noise. Then, in order to construct a complete image data set and its linear combination of transfer process, a denoising algorithm based on reinforcement learning is proposed, which uses the sparse vector based on noise obtained by reinforcement learning to represent a given noise signal. Finally, based on image denoising based on reinforcement learning, an image registration optimization mechanism is proposed by maximizing the similarity measure between two images or minimizing the distance measure to find the coordinate correspondence between images. The simulation results show that the proposed algorithm is credible, effective and efficient in terms of consistency of noise analysis, accuracy of correspondence between feature points, registration error and computational utility of the algorithm. [ABSTRACT FROM AUTHOR]

In this paper we consider a problem of controlling an oversaturated intersection in real time. We developed a mathematical model for solving the problem, based on fuzzy logic. The model can be applied to intersections characterized by oversaturated traffic flows. We compared this fuzzy logic approach to the 'fixed time' controlling of the oversaturated intersection. By 'fixed time' we understood controlling based on the hystorical data about traffic flows. In the case of the oversaturated intersection considered in this paper, a classical approach of controlling in real time ('actuated time control') gives the same solutions as 'fixed time' control. The criterion function for comparing solutions represents the control delay of all vehicles that pass through the intersection within a certain period of analysis. We tested these approaches on a 'T' intersection, where the suggested model based on fuzzy logic generated solutions with less control delay in comparison to the 'fixed time' model. / В данной работе рассматривается проблема управления светофором на изолированном перекрестке в реальном времени. В статье представлена разработанная на основании фаззи-логики математическая модель, которую можно использовать в подобных ситуациях. Данная модель специально разработана для регулирования перекрестка с загруженным транспортным потоком. Разработанный метод сравнивается с управлением загруженным перекрестком методом «фиксированного времени». Метод «фиксированного времени» подразумевает управление на основании базы данных о транспортном потоке. В случаях загруженности перекрестка, о которых идет речь в данной статье, применяется метод «реального времени», который по результатам не уступает методу «фиксированного времени» управления. Функция сравнительных критериев представляет суммарную потерю времени всех транспортных средств, проезжающих перекресток в течение проведения анализа. Методы были испытаны на перекрестке «Т», результаты тестирования показали, что модель, основанная на фаззи-логике дала решения с меньшими значениями критериев функций в анализируемом промежутке времени, по сравнению с прочими методами. / U radu je razmatran problem upravljanja izolovanom semaforisanom raskrsnicom u realnom vremenu. Razvijen je matematički model za rešavanje predmetnog problema koji je baziran na fazi logici. Model se odnosi samo na raskrsnicu koju karakterišu prezasićeni saobraćajni tokovi. Pristup rešavanju predmetnog problema poređen je sa 'fihed time' upravljanjem prezasićenom raskrsnicom. 'Fihed time' podrazumeva upravljanje na osnovu podataka o saobraćajnim tokovima. U slučaju prezasićene raskrsnice klasničan pristup upravljanja u realnom vremenu ('actuated time control') daje ista rešenja kao i 'fixed time' upravljanje. Kriterijumska funkcija za poređenje rešenja predstavlja ukupne vremenske gubitke svih vozila koja prođu raskrsnicom u određenom periodu analize. Pristupi su testirani na 'T' raskrsnici, gde je model zasnovan na fazi logici generisao rešenja sa manjom vrednošću kriterijumske funkcije u odnosu na ostale pristupe, u određenom periodu analize.

This paper presents a review of the current state of the art of real time control (RTC) of water distribution networks (WDNs). After proving the basic concept and terms of RTC and presenting sensors, regulation devices and controllers typically used in WDNs, the paper goes on by describing the most frequent control objectives, which mainly include service pressure regulation, control of tank filling and energy production in each WDN district. Various control methodologies recently proposed in the scientific literature are presented and discussed, along with experimental and numerical results achieved. Also, aspects related to the cost-effectiveness of RTC are critically analyzed. The paper ends by giving an outlook into potential future developments in the area of RTC for WDNs. Image 1 • Real Time Control (RTC) in Water Distribution Networks (WDNs) has been reviewed. • The fundamental concepts of RTC and the devices used in WDNs are presented. • RTC of service pressure, tank level and electric energy production is described. • The successful application of service pressure RTC to a real WDN is reported. • Need of new experimental works to corroborate numerical findings obtained so far. [ABSTRACT FROM AUTHOR]

• Real-time tracking of NTMs position using ECE in the quasi-in-line configuration. • Experimental proof of principle of NTMs detection and tracking. • A closed loop control scheme for NTM instabilities control with ECCD. An important goal of the control system in a tokamak is the suppression of magneto-hydrodynamic (MHD) instabilities with low m, n (poloidal and toroidal mode numbers), which can influence the confinement time of energy and particles and possibly lead to plasma disruption. These instabilities, which appear as rotating magnetic islands, can be reduced or completely suppressed by a current driven by electron cyclotron waves (ECW) accurately located within the island. A fundamental requisite for this control technique is the ability to identify the island parameters (amplitude and radial position) and to vary accordingly the ECW deposition location. Here we describe a control scheme of the steering mirror of the ECW source based on the real-time tracking of the island radial position realized using only the electron cyclotron emission (ECE) diagnostics in quasi-in-line configuration, i.e. with toroidal anti-parallel propagation of the ECW and ECE beams. The successful experimental proof of principle of this scheme, tested on the TCV tokamak, is here reported. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Polytechnic is the property of Journal of Polytechnic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents a new methodology for optimizing the operation of pumps supplying water from a low source to an elevated tank in water distribution systems (WDSs). It is based on the use of the on/off trigger level technique for each pump present in the pumping station. The novelty of the methodology consists of the addition of time slots for the optimization of the trigger levels. These slots are created at the end of each energy tariff period, to drive the tank level to the highest and lowest points at the beginning and at the end of the peak, respectively. As a result, pumps are led to work more and less during low and high tariff periods, respectively, yielding reductions in energy costs. In the applications, the methodology was introduced within a multi-objective optimization framework, searching for solutions in the trade-off between daily average energy cost and daily average number of pump switches, representative of the stressing conditions for the system. The methodology was applied to case studies with single and multiple pumps, using realistic demand patterns, and was compared with other trigger levels-based methodologies in the scientific literature. The results proved its benefits, in yielding solutions with reduced number of pump switches for prefixed values of energy cost. This is more evident when the operation of three pumps must be optimized. In an explicative example with three operating pumps, for an energy cost around 6000 €/day, the newly proposed methodology leads to a number of pump switches between 17% and 33% lower than the results obtained with the methods considered for comparison. [ABSTRACT FROM AUTHOR]

• Developed BioRTC as the first model for real time control (RTC) of biofilters. • High parameter transferability allows BioRTC capable of evaluating RTC strategies. • Explored RTC with scenario testing on a field-scale biofilter system using BioRTC. • The presence of Pareto fronts reveals the necessity of muti-objective optimisation. • RTC allows for the adaptation to climate change and changing demands for harvesting. Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a 'base' model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (E c) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively. [Display omitted] [ABSTRACT FROM AUTHOR]

The fuzzy controller is one of the intelligent soft computing methods that realize a human being hierarchy sense and expert by building the program that realized it . In this work real time implementation of a fuzzy controller is realized by programming the industrial computer in c++ language. The performed fuzzy controller has two inputs and one output. The inputs are the speed error and change in error with controller output as PWM. The applied program architecture uses the matrix representation and subroutines for data entering the linguistic memberships for both error and change in error and performing rule-base in the inference mechanism using fuzzy logic . The output of the defuzification is pulse width modulation to the chopper drive circuit. The result shows good a fulfillment of the soft computing of the controller and with fast response and the effect of load as a disturbance on the shaft of the motor has been rejected quickly.