Applying real-time control to enhance the performance of nitrogen removal in CAST system

A bench-scale reactor（72 L） red with domestic sewage, was operated more than 3 months with three operation modes： traditional mode, modified mode and real-time control mode, so as to evaluate effects of the operation mode on the system performance and to develop a feasible control strategy. Results obtained from fixed-time control study indicate that the variations of the pH and oxidation-reduction potential（ORP） profiles can represent dynamic characteristics of system and the cycle sequences can be controlled and optimized by the control points on the pH and ORP profiles. A control strategy was, therefore, developed and applied to real-time control mode. Compared with traditional mode, the total nitrogen（TN） removal can be increased by approximately 16% in modified mode and a mean TN removal of 92% was achieved in real-time control mode. Moreover, approximately 12.5% aeration energy was saved in real- time control mode. The result of this study shows that the performance of nitrogen removal was enhanced in modified operation mode. Moreover, the real-time control made it possible to optimize process operation and save aeration energy.

Intercross real-time control strategy in alternating activated sludge process for short-cut biological nitrogen removal treating domestic wastewater

To develop technically feasible and economically favorable dynamic process control(DPC)strategies for an alternating activated sludge(AAS)system,a bench-scale continuous-flow alternating aerobic and anoxic reactor,performing short-cut nitrogen removal from real domestic wastewater was operated under different control strategies for more than five months.A fixed-time control(FTC) study showed that bending-points on pH and oxidation-reduction potential(ORP)profiles accurately coincided with the major biologic...

Construction Simulation and Real-Time Control for High Arch Dam

A method of combining dynamic simulation with real-time control was proposed to fit the randomness and uncertainty in the high arch dam construction process. The mathematical logic model of high arch dam construction process was established. By combining dynamic construction simulation with schedule analysis, the process of construction schedule forecasting and analysis based on dynamic simulation was studied. The process of real-time schedule control was constructed and some measures for dynamic adjustment and control of construction schedule were provided. A system developed with the method is utilized in a being constructed hydroelectric project located at the Yellow River in northwest China, which can make the pouring plan of the dam in the next stage (a month, quarter or year) to guide the practical construction. The application result shows that the system provides an effective technical support for the construction and management of the dam.

Real-time Control Oriented HCCI Engine Cycle-to-cycle Dynamic Modelling

For homogeneous charge compression ignition （HCCI） combustion, the auto-ignition process is very sensitive to in-cylinder conditions, including in-cylinder temperature, in-cylinder components and concentrations. Therefore, accurate control is required for reliable and efficient HCCI combustion. This paper outlines a simplified gasoline-fueled HCCI engine model implemented in Simulink environment. The model is able to run in real-time and with fixed simulation steps with the aim of cycle-to-cycle control and hardware- in-the-loop simulation. With the aim of controlling the desired amount of the trapped exhaust gas recirculation （EGR） from the previous cycle, the phase of the intake and exhaust valves and the respective profiles are designed to vary in this model. The model is able to anticipate the auto-ignition timing and the in-cylinder pressure and temperature. The validation has been conducted using a comparison of the experimental results on Ricardo Hydro engine published in a research by Tianjin University and a JAGUAR V6 HCCI test engine at the University of Birmingham. The comparison shows the typical HCCI combustion and a fair agreement between the simulation and experimental results.

Experimental Study on Real-Time Control System Testing

An experimental study on the testing of process control for a real-time control system is presented. Several indexes, such as the capability of system approximation output, the ramp rates, the smoothness and stability of output, and control of temperature overshoot, are selected as performance parameters. With these indexes, the thermal performance of thermal cyelers is validated, analyzed, and monitored. A testing prototype is designed and fabricated as a supplementary instrument for the experimental study. A tracking temperature algorithm with feedforward and feedback controls are also introduced to improve the efficiency of system performance testing.

A Model Predictive Scheduling Algorithm inReal-Time Control Systems

Abstract-The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.

Alternating shortcut nitrification-denitrification for nitrogen removal from soybean wastewater by SBR with real-time control

A novel treating technology for nitrogen removal from soybean wastewater was studied. The process for nitrogen removal was achieved by alternating aeration and mixing, combined with real\|time control strategies. Results showed that the COD and total nitrogen removal rates are more than 90% and 92% at COD and total nitrogen loads of 1\^0-1\^2 kg COD/(kgMLSS·d) and 0\^20-0\^27 kg TN/(kgMLSS·d), respectively. In addition, it could improve sludge settling property. SVI value is less than 70 g/ml during the whole cycles. The method not only may be adapted to treat soybean wastewater with high nitrogen, but also may be applied to treat other high nitrogen wastewater.

Development of a Simulation-Based Intelligent Decision Support System for the Adaptive Real-Time Control of Flexible Manufacturing Systems

This paper describes a simulation-based intelligent decision support system (IDSS) for real time control of a flexible manufacturing system (FMS) with machine and tool flexibility. The manufacturing processes involved in FMS are complicated since each operation may be done by several machining centers. The system design approach is built around the theory of dynamic supervisory control based on a rule-based expert system. The paper considers flexibility in operation assignment and scheduling of multi-purpose machining centers which have different tools with their own efficiency. The architecture of the proposed controller consists of a simulator module coordinated with an IDSS via a real time event handler for implementing inter-process synchronization. The controller’s performance is validated by benchmark test problem.

Effect of Sludge Retention Time on Nitrite Accumulation in Real-time Control Biological Nitrogen Removal Sequencing Batch Reactor

In this study,four sequencing batch reactors(SBR),with the sludge retention time(SRT)of 5,10,20 and 40 d,were used to treat domestic wastewater,and the effect of SRT on nitrite accumulation in the biological nitrogen removal SBR was investigated.The real-time control strategy based on online parameters,such as pH,dissolved oxygen(DO)and oxidation reduction potential(ORP),was used to regulate the nitrite accumulation in SBR. The model-based simulation and experimental results showed that with the increase of SRT,longer time was needed to achieve high level of nitritation.In addition,the nitrite accumulation rate(NAR)was higher when the SRT was relatively shorter during a 112-day operation.When the SRT was 5 d,the system was unstable with the mixed liquor suspended solids(MLSS)decreased day after day.When the SRT was 40 d,the nitrification process was significantly inhibited.SRT of 10 to 20 d was more suitable in this study.The real-time control strategy combined with SRT control in SBR is an effective method for biological nitrogen removal via nitrite from wastewater.

Real-time controller hardware-in-the-loop co-simulation testbed for cooperative control strategy for cyber-physical power system

Various distributed cooperative control schemes have been widely utilized for cyber-physical power system(CPPS),which only require local communications among geographic neighbors to fulfill certain goals.However,the process of evaluating the performance of an algorithm for a CPPS can be affected by the physical target characteristics and real communication conditions.To address this potential problem,a testbed with controller hardware-in-the-loop(CHIL)is proposed in this paper.On the basis of a power grid simulation conducted using the real-time simulator RT-LAB developed by the company OPAL-RT,along with a communication network simulation developed with OPNET,multiple distributed controllers were developed with hardware devices to directly collect the real-time operating data of the power system model in RT-LAB and provide local control.Furthermore,the communication between neighboring controllers was realized using the cyber system modelin OPNET with an Ethernet interface.The hardware controllers produced a real-world control behavior instead of a digital simulation,and precisely simulated the dynamic features of a CPPS with high speed.A classic cooperative control case for active power output was studied to explain the integrated simulation process and validate the effectiveness of the co-simulation testbed.

Real-time control of aerobic/anoxic digestion for waste activated sludge

Experiments were conducted to study the performance characters of aerobic/anoxic （A/ A） digestion of sludge at 30± 1 ℃, while the sludge retention time （SRT） was kept 16 d. The varia tions of oxidation reduction potential （Eh ） and pH were continuously monitored during the A/A di gestion and the conversions of ammonium and nitrate were investigated. Important features on both Eh and pH profiles were identified to develop process control strategy. Since the feature point on Eh profile where d2 Eh/dt^2 =0 is very stable during anoxic cycle, it can be used to determine the end of denitrification. The end of nitrification can be identified according to dpH/dt = 0. A real-time control strategy of A/A digestion of sludge was developed and tested with pH and Eh as control parameters. It is shown that the performance of the real-time control strategy is better than that of a fixed time control strategy. While the real time controlled A/A digestion system can achieve a similar volatile suspended solids （VSS） destruction efficiency of 35.2 % as a continuously aerated system, it im proves the supernatant quality in a shorter aeration time（7. 75 d for a 20 d period）.

Computation Method for the Real-Time Control Problems in Differential-Algebraic Systems

In this paper, a real-time computation method for the control problems in differential-algebraic systems is presented. The errors of the method are estimated, and the relation between the sampling stepsize and the controlled errors is analyzed. The stability analysis is done for a model problem, and the stability region is ploted which gives the range of the sampling stepsizes with which the stability of control process is guaranteed.

Real-Time Control System Adopted to Energy Storage for Smart Grid Low Wind Applications:A Part of Distributed Renewables in Smart City

In this paper,extensive efforts have been undertaken to design and develop a control system,which is incorporated with an energy storage device that can store energy from low-voltage renewable sources.The developed device acts as a storage element,which can be used to charge small-scale batteries,cellular devices,and other applications in remote places where the grid connection is not available.The circuit is developed using a case-by-case analysis.In order to solve the low output voltage problem,a bipolar junction transistor-metal oxide semiconductor field-effect transistor(BJT-MOSFET)based switch control technology with the Arduino microcontroller has been implemented.The developed control system is extremely efficient in charging batteries through a supercapacitor for low-voltage sources.In this research,a small-scale 200-W portable vertical axis wind turbine is used at a wind speed of 3 m/s.The result shows the efficiency of the proposed system as compared with the conventional systems.The proposed system can be an important tool of the latest distributed energy generation technology which is an important part of a smart city.Lastly,the limitations and future scopes of the development of the control device are discussed for the future barrier.An important future scope identified is to integrate the Internet of Things based mobile interface for remote monitoring for any kind of pandemic situation like COVID-19.Now,it is high time to get our smart city concept aligned with the post COVID pandemic situation and get us prepared smartly for similar future occurrences.

RESEARCH ON A REAL-TIME CONTROL SYSTEM OF LOW POWER DISSIPATION FOR CONTINUOUS CYCLIC PERITONEAL DIALYSIS(CCPD) CYCLER

A low power dissipation control system for continuous cyclic peritoneal dialysis (CCPD) cycler and its characteristics are reported. Combined withhemodialysis and renal transplantation, peritoneal dialysis is used mainly for thetreatment of renal failure. CCPD has been developed during 1980＇s. It provided automatic dialysis procedures during the night to avoid interruptions in patients＇dailyroutine. Furthermore,there is a remarkable decrease in peritonitis occurance usingCCPD. The control system is a critical part for CCPD cycler. The system is approvedto be reliable and flexible in practical experiments. When AC power failure,the system can still ensure the completion of dialysis.

Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system.First,we employ a strategy that restricts long-and short-term power output deviations to smoothen wind power fluctuations in real time.Second,we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise(SW-ICEEMDAN)strategy to achieve real-time decomposition of the energy storage power,facilitating internal power distribution within the hybrid energy storage system.Finally,we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components.Through simulation validation,we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power.Compared with traditional empirical mode decomposition(EMD),ensemble empirical mode decomposition(EEMD),and complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)decomposition strategies,the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal.Additionally,the state-of-charge of energy storage components fluctuates within a reasonable range,enhancing the stability of the power system and ensuring the secure operation of the energy storage system.

Exploration of instantaneous frequency for local control assessment in real-time hybrid simulation

Local control parameters such as instantaneous delay and instantaneous amplitude play an essential role in evaluating the performance and maintaining the stability of real-time hybrid simulation(RTHS).However,existing methods have limitations in obtaining this local assessment in either the time domain or frequency domain.In this study,the instantaneous frequency is introduced to determine local control parameters for actuator tracking assessment in a real-time hybrid simulation.Instantaneous properties,including amplitude,delay,frequency and phase,are then calculated based on analytic signals translated from actuator tracking signals through the Hilbert transform.Potential issues are discussed and solutions are proposed for calculation of local control parameters.Numerical simulations are first conducted for sinusoidal and chirp signals with time varying amplitude error and delay to demonstrate the potential of the proposed method.Laboratory tests also are conducted for a predefined random signal as well as the RTHS of a single degree of freedom structure with a self-centering viscous damper to experimentally verify the effectiveness of the proposed use of the instantaneous frequency.Results from the ensuing analysis clearly demonstrate that the instantaneous frequency provides great potential for local control assessment,and the proposed method enables local tracking parameters with good accuracy.

Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks

Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

Real-time model correction using Kalman filter for Raman-controlled cell culture processes

Raman spectroscopy has found extensive use in monitoring and controlling cell culture processes.In this context,the prediction accuracy of Raman-based models is of paramount importance.However,models established with data from manually fed-batch cultures often exhibit poor performance in Raman-controlled cultures.Thus,there is a need for effective methods to rectify these models.The objective of this paper is to investigate the efficacy of Kalman filter(KF)algorithm in correcting Raman-based models during cell culture.Initially,partial least squares(PLS)models for different components were constructed using data from manually fed-batch cultures,and the predictive performance of these models was compared.Subsequently,various correction methods including the PLS-KF-KF method proposed in this study were employed to refine the PLS models.Finally,a case study involving the auto-control of glucose concentration demonstrated the application of optimal model correction method.The results indicated that the original PLS models exhibited differential performance between manually fed-batch cultures and Raman-controlled cultures.For glucose,the root mean square error of prediction(RMSEP)of manually fed-batch culture and Raman-controlled culture was 0.23 and 0.40 g·L^(-1).With the implementation of model correction methods,there was a significant improvement in model performance within Raman-controlled cultures.The RMSEP for glucose from updating-PLS,KF-PLS,and PLS-KF-KF was 0.38,0.36 and 0.17 g·L^(-1),respectively.Notably,the proposed PLS-KF-KF model correction method was found to be more effective and stable,playing a vital role in the automated nutrient feeding of cell cultures.

Feasibility Assessment of Fast Numerical Simulations for Real-Time Monitoring and Control of PEM Fuel Cells

Computational models that ensure accurate and fast responses to the variations in operating conditions,such as the cell tem-perature and relative humidity(RH),are essential monitoring tools for the real-time control of proton exchange membrane(PEM)fuel cells.To this end,fast cell-area-averaged numerical simulations are developed and verifi ed against the present experiments under various RH levels.The present simulations and measurements are found to agree well based on the cell voltage(polarization curve)and power density under variable RH conditions(RH=40%,RH=70%,and RH=100%),which verifi es the model accuracy in predicting PEM fuel cell performance.In addition,computationally feasible reduced-order models are found to deliver a fast output dataset to evaluate the charge/heat/mass transfer phenomena as well as water production and two-phase fl ow transport.Such fast and accurate evaluations of the overall fuel cell operation can be used to inform the real-time control systems that allow for the improved optimization of PEM fuel cell performance.