Pollution based real time control strategies for combined sewer systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 331-336 ◽  
Author(s):  
Gabriela Weinreich ◽  
Wolfgang Schilling ◽  
Ane Birkely ◽  
Tallak Moland
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Ammonia Nitrogen ◽  
Simple Extension ◽  
Real Time Control ◽  
Time Control ◽  
Sewer Systems ◽  
Receiving Waters ◽  
Tunnel System

This paper presents results from an application of a newly developed simulation tool for pollution based real time control (PBRTC) of urban drainage systems. The Oslo interceptor tunnel is used as a case study. The paper focuses on the reduction of total phosphorus Ptot and ammonia-nitrogen NH4-N overflow loads into the receiving waters by means of optimized operation of the tunnel system. With PBRTC the total reduction of the Ptot load is 48% and of the NH4-N load 51%. Compared to the volume based RTC scenario the reductions are 11% and 15%, respectively. These further reductions could be achieved with a relatively simple extension of the operation strategy.

scholarly journals An MPC-Enabled SWMM Implementation of the Astlingen RTC Benchmarking Network

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1034 ◽  
Author(s):  
Congcong Sun ◽  
Jan Lorenz Svensen ◽  
Morten Borup ◽  
Vicenç Puig ◽  
Gabriela Cembrano ◽  
...  
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Real Time Control ◽  
Time Control ◽  
Advanced Control ◽  
Water Association ◽  
Benchmark System ◽  
Receiving Waters ◽  
Global Strategies ◽  
Swmm Model

The advanced control of urban drainage systems (UDS) has great potential in reducing pollution to the receiving waters by optimizing the operations of UDS infrastructural elements. Existing controls vary in complexity, including local and global strategies, Real-Time Control (RTC) and Model Predictive Control (MPC). Their results are, however, site-specific, hindering a direct comparison of their performance. Therefore, the working group ‘Integral Real-Time Control’ of the German Water Association (DWA) developed the Astlingen benchmark network, which has been implemented in conceptual hydrological models and applied to compare RTC strategies. However, the level of detail of such implementations is insufficient for testing more complex MPC strategies. In order to provide a benchmark for MPC, this paper presents: (1) The implementation of the conceptual Astlingen system in an open-source hydrodynamic model (EPA-SWMM), and (2) the application of an MPC strategy to the developed SWMM model. The MPC strategy was tested against traditional and well-established local and global RTC approaches, demonstrating how the proposed benchmark system can be used to test and compare complex control strategies.

Case Study: Real Time Control Strategies for CSO Control

2010 ◽  
Vol 2010 (6) ◽  
pp. 83-109
Author(s):  
Srini Vallabhaneni ◽  
Daphne Chiu ◽  
Eddie Speer ◽  
Bob Masbaum
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Real Time Control ◽  
Time Control

General assessment of potential CSO reduction by means of real time control

1995 ◽  
Vol 32 (1) ◽  
pp. 249-257 ◽  
Author(s):  
Michael Jørgensen ◽  
Wolfgang Schilling ◽  
Poul Harremoës
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Control Strategies ◽  
Systematic Investigation ◽  
Optimum Control ◽  
Real Time Control ◽  
General Applicability ◽  
Time Control ◽  
Sewer Systems ◽  
Combined Sewer

A number of case studies have been carried out in which the potential reduction of combined sewer overflows (CSO) by means of real time control (RTC) is assessed for existing sewer systems. It is an inherent problem of case studies that results cannot necessarily be generalized. In this paper results of a systematic investigation of hypothetical combined sewer systems are presented. The systems were characterized in terms of their topological structure, size, type and arrangement of storage and transport elements. The RTC optimization model LOCUS was applied to simulate the performance of local control and of optimum control strategies. The results are expressed as “CSO reduction achieved by optimum control, compared to the locally controlled system”. General conclusions are drawn with respect to possible CSO reduction for a system with given topology, storage and transport characteristics. Finally, these are compared to some case studies reported in the literature in order to verify and show the general applicability of the findings.

Integrative Modeling Platform for Design and Control of an Adaptive Wind Turbine Blade

2018 ◽  
Author(s):  
Hamid Khakpour Nejadkhaki ◽  
John F. Hall ◽  
Minghui Zheng ◽  
Teng Wu
Keyword(s):  
Simulation Model ◽  
Wind Turbine ◽  
Real Time ◽  
Turbine Blade ◽  
Design Tool ◽  
Real Time Control ◽  
Time Control ◽  
Partial Load ◽  
And Control

A platform for the engineering design, performance, and control of an adaptive wind turbine blade is presented. This environment includes a simulation model, integrative design tool, and control framework. The authors are currently developing a novel blade with an adaptive twist angle distribution (TAD). The TAD influences the aerodynamic loads and thus, system dynamics. The modeling platform facilitates the use of an integrative design tool that establishes the TAD in relation to wind speed. The outcome of this design enables the transformation of the TAD during operation. Still, a robust control method is required to realize the benefits of the adaptive TAD. Moreover, simulation of the TAD is computationally expensive. It also requires a unique approach for both partial and full-load operation. A framework is currently being developed to relate the TAD to the wind turbine and its components. Understanding the relationship between the TAD and the dynamic system is crucial in the establishment of real-time control. This capability is necessary to improve wind capture and reduce system loads. In the current state of development, the platform is capable of maximizing wind capture during partial-load operation. However, the control tasks related to Region 3 and load mitigation are more complex. Our framework will require high-fidelity modeling and reduced-order models that support real-time control. The paper outlines the components of this framework that is being developed. The proposed platform will facilitate expansion and the use of these required modeling techniques. A case study of a 20 kW system is presented based upon the partial-load operation. The study demonstrates how the platform is used to design and control the blade. A low-dimensional aerodynamic model characterizes the blade performance. This interacts with the simulation model to predict the power production. The design tool establishes actuator locations and stiffness properties required for the blade shape to achieve a range of TAD configurations. A supervisory control model is implemented and used to demonstrate how the simulation model blade performs in the case study.

Dynamic modeling, system identification and comparative study of various control strategies for a spatial parallel manipulator

2021 ◽  
pp. 095965182110320
Author(s):  
Mervin Joe Thomas ◽  
Shoby George ◽  
Deepak Sreedharan ◽  
ML Joy ◽  
AP Sudheer
Keyword(s):  
Real Time ◽  
Parallel Manipulator ◽  
Control Strategies ◽  
Proportional Integral Derivative ◽  
Real Time Control ◽  
Model Predictive Controller ◽  
End Effector ◽  
Proportional Integral ◽  
Time Control ◽  
Predictive Controller

The significant challenges seen with the mathematical modeling and control of spatial parallel manipulators are its difficulty in the kinematic formulation and the inability to real-time control. The analytical approaches for the determination of the kinematic solutions are computationally expensive. This is due to the passive joints, solvability issues with non-linear equations, and inherent kinematic constraints within the manipulator architecture. Therefore, this article concentrates on an artificial neural network–based system identification approach to resolve the complexities of mathematical formulations. Moreover, the low computation time with neural networks adds up to its advantage of real-time control. Besides, this article compares the performance of a constant gain proportional–integral–derivative (PID), variable gain proportional–integral–derivative, model predictive controller, and a cascade controller with combined variable proportional–integral–derivative and model predictive controller for real-time tracking of the end-effector. The control strategies are simulated on the Simulink model of a 6-degree-of-freedom 3-PPSS (P—prismatic; S—spherical) parallel manipulator. The simulation and real-time experiments performed on the fabricated manipulator prototype indicate that the proposed cascade controller with position and velocity compensation is an appropriate method for accurate tracking along the desired path. Also, training the network using the experimentally generated data set incorporates the mechanical joint approximations and link deformities present in the fabricated model into the predicted results. In addition, this article showcases the application of Euler–Lagrangian formalism on the 3-PPSS parallel manipulator for its dynamic model incorporating the system constraints. The Lagrangian multipliers include the influence of the constraint forces acting on the manipulator platform. For completeness, the analytical model results have been verified using ADAMS for a pre-defined end-effector trajectory.

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