Strategies to enhance the biodegradation of toxic compounds using discontinuous processes

2001 ◽  
Vol 43 (3) ◽  
pp. 283-290 ◽  
Author(s):  
G. Buitrón ◽  
G. Soto ◽  
G. Vite ◽  
J. Moreno
Keyword(s):  
Optimal Control ◽  
Activated Carbon ◽  
Dissolved Oxygen ◽  
Batch Reactor ◽  
Biological Degradation ◽  
Optimal Control Strategy ◽  
Measured Variable ◽  
Time Optimal ◽  
High Concentrations ◽  
And Control

This study presents two strategies used to enhance the biological degradation of phenolic wastewaters. In the first one the operation of a sequencing batch biofilter added with granular activated carbon (SBB-AC) was studied. The second strategy presents the results of the automation of a sequencing batch reactor in order to optimize the reaction phase. In this case, the dissolved oxygen was employed to monitor and control the reactor. The results of the SBB-AC system, based on the configuration of the reactor, type and size of activated carbon and size of the packing material, are discussed. The system biodegraded efficiently (total phenol removals as high as 97%) high concentrations (600 mg/l) of a mixture of phenol, 4-chlorophenol, 2,4-dichlorophenol and 2,4,6-trichlorophenol. Maximal eliminated loads of 4.33 kg COD/m3-d were achieved. For the second strategy, the applicability of an optimal control for a SBR using the dissolved oxygen as the measured variable was demonstrated. When the reactor was operated under the time-optimal control strategy, the degradation time of 4-chlorophenol was reduced. A very satisfactory operation of the reactor was observed, since the removal efficiencies were around 99%.

Observer-based time-optimal control of an aerobic SBR for chemical and petrochemical wastewater treatment

2000 ◽  
Vol 42 (5-6) ◽  
pp. 163-170 ◽  
Author(s):  
A. Vargas ◽  
G. Soto ◽  
J. Moreno ◽  
G. Buitrón
Keyword(s):  
Optimal Control ◽  
Reaction Time ◽  
Control Strategy ◽  
Optimal Operation ◽  
Time Optimal Control ◽  
Nonlinear Observer ◽  
Synthetic Wastewater ◽  
Optimal Control Strategy ◽  
Time Optimal ◽  
High Concentrations

The present study implements a time-optimal control strategy for a discontinuous aerobic bioreactor, used to treat highly concentrated toxic wastewater present in some effluents of the chemical and petrochemical industries, using respirometric techniques. The control strategy regulates the feed rate to maintain a constant optimal substrate concentration in the reactor, which in turn minimizes the reaction time. Since this control requires on-line knowledge of unmeasurable variables, an Extended Kalman Filter is used as a nonlinear observer. The experimental setup was a 7 litre laboratory bioreactor used to treat synthetic wastewater with high concentrations of 4-chlorophenol. The controller consisted of a personal computer with data acquisition hardware and real-time software tools, peristaltic pumps and an electronic oxygen meter. Three experiments were performed: one to obtain parameters and calibrate the observer, another one to validate the time-optimal strategy and a final one to evaluate theperformance of a fully automated time-optimal operation. When well calibrated, the observer provided good enough estimates and the controller worked as expected, reducing reaction time and increasing the overall efficiency of the bioreactor, when compared with the usual SBR-type operation.

scholarly journals Optimal Control of an SIR Model with Delay in State and Control Variables

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Mohamed Elhia ◽  
Mostafa Rachik ◽  
Elhabib Benlahmar
Keyword(s):  
Optimal Control ◽  
Influenza A ◽  
Optimization Strategy ◽  
Sir Epidemic Model ◽  
Optimal Control Strategy ◽  
Control Variables ◽  
Sir Epidemic ◽  
Influenza A H1n1 ◽  
Using Data ◽  
And Control

We will investigate the optimal control strategy of an SIR epidemic model with time delay in state and control variables. We use a vaccination program to minimize the number of susceptible and infected individuals and to maximize the number of recovered individuals. Existence for the optimal control is established; Pontryagin’s maximum principle is used to characterize this optimal control, and the optimality system is solved by a discretization method based on the forward and backward difference approximations. The numerical simulation is carried out using data regarding the course of influenza A (H1N1) in Morocco. The obtained results confirm the performance of the optimization strategy.

Real-Time Optimal Power Management for Hybrid Electric Vehicle Based on Prediction of Trip Information

2013 ◽  
Vol 321-324 ◽  
pp. 1539-1547 ◽  
Author(s):  
Li Cun Fang ◽  
Gang Xu ◽  
Tian Li Li ◽  
Ke Min Zhu
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Power Management ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Driving Cycle ◽  
Moving Window ◽  
Optimal Control Strategy ◽  
Time Optimal

Power management of hybrid electric vehicle (HEV) is an important operational factor for HEV to enhance fuel economy and reduce emissions. Optimal control for HEV requires the knowledge of entire driving cycle and elevation profile to obtain the optimal control strategy over fixed driving cycle. In this paper, the traffic knowledge extracted from intelligent transportation systems (ITSs),global positioning systems (GPSs) and geographical information systems (GISs) is used for predicting the knowledge of the future driving cycle, and the real-time optimal control strategy based on dynamic programming in a moving window is investigated in order to minimize fuel consumption. A simulation study was conducted for two driving cycles, and the results showed significant improvement in fuel economy compared with a rule-based control. Furthermore, the results showed that the distance of the moving window has obvious effect on the fuel economy.

Optimal vaccination policy and cost analysis for epidemic control in resource-limited settings

Kybernetes ◽  
2015 ◽  
Vol 44 (3) ◽  
pp. 475-486 ◽  
Author(s):  
Kuan Yang ◽  
Ermei Wang ◽  
Yinggao Zhou ◽  
Kai Zhou
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Mass Action ◽  
Sir Epidemic Model ◽  
Epidemic Control ◽  
Optimal Control Strategy ◽  
Content Type ◽  
Total Cost ◽  
Time Optimal ◽  
The Impact

Purpose – The purpose of this paper is to use analytical method and optimization tools to suggest time-optimal vaccination program for a basic SIR epidemic model with mass action contact rate when supply is limited. Design/methodology/approach – The Lagrange Multiplier Method and Pontryagin’s Maximum Principle are used to explore optimal control strategy and obtain analytical solution for the control system to minimize the total cost of disease with boundary constraint. The numerical simulation is done with Matlab using the sequential linear programming method to illustrate the impact of parameters. Findings – The result highlighted that the optimal control strategy is Bang-Bang control – to vaccinate with maximal effort until either all of the resources are used up or epidemic is over, and the optimal strategies and total cost of vaccination are usually dependent on whether there is any constraint of resource, however, the optimal strategy is independent on the relative cost of vaccination when the supply is limited. Practical implications – The research indicate a practical view that the enhancement of daily vaccination rate is critical to make effective initiatives to prevent epidemic from out breaking and reduce the costs of control. Originality/value – The analysis of the time-optimal application of outbreak control is of clear practical value and the introducing of resource constraint in epidemic control is of realistic sense, these are beneficial for epidemiologists and public health officials.

scholarly journals ON DIFFERENTIATION OF FUNCTIONALS OF APPROXIMATING PROBLEMS IN THE FRAME OF SOLUTION OF FREE TIME OPTIMAL CONTROL PROBLEMS BY THE SLIDING NODES METHOD

2018 ◽  
pp. 861-876
Author(s):  
Andrei Vladimirovich Chernov
Keyword(s):  
Optimal Control ◽  
Optimal Control Problems ◽  
Free Time ◽  
Time Optimal Control ◽  
Control Problems ◽  
Control Parametrization ◽  
Derivative Formulas ◽  
Control Parametrization Technique ◽  
Time Optimal ◽  
And Control

We give strict justification for derivative formulas of functionals in problems approximating free time optimal control problems in the frame of sliding nodes method and control parametrization technique. As example we present results of numerical solution for landing on the Moon problem.

Shape memory alloy actuators in smart structures: Modeling and simulation

2004 ◽  
Vol 57 (1) ◽  
pp. 23-46 ◽  
Author(s):  
Stefan Seelecke ◽  
Ingo Mu¨ller
Keyword(s):  
Optimal Control ◽  
Shape Memory Alloy ◽  
Modeling And Simulation ◽  
Shape Memory ◽  
Smart Structures ◽  
Review Article ◽  
Material Behavior ◽  
Control Methods ◽  
Time Optimal ◽  
And Control

This review article gives an overview of the new and quickly developing field of shape memory alloy (SMA) actuators in smart structures. The focus is on the aspects of modeling and simulation of such structures, a task that goes beyond classical modeling approaches as it has to combine constitutive modeling with structural and control aspects in a highly interdisciplinary way. We review developments in each of these fields, trying to combine them into a smooth picture of how to treat the problem efficiently. After a discussion of modeling aspects with particular regard to actuator applications, the simulation of standard feedback control methods is demonstrated. Subsequently, model based methods from optimal control theory are presented, accounting for the strongly nonlinear and hysteretic material behavior of SMAs. Real-time optimal control methods are introduced and, finally, aspects of finite element implementation of an SMA actuator model are discussed and illustrated by the simulation of an adaptive aircraft wing. This review article cites 155 references.

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