scholarly journals Model-based methodology for the design of optimal control strategies in MBR plants

2017 ◽  
Vol 75 (11) ◽  
pp. 2546-2553 ◽  
Author(s):  
Juan Odriozola ◽  
Sergio Beltrán ◽  
Montse Dalmau ◽  
Luis Sancho ◽  
Joaquim Comas ◽  
...  
Keyword(s):  
Optimal Control ◽  
Total Nitrogen ◽  
Conceptual Knowledge ◽  
Wastewater Treatment Plants ◽  
Control Strategies ◽  
Control Laws ◽  
Operational Strategies ◽  
Model Based ◽  
Different Temperatures ◽  
Input Variables

This paper proposes a model-based methodology that allows synthesising the most appropriate strategies for optimising the operation of wastewater treatment plants (WWTPs). The methodology is applied with the aim of maximising the nitrogen removal in membrane bioreactors (MBRs). The proposed procedure is based on a systematic approach composed of four steps. First, a sensitivity analysis of the input variables is carried out in order to obtain a first assessment of the potential for operational improvements. Then, the optimum input variable values are calculated by a model-based optimisation algorithm that minimises a cost function associated with the effluent total nitrogen at different temperatures. Then, the optimum operational strategies are identified. Finally, these operational strategies form the conceptual knowledge base for designing automatic control laws. The obtained optimal control strategies have shown a significant improvement in performance in comparison with fixed operation for the studied case, reducing the total nitrogen by 40%.

Adaptive Vibration Control of an Axially Moving String

1999 ◽  
Vol 121 (1) ◽  
pp. 41-49 ◽  
Author(s):  
M. S. de Queiroz ◽  
D. M. Dawson ◽  
C. D. Rahn ◽  
F. Zhang
Keyword(s):  
Control Strategies ◽  
Adaptive Controller ◽  
String Tension ◽  
Control Force ◽  
Control Laws ◽  
Axially Moving String ◽  
Model Based ◽  
Parameter Field ◽  
Axially Moving ◽  
Mechanical Guide

In this paper, the displacement of an axially moving string is regulated using a control force and a control torque applied to the string via a mechanical guide. Given the hybrid model of the string system (i.e., distributed parameter field equation coupled to discrete actuator equations), Lyapunov-type arguments are utilized to design model-based and adaptive control laws that exponentially and asymptotically stabilize the string displacement, respectively. The proposed control laws are based on measurements of the string displacement, velocity, slope, and slope rate at the mechanical guide. While the model-based controller requires exact knowledge of the actuator/string parameters (e.g., actuator mass and string tension), the adaptive controller estimates the parameters online. Dynamic simulation results demonstrate the vibration damping provided by the control strategies.

EXPLOITING OPTIMAL CONTROL FOR TARGET-ORIENTED MANIPULATION OF (BIO)CHEMICAL SYSTEMS: A MODEL-BASED APPROACH TO SPECIFIC MODIFICATION OF SELF-ORGANIZED DYNAMICS

2005 ◽  
Vol 19 (25) ◽  
pp. 3763-3798 ◽  
Author(s):  
D. LEBIEDZ
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Open Loop ◽  
External Control ◽  
Spatiotemporal Pattern ◽  
Chemical Systems ◽  
Spatiotemporal Pattern Formation ◽  
Model Based ◽  
Self Organized ◽  
Feedback Optimal Control

In this paper we review recent progress in the development and application of advanced optimal control methods for target-oriented manipulation of self-organized dynamics in (bio)chemical reaction systems. We discuss results related to nonlinear model-based external control aimed at forcing and stabilization of spatiotemporal pattern formation and specific driving, phase resetting and annihilation of limit cycle oscillators. We refer to both open-loop and feedback optimal control approaches. Optimal control strategies for self-organized systems may be highly beneficial in applications concerned with steering of technical processes in open non-equilibrium systems and specific manipulation of self-organized cellular dynamics in biomedicine.

scholarly journals Intelligent Control/Operational Strategies in WWTPs through an Integrated Q-Learning Algorithm with ASM2d-Guided Reward

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 927 ◽  
Author(s):  
Jiwei Pang ◽  
Shanshan Yang ◽  
Lei He ◽  
Yidi Chen ◽  
Nanqi Ren
Keyword(s):  
Optimal Control ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Learning Algorithm ◽  
Control Strategies ◽  
Treatment Plant ◽  
Model Verification ◽  
Operational Strategies ◽  
Q Learning ◽  
Time Optimal

The operation of a wastewater treatment plant (WWTP) is a typical complex control problem, with nonlinear dynamics and coupling effects among the variables, which renders the implementation of real-time optimal control an enormous challenge. In this study, a Q-learning algorithm with activated sludge model No. 2d-guided (ASM2d-guided) reward setting (an integrated ASM2d-QL algorithm) is proposed, and the widely applied anaerobic-anoxic-oxic (AAO) system is chosen as the research paradigm. The integrated ASM2d-QL algorithms equipped with a self-learning mechanism are derived for optimizing the control strategies (hydraulic retention time (HRT) and internal recycling ratio (IRR)) of the AAO system. To optimize the control strategies of the AAO system under varying influent loads, Q matrixes were built for both HRTs and IRR optimization through the pair of <max reward-action> based on the integrated ASM2d-QL algorithm. 8 days of actual influent qualities of a certain municipal AAO wastewater treatment plant in June were arbitrarily chosen as the influent concentrations for model verification. Good agreement between the values of the model simulations and experimental results indicated that this proposed integrated ASM2d-QL algorithm performed properly and successfully realized intelligent modeling and stable optimal control strategies under fluctuating influent loads during wastewater treatment.

scholarly journals Deduction of Optimal Control Strategies for a Sector-Coupled District Energy System

2021 ◽  
Author(s):  
Adrian Grimm ◽  
Patrik Schönfeldt ◽  
Herena Torio ◽  
Peter Klement ◽  
Benedikt Hanke ◽  
...  
Keyword(s):  
Optimal Control ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Discrete Time ◽  
Control Strategies ◽  
Energy System ◽  
Linear Discriminant ◽  
Perfect Foresight ◽  
District Energy ◽  
Model Based

We present a method to turn results of model-based optimisations into resilient and comprehensible control strategies. Our approach is to define priority lists for all available technologies in a district energy system. Using linear discriminant analysis and the results of the optimisations, these are then assigned to discrete time steps using a set of possible steering parameters. In contrast to the model-based optimisations, the deduced control strategies do not need perfect foresight but solely rely on data about the present. Our result indicate that the results of the control strategies obtained using the proposed method are comparable to the results of the linear optimisations, in our case in terms of emissions and prices.

Cooperative Optimal Synchronization of Networked Uncertain Nonlinear Euler–Lagrange Heterogeneous Multi-Agent Systems With Switching Topologies

2014 ◽  
Vol 137 (4) ◽  
Author(s):  
A. R. Mehrabian ◽  
K. Khorasani
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Control Algorithms ◽  
Synchronization Control ◽  
Multi Agent Systems ◽  
Control Laws ◽  
Control Techniques ◽  
Multi Agent ◽  
Systems Simulation ◽  
Attitude Synchronization

This paper is concerned with design of distributed optimal synchronization control strategies for a class of networked nonlinear heterogeneous multi-agent (HMA) systems whose dynamics are governed by Euler–Lagrange (EL) equations. We employ optimal control techniques to design synchronization (consensus seeking) and set-point regulation controllers for HMA systems through optimization of individual cost functions. We introduce an analytical solution to the optimization problem and show that the developed optimal control laws can manage switchings in the communication network topology. Additionally, we propose two control strategies (namely, adaptive and robust) to modify and generalize the developed optimal control laws in presence of parametric uncertainties in the HMA systems. Simulation results for the attitude synchronization control of a network of eight spacecraft are presented to demonstrate the effectiveness and capabilities of our proposed control algorithms.

scholarly journals Deduction of Optimal Control Strategies for a Sector-Coupled District Energy System

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7257
Author(s):  
Adrian Grimm ◽  
Patrik Schönfeldt ◽  
Herena Torio ◽  
Peter Klement ◽  
Benedikt Hanke ◽  
...  
Keyword(s):  
Optimal Control ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Discrete Time ◽  
Control Strategies ◽  
Energy System ◽  
Linear Discriminant ◽  
District Energy ◽  
Model Based

We present a method to turn the results of model-based optimisations into resilient and comprehensible control strategies. Our approach is to define priority lists for all available technologies in a district energy system. Using linear discriminant analysis and the results of the optimisations, these are then assigned to discrete time steps using a set of possible steering parameters. In contrast to the model-based optimisations, the deduced control strategies do not need predictions or even perfect foresight but solely rely on data about the present. The case study using priority lists presents results in terms of emissions and prices that are only about 5% off the linear optimum. Considering that the priority lists only need information about the present, the results of the control strategies obtained using the proposed method can be considered competitive.

Analysis of Constrained Optimal Control with Related Constraints of Input Variables

2014 ◽  
Vol 39 (5) ◽  
pp. 679-689 ◽  
Author(s):  
Xiong-Lin LUO ◽  
Xiao-Long ZHOU ◽  
Shu-Bin WANG
Keyword(s):  
Optimal Control ◽  
Constrained Optimal Control ◽  
Input Variables

Danish Experience with Emergent Hydrophyte Treatment Systems (EHTS) and Prospects in the Light of Future Requirements on Outlet Water Quality

1990 ◽  
Vol 22 (3-4) ◽  
pp. 65-72 ◽  
Author(s):  
H.-H. Schierup ◽  
H. Brix
Keyword(s):  
Wastewater Treatment ◽  
Total Nitrogen ◽  
Total Phosphorus ◽  
Wastewater Treatment Plants ◽  
Sewage Treatment ◽  
Reed Beds ◽  
Effluent Quality ◽  
Multi Stage ◽  
Run Off ◽  
Stage System

Since 1983 approximately 150 full-scale emergent hydrophyte based wastewater treatment plants (reed beds) have been constructed in Denmark to serve small wastewater producers. The development of purification performance for 21 plants representing different soil types, vegetation, and hydraulic loading rates has been recorded. Cleaning efficiencies were typically in the range of 60-80% reduction for BOD, 25-50% reduction for total nitrogen, and 20-40% reduction for total phosphorus. The mean effluent BOD, total nitrogen and total phosphorus concentrations of the reed beds were 19 ± 10, 22 ± 9 and 6.7 ± 3.2 mg/l (mean ± SD), respectively. Thus, the general Danish effluent standards of 8 mg/l for N and 1.5 mg/l for P for sewage plants greater than 5,000 PE cannot be met by the present realised design of EHTS. The main problem observed in most systems is a poor development of horizontal hydraulic conductivity in the soil which results in surface run-off. Since the political demands for effluent quality will be more strict in the future, it is important to improve the performance of small decentral sewage treatment plants. On the basis of experiences from different types of macrophyte based and conventional low-technology wastewater treatment systems, a multi-stage system is suggested, consisting of sedimentation and sand filtration facilities followed by basins planted with emergent and submergent species of macrophytes and algal ponds.

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