scholarly journals Distributed tree-based model predictive control on a drainage water system

2012 ◽  
Vol 15 (2) ◽  
pp. 335-347 ◽  
Author(s):  
J. M. Maestre ◽  
L. Raso ◽  
P. J. van Overloop ◽  
B. De Schutter
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Drainage System ◽  
Water System ◽  
Open Water ◽  
Weather Forecast ◽  
Drainage Water ◽  
Programming Approach ◽  
Continuous Exposure ◽  
Dual Decomposition

Open water systems are one of the most externally influenced systems due to their size and continuous exposure to uncertain meteorological forces. The control of systems under uncertainty is, in general, a challenging problem. In this paper, we use a stochastic programming approach to control a drainage system in which the weather forecast is modeled as a disturbance tree. Each branch of the tree corresponds to a possible disturbance realization and has a certain probability associated to it. A model predictive controller is used to optimize the expected value of the system variables taking into account the disturbance tree. This technique, tree-based model predictive control (TBMPC), is solved in a distributed fashion. In particular, we apply dual decomposition to get an optimization problem that can be solved by different agents in parallel. In addition, different possibilities are considered in order to reduce the communicational burden of the distributed algorithm without reducing the performance of the controller significantly. Finally, the performance of this technique is compared with others such as minmax or multiple MPC.

scholarly journals Model Predictive Control of a River Reach with Weirs

10.29007/1nnf ◽  
2018 ◽  
Author(s):  
Klaudia Horváth ◽  
Bart van Esch ◽  
Jorn Baayen ◽  
Ivo Pothof ◽  
Jan Talsma ◽  
...  
Keyword(s):  
Decision Support ◽  
Convex Optimization ◽  
Decision Support System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Support System ◽  
Water System ◽  
Open Water ◽  
Global Optimum ◽  
Water Levels

A decision support system for water management based on convex optimization, RTC-Tools 2, is applied for a water system containing river branches connected by weirs. The advantage of convex optimization is the ability of finding the global optimum, which makes the decision support system robust and deterministic. In this work the convex modeling of open water channels and weirs is presented. The decision support system is implemented for a river made of 12 river reaches divided by movable weirs. It is shown how the discharge wave is dispatched in the river without the water levels exceeding the bounds by controlling the weir heights. After this test the optimization can be applied to a realistic numerical model and model predictive control can be implemented.

scholarly journals Time-instant optimization for hybrid model predictive control of the Rhine–Meuse delta

2013 ◽  
Vol 15 (2) ◽  
pp. 271-292 ◽  
Author(s):  
H. van Ekeren ◽  
R. R. Negenborn ◽  
P. J. van Overloop ◽  
B. De Schutter
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Sea Water ◽  
Water System ◽  
Open Water ◽  
Time Instant ◽  
Water Levels ◽  
Continuous Variables ◽  
Discrete Events ◽  
Control Structures

In order to ensure safety against high sea water levels, in many low-lying countries, water levels are maintained at certain safety levels, and dikes have been built, while large control structures have been installed that can also be adjusted dynamically after they have been constructed. Currently, these control structures are often operated purely locally, without coordination of actions being taken at different locations. Automatically coordinating these actions is difficult, as open water systems are complex, hybrid dynamical systems, in the sense that continuous dynamics (e.g. the evolution of the water levels) appear mixed with discrete events (e.g. the opening or closing of barriers). In low lands, this complexity is increased further due to bi-directional water flows resulting from backwater effects and interconnectivity of flows in different parts of river deltas. In this paper, we propose a model predictive control (MPC) approach that is aimed at automatically coordinating the actions of control structures. The hybrid dynamical nature of the water system is explicitly taken into account. In order to relieve the computational complexity involved in solving the MPC problem, we propose TIO-MPC, where TIO stands for time-instant optimization. Using this approach, the original MPC optimization problem that uses both continuous and integer variables is transformed into a problem involving only continuous variables. Simulation studies of current and future situations are used to illustrate the behavior of the proposed scheme.

scholarly journals A New Model Predictive Control Method for Eliminating Hydraulic Oscillation and Dynamic Hydraulic Imbalance in a Complex Chilled Water System

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3608
Author(s):  
Yang Yuan ◽  
Neng Zhu ◽  
Haizhu Zhou ◽  
Hai Wang
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Water System ◽  
Energy Performance ◽  
Effective Control ◽  
New Model ◽  
Chilled Water ◽  
Chilled Water System ◽  
Hydraulic Oscillation

To enhance the energy performance of a central air-conditioning system, an effective control method for the chilled water system is always essential. However, it is a real challenge to distribute exact cooling energy to multiple terminal units in different floors via a complex chilled water network. To mitigate hydraulic imbalance in a complex chilled water system, many throttle valves and variable-speed pumps are installed, which are usually regulated by PID-based controllers. Due to the severe hydraulic coupling among the valves and pumps, the hydraulic oscillation phenomena often occur while using those feedback-based controllers. Based on a data-calibrated water distribution model which can accurately predict the hydraulic behaviors of a chilled water system, a new Model Predictive Control (MPC) method is proposed in this study. The proposed method is validated by a real-life chilled water system in a 22-floor hotel. By the proposed method, the valves and pumps can be regulated safely without any hydraulic oscillations. Simultaneously, the hydraulic imbalance among different floors is also eliminated, which can save 23.3% electricity consumption of the pumps.

Event-triggered model predictive control of positive systems with random actuator saturation

2021 ◽  
Author(s):  
Junfeng Zhang ◽  
Suhuan Zhang ◽  
Peng Lin
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Actuator Saturation ◽  
Domain Of Attraction ◽  
Programming Approach ◽  
Interval Estimate ◽  
Positive Systems ◽  
Predictive Algorithm ◽  
Controller Gain ◽  
Event Triggered

Abstract This paper investigates the event-triggered model predictive control of positive systems with actuator saturation. Interval and polytopic uncertainties are imposed on the systems, respectively. First, a new model with actuator saturation obeying Bernoulli distribution is established, which is more general and powerful for describing the saturation phenomenon than the saturation in a certain way. Then, a linear event-triggering condition is constructed based on the state and error signal. An interval estimate approach is presented to reach the positivity and stability of the systems. The saturation part in the controller is technically transformed into a non-saturation part. Thus, a linear programming approach is proposed to compute the event-triggered controller gain and the corresponding domain of attraction gain. A predictive algorithm is introduced for the computation of the event-triggered controller parameters. Finally, an example is provided to illustrate the validity of the design.

Nonlinear distributed model predictive control for complex systems: application for hydraulic system

2018 ◽  
Vol 41 (10) ◽  
pp. 2751-2763 ◽  
Author(s):  
Nadia Hajji ◽  
Saber Maraoui ◽  
Larbi Chrifi-Alaoui ◽  
Kais Bouzrara
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Hydraulic System ◽  
Water Levels ◽  
Distributed Model ◽  
Dual Decomposition ◽  
Decomposition Approach ◽  
Distributed Model Predictive Control ◽  
Nonlinear Predictive Control ◽  
Tank System

In this paper, a nonlinear distributed model predictive control based on dual decomposition approach is proposed for complex system. The global system can be decomposed into several subsystems and each one will be managed by its own controller. To design the nonlinear predictive control in a distributed fashion, an analytical solution is proposed. The latter is based on the approximation of the error using its expansion of Taylor series. The proposed approach is implemented on the three tank system to control the water levels. Simulation results demonstrate the effectiveness of the proposed approach.

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