A Cyber-Physical System for Distributed Real-Time Control of Urban - - PowerPoint PPT Presentation

A Cyber-Physical System for Distributed Real-Time Control of Urban Drainage Networks in Smart Cities

Andrea Giordano, Giandomenico Spezzano, Andrea Vinci

ICAR - CNR Rende (CS), Italy

Giuseppina Garofalo, Patrizia Piro

Dipartimento Ingegneria Civile- Indirizzo Idraulica Università della Calabria Rende (CS), Italy

Background

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Sewer system

• The magnitude and the frequency of

flooding in urban areas are likely to increase due to

• climate change
• expanding urbanization
• In current practices, engineers and

administrators focus their attention on flooding phenomena due to rivers inside the cities

• Conversely, There is not enough attention

toward flooding triggered by overload conditions occurring in the sewer system (sewer flooding).

• Flooding phenomena give rise to

potential risks to human life, economic assets and the environment, etc.

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3

Sewer system Drains Road surface

Flooding phenomenon

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Sewer system Drains Road surface

Flooding phenomenon

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“Smart” Gates

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electronically adjustable

• gates. They allow you

dynamically changing the flow of the water

Distributed real-time control

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 Real time control:

• Reading from sensors
• Elaborating information (as soon as possible)
• Actuating on the gates

 Issues related on ‘centralized’ control

• Need for comprehensive mathematical model of the whole hydraulic

network

• Need for communication between each sensor and gate and the

centralized control

• the huge amount of the incoming data gives rise to real time constraint

violation  Proposed approach: fully distributed:

• Computational nodes spread across the drainage network (RaspBerry)
• Only short-range communications are required
• Enabling Agent-based e Swarm Intelligence

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Drainage network

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 A drainage network is made up

• f:
• conduits, i.e. pipes where water

flows

• Inlet nodes, i.e. water entry points

(manhole)

• Outlet nodes, i.e. exit points

where water is discharged into a river, lake, reservoir and so forth

• Junctions, i.e intersection points

for conduits  A whole drainage network of a

city can be broken down in a set of not connected tree-like structured drainage networks which own only on outlet node

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Drainage network

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 A drainage network is defined in a

recursive way: it is made up of a main channel into which recursively defined (sub)network

• discharge. The recursive process

stops when reaching the Most simple Drainage Network (MSDN) made up of only a conduit and an inlet node.

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Drainage network

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Generated networks

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Gates position

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 The gates are inserted at the start

• f each branch, i.e. between the

junctions of the main channel and the sub-networks

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Gate-agents

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 One agent per gate  One agent per outlet

node

 The whole problem

become: «for each network, each agent has to tune its gate in

• rder to ensure that

filling levels of the conduits are balanced as much as possible»

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agent algorithm

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 agents continuously execute

two tasks:

• Task 1: Figuring out the average
• f the water level in the specific

network

• Task 2: triggering specific gates

in order to bring the water level closer to that average

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Task1: Gossip-based algorithm

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 Nodes own such numerical values  The goal is to compute global average even if each node is

able to communicate only with neighbour nodes

 Each node holds the current “local” average value (initially

sets to the measured value)

 These local average values are continuously exchanged

among neighbor nodes which update their local averages by applying the average operator

 It can be proved that the algorithm converges to the global

average value after an enough steps *

 The algorithm ensures fault tolerance and adaptivity

*Jelasity M., Montresor A., Babaoglu O., Gossip-based aggregation in large dynamic networks, ACM

Transactions on Computer Systems 23, 3, 219 - 252, 2005.

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Task2: how to tune the gate?

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 Even though we know the optimal water level to set, we

don’t know how to adjust gates so as to get it

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PID Controller

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 The average value computed in task1 is used as setpoint

• f a PID (Proporzionale, Integrativo, Derivativo) controller

     

t t e

• utput

t setpoint  

       

t e dt d K d e K t e K t u

d t i p

  



 

Average Water level Gate opening degree

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SWMM simulation software

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Customizing SWMM

A A A A A A A A A A A A Real-Time connector SWMM Gossip-Algorithm + PID

Experimental results

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Uncontrolled Controlled

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Any questions?

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