Oxygen control in a wastewater treatment plant using adaptive

predictive controllers

Gregor Kandare, Jozef Stefan Institute, Slovenia

Adaptive predictive control

SET POINTDESIREDOUTPUT

PROCESSOUTPUT

CONTROLSIGNAL

DRIVER CONTROL

BLOCKBLOCKPROCESS

ADAPTIVE

MECHANISM

EXPERT

BLOCK

Process description

6 pools with butterfly valves and 2 dissolved oxygen sensors each.

4 blowers with diffuser for pressure control.

Process description

Process description

Control issues

Biological dynamics of the process Aleatory operation context Lack of process information Interactive nature of the process

Control objectives Maintain the dissolved oxygen signal at its

setpoint by manipulationg the aeration with butterfly valves.

Maintain the air pressure in the main air conduct at a setpoint that minimises energy consumption and assures good oxygen control.

Control strategy

6 controllers – one for each pool

Adaptive predictive controller

Biological reactor

Oxygen setpoint

PV: Oxygen

Measured disturbance:air flow

Valve opening

PID control

Oxygen and valve opening

PID control

Air pressure and airflow

Adaptive predictive control

Oxygen and valve opening

Adaptive predictive control

Air pressure and airflow

Oxygen control evaluation

Reactor PID AP Factor

1 0.3974 0.1863 2.13

2 0.6632 0.2528 2.62

5 0.5221 0.1432 3.65

6 0.9138 0.151 6.05

Energy optimisation

Objectives: Maintain air pressure at a minimal level which

still permits satisfactory oxygen control. Maintain dissolved oxygen setpoints at a

minimal level that ensures required effluent

water quality.

Pressure optimisation

Pressure optimisation

Pressure optimisation

Pressure optimisation

Change PID – adaptive predictive

Energy consumption estimation

dVpdW W – energy, p – pressure, V - volume

VpdtdV

pdtdW

P P – power, ΦV - airflow

1

0

)()()( 1

t

t

V dtttptW W – consumed energy in each pool ina time interval [t0,t1]

Consumption reduction

Pool

Average power consumed with PID control

Average power consumed with AP control with pressure optimisation

Average energy savings [%]

Pool 1 51.36 42.25 17.74

Pool 2 61.55 34.97 43.18

Pool 5 67.63 52.28 22.70

Pool 6 54.47 41.98 22.93

Total 235.01 171.489 27.03

Conclusions The adaptive predictive controllers stabilise the

process and maintain oxygens at therir setpoints

More stable oxygen control and pressure setpoint optimisation decrease energy consumption by 15-23 %