Adaptive Active Control of Sound in Smart Rooms (2014)

ADAPTIVE ACTIVE CONTROL OF SOUND

IN SMART ROOMS

DR. IMAN ARDEKANI

2

This Presentation

Introduction 2Stabilization of ANC in Smart Rooms 3

1 Background

Remote Acoustic Sensing in Smart Rooms 4Experiments5Conclusion and Future Work 6

3

Background

Why ANC in Smart rooms:

① Evolving technological approaches

② Future of living rooms, hospital rooms office rooms & class rooms

③ Research with impact

Smart Rooms

4

Background

① Interesting theory in Physics

② Interesting theory in Control Engineering

③ High-tech design & implementation, e.g. FPGA, DSP

④ New challenges (when integrated with smart rooms)

Active Noise Control

5

Background

Active Noise Control / Smart Sensor Networks for Passenger Cars

Professional Research on ANC and Smart Rooms- Founder of Unitec Smart Rooms- Adaptive ANC in Smart Rooms- Finalist of IBM Innovation Award 2014

PhD & FRDF Postdoctoral Research on Adaptive ANC- More than 30 journal/conference papers on ANC- International research collaboration- Nominated for UoA Top Doctoral Thesis Award (by FoE)

6

INTRODUCTION

Smart Rooms Adaptive ANC Challenges

7

EnhancingQuality of Lifein Smart Living Rooms

8

EnhancingHuman Productivityin Smart Office Rooms

9

Enhancing Quality of Carein Smart Hospital Rooms

10

Enhancing Quality of Learningin Smart Class Rooms

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Smart Rooms’ Structure - Proposed

Acoustic Sig Pro

Medical Sig Pro

Features

Room BookRoom Book

Computer

Vision

Other Sig Pro Tech

Feat

ures

Controllers

Intelligent Agents

Robots

Other

Devices

Room BookRoom Book

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This Seminar Focus

Acoustic Sig Pro

Medical Sig Pro

Room BookRoom Book

Computer

Vision

Other Sig Pro Tech

Controllers

Intelligent Agents

Robots

Other

Devices

Room BookRoom Book

Features

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Why ANC in Smart Rooms?

Acoustic Sig Pro

Intelligent Agents

Noise

Why Noise Control? 1. Human productivity (especially in open plan office rooms)2. Quality of life (more pleasant rooms) 3. Quality of interaction between smart room and occupants (speech)

Why not Passive Noise Control? • Passive Noise Control is bulky and inefficient for low frequency.

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ANC in Smart Rooms

Acoustic Sig Pro

Intelligent Agents

Noise

Residual Noise

Noise

Anti-Noise

1) can not be measured.

2) and are unknown dynamic systems.

P

S

PS

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ANC Stability

1 2 3

Uncertainty

Stab

ility

High

Moderat

eLo

w

Low Moderate High

1

2

3

Traditional ANC algorithms suffer low robustness in real-life applications. 1

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Acoustic Sensing in ZoQ

- It is essential to place an Error Microphone (Err Mic.) in the desired quiet zone to sense the residual noise.

- The size of the quiet zone is very limited. - Can we use one of the smart room’s built-in microphone instead?- If we can, then

- 1) more effective use of space in the quiet zone- 2) more cost effective hardware design

10 dB ZoQ

NoiseP

S𝜆20

Err Mic

2

18

STABILIZATION OF ANC IN SMART ROOMS

Root Locus (RL) Method ANC RL Plots Stabilization

Process

1

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Numerical methods

Root Locus Method

Char Eq.

LTI Digital Systems

Numericalmethods

x

x

x

z-plane

𝐺 (𝑧 ) 𝐺 (𝑧 )

Char Eq.

RL

𝑘=0

Increasin

g

✗

𝐺 (𝑧 )=𝑎0+𝑎1 𝑧+𝑎2 𝑧

2+…𝑏0+𝑏1𝑧+𝑏2 𝑧

2+…

𝐺 (𝑧 )= 𝐴(𝑧)𝐵(𝑧) 𝐻 (𝑧 )= 𝐺(𝑧)

1+𝑘𝐺 (𝑧)=

𝐴(𝑧)𝐵(𝑧)+𝑘 𝐴(𝑧 )

𝑘

𝑘=∞

x

x

z-planex

x

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2

1

Root Locus Methods

LTI Digital Systems

Char Eq.

RL

𝐺 (𝑧 ) 𝐺 (𝑧 )𝑘

Char Eq.

Numericalmethods

x

x

x

z-plane

𝐺 (𝑧 )=𝑎0+𝑎1 𝑧+𝑎2 𝑧

2+…𝑏0+𝑏1𝑧+𝑏2 𝑧

2+…

𝐺 (𝑧 )= 𝐴(𝑧)𝐵(𝑧) 𝐻 (𝑧 )= 𝐺(𝑧)

1+𝑘𝐺 (𝑧)=

𝐴(𝑧)𝐵(𝑧)+𝑘 𝐴(𝑧 )

x

z-planex

x𝑘=0

Increasin

g

𝑘=∞

x

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Root Locus Method

1LTI Digital Systems

2Char Eq.

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𝐴(𝑧)

ANC RL Plots• Adaptation process performed by the FxLMS in adaptive ANC is a recursive

and non-linear process.

• However, by using the Independence Assumptions, a linear approximation

for the FxLMS adaptation process can be obtained.

• FxLMS stability is highly related to the adaptation step-size k so a stability

analysis w.r.t. k is needed.

𝑧𝑄−𝑧𝑄−1+𝑘 𝑃𝑥 ∑𝑚=𝑞

𝑄−1

𝑠𝑚❑ 2𝑧𝑄−1−𝑚=0

𝐵(𝑧)

2Char Eq.

1LTI Digital Systems

is an available parameter but and do not physically exist .

𝑞 𝑄−1

Room impulse response

Ampl

itude

Time index𝑠𝑞

𝑠𝑄− 1

noise power.

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ANC RL Plots

coefficients are always positive .

𝐴(𝑧)

𝑧𝑄−𝑧𝑄−1+𝑘 𝑃𝑥 ∑𝑚=𝑞

𝑄−1

𝑠𝑚❑ 2𝑧𝑄−1−𝑚=0

𝐵(𝑧)

𝐵 (𝑧 )=𝑧𝑄−𝑧𝑄−1

Typical Trajectories for the FxLMS Root Locus(independent of the room acoustics)

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ANC RL Plotsz-plane

Start points of ANC RL are located

at the roots of B(z).

B(z)=zQ-z Q-1

Q-1 start points at the origin and

1 start point at z=1.

z=0

z=1

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ANC RL Plotsz-plane

The real interval of (0,1) belongs

to the ANC RL.

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ANC RL Plotsz-plane

𝑥𝐵

B1

B2

There is always a breakaway

point on (0,1), given by

.

(close to z=1)

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ANC RL Plotsz-plane

𝑥𝐵

B1

B2

B4

B3

There are still Q-2 start points at

the origin:

B3, B4 … BQ starts from the

origin, moving towards their end

points (can take any shapes).

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ANC RL Plotsz-plane

𝑥𝐵

B1

B2

B4

B3

o

o

to infinite end points

to infinite end points

Finite End Points at roots of A(z).

A(z) coefficients: sq2: positive

so all the finite end points are in

the left side of Imaginary axis.

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ANC RL Plotsz-plane

𝑥𝐵

B4

B3

o

o

increasing

k=0B1

B2

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Stabilization Processz-plane

𝑥𝐵

B1

B2

B4

B3

o

o

The root moving on B1

- is closest root to the critical

point

z=1.

- is dominant!

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𝑥𝐵

B1

B2

B4

B3

o

o

The short distance of this root

from z=1 restricts the stability

margin of adaptive ANC.

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𝑥𝐵

B1

B2

B4

B3

o

o

Can we detour B1 so that it can

go further from the critical

point ?

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𝑥𝐵

B1

B2

B4

B3

o

o

How?

By introducing a RL end point in

(0,1): a new root for A(z):

A(z)⟶(z-ξ)A(z)

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Stabilization Process

A(z)⟶(z-ξ)A(z)

z-plane

B1

o𝑥𝐵

B2B4

B5

o

o B3

𝝃A(z)⟶(z-ξ)A(z)

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Stabilization ProcessModified RLOriginal RL

𝑥𝐵

B1

B2

B4

B5

o

o

B1

o

B2B4

B3

o

o B3

𝝃

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Stabilization Process

• but is not an actual systems.

Room Impulse Response

x

Ref Mic.

Err Mic.

+

Current Filter Parameters

Updated Filter Parameters

C(z)Compensator

𝐶 (𝑧 )= 1−𝜉1−𝜉 𝑧− 1

Filtered-Weight FxLMS

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STABILIZATION OF ANC IN SMART ROOMS

1

Summary

• A novel method based on RL theory is developed.

• RL analysis of the adaptation process leads to develop new adaptive ANC algorithms.

• The new algorithms show good stability behavior in smart rooms.

• It is proved mathematically.

• Simulation and practical results support the theoretical findings.

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REMOTE ACOUSTIC SENSING IN SMART

ROOMS

ANC Analysis in Acoustic Domain

Remote ANC Systems

2

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Error Microphone Location

𝜆 20

Traditional ANC

Problems: - very small zone of quiet- space occupied by the error mic

10 dB ZoQ

10 dB ZoQ

Advantage:- effective use of space in quiet zones- Effective use of smart room

hardware resources

Remote ANC (proposed)

e(n) e(n)

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y-axis+

x-ax

is+

𝑊 𝑜𝑝𝑡 (𝑧 )=𝑈𝑥 (𝑧)𝑈 𝑦 (𝑧)

𝐾 𝑥𝑦 𝑧−∆𝑥𝑦

x(n)

Ref Mic

Lx

y(n)

Control Source

Ly

LxLy

Lo

𝑑𝑦𝑑𝑥𝜑 𝑦Lr

𝑑𝑟

e(n)

Lo

Err Mic (ZoQ)

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• Since and are unknown, we cannot implement directly but The FxLMS

algorithm can adaptively adjust the adaptive filter to an estimate of .

𝑊 𝑜𝑝𝑡 (𝑧 )=𝑈𝑥 (𝑧)𝑈 𝑦 (𝑧)

𝐾 𝑥𝑦 𝑧−∆𝑥𝑦


x

Ref Mic.

Err Mic.

+



⟶𝑊𝑜𝑝𝑡 (𝑧 )

FxLMS Algorithm

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Px(n) e(n)

FxLMS

S

Control System

W

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Remote Active Noise Control

y(n)

Ly

y-axis+

x-axis+

Lre(n)

Lo

x(n) Lx

LxLy

Lo

𝑑𝑦𝑑𝑥𝜑 𝑦Lr

𝑑𝑟

𝑑𝑥𝑟 𝑑 𝑦𝑟

𝑊 𝑜𝑝𝑡(𝑧)=𝑊𝑜𝑝𝑡 (𝑧)𝐾 𝜌 𝑧−∆𝜌

Static gain Time-delay

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𝑊 𝑜𝑝𝑡(𝑧)=𝑊𝑜𝑝𝑡 (𝑧)𝜌 (𝑧 )

known

unknown

Px(n) e(n)

FxLMS

S

Control System

Remote ANCAlgorithm

W

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x

Ref Mic.

Err Mic.

+



⟶𝑊𝑜𝑝𝑡 (𝑧 )

FxLMS-based Remote ANC Algorithm

+∆ 𝑒(𝑛)−

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𝑊 𝑜𝑝𝑡(𝑧)=𝑊𝑜𝑝𝑡 (𝑧)𝜌 (𝑧 )

known

unknown

Px(n) e(n)

FxLMS

S

Control System

Remote ANCAlgorithm

W

-


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EXPERIMENTS

Setup Results

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Experimental Setup

NoiseP

S

NI CRIO

Smart Room Mic (Err Mic)

Smart Room Mic (Ref Mic)

Real-time Software(FPGA Design)

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Experimental Results – Remote ANC

10 cm

Initial noise level

Final noise level

Learning Room Acoustics

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Experimental Results – Stability

FxLMS

FwFxLMS

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CONCLUSION

Contributions Future Work

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Contributions

Investigated practical problems with adaptive ANC2Moved towards the integration of ANC into Smart Rooms 3

1 Improved the theoretical understanding of ANC

Developed a flexible and high-performance experimental setup for ANC4Published the results in high ranking journals5Made international collaboration 6

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Future Work – ANC In Medical Devices

MRI

Incubator

Hearing Aids Other devices

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Future Work – Smart Rooms

Acoustic Sig Pro

Medical Technology

Room Book

Computer

Vision

Intelligent Agents

Assisti

ve

Robotics

- Smart Hospital Rooms - Smart Assistive Rooms (for elderly and people with disabilities )

Current

Research

Future

Plan

Energy

Management

Adaptive Active Control of Sound in Smart Rooms (2014)

Technology

Transcript of Adaptive Active Control of Sound in Smart Rooms (2014)