Reglerteknik, TNG028 - Lecture 1 - Linköping Universitywebstaff.itn.liu.se/~annlo98/TNG028/lectures/TNG028_Fo1.pdfTNG028 - Lecture 1 Anna Lombardi September 2, 2019 Lectures (13x2

Reglerteknik, TNG028Lecture 1

Anna Lombardi

TNG028 - Lecture 1 Anna Lombardi September 2, 2019

Welcome!

Reglerteknik - Automatic Control

TNG028 - 6 points (hp)

Course responsible: Anna Lombardi


Reglerteknik

Lectures 13x2 hours

Tutorials 12x2 hours

Lab sessions 3x4 hours

• Anna Lombardi

room: TP6166

email: [email protected]


Lectures (13x2 hours)

• Preliminary plan of the lectures (course info)

read in advance chapters of the book

• Slides available on the net

• Lectures are given in English


Tutorials (12x2 hours)

• Preliminary plan of the tutorials (course info)

• Students are supposed to solve the exercises

• Teacher helps and discusses the solution

solve exercises in advance

• 3 classes: Omer, Anna

group 1: MT3.agroup 2: MT3.bgroup 3: ED3 + KTS3

• Tutorials are given in English


Lab sessions (3x4 hours)

MinSeg robot

It consists of Arduino microcontroller,DC-motor and wheels



• Lab 1: DC-motor modelling and parameter identi�cation

• Lab 2: DC-motor PID control

• Lab 3: MinSeg balancing using pole-placement

• SIGN in the lists in LISAM

deadline approx 3 days before lab starts

• Lab PM available in Lisam

• Lab assistants: Kjell (lab 1, 2), Omer (lab 3)

• Lab sessions are part of the exam! Keep the signed lab PM



• Lab 1: DC-motor modelling and parameter identi�cation

• Lab 2: DC-motor PID control

• Lab 3: MinSeg balancing using pole-placement

• Assignments must be prepared before each lab.

• Assignments are individual

• Assignments must be handed to the lab assistant at thebeginning of lab session

• Assignments can be submitted in Lisam before the lab session

• Lab sessions are part of the exam! Keep the signed lab PM


Reglerteknik

• Lectures and tutorials are complementary:

- lectures are aimed to discuss theory- only few examples are illustrated during the lectures- tutorials are aimed to discuss and practice computational issues

the course is planned assuming that students attend bothlectures and tutorials

• Times for questions will be scheduled every week

- plan your work according to when you can get help


Literature

• T.Glad, L.LjungReglerteknik - Grundläggande teori.Studentlitteratur

• Reglerteknik: Exercises + Solutions for Exercises in AutomaticControl. Bokakademin

They can be downloaded here

• Books in English (see list in the course info in Lisam)

http://www.control.isy.liu.se/student/tsrt19/ht1/file/rt_exercises.pdf


Exam

• Exercises for a total of 50 points

• Time: 5 hours

• Text is both in Swedish and English

• Use of course book is allowed

• No notes in the book

• Tables of formulas are NOT allowed during the exam


Homepage of the course

Lisam

• Course info: plan of lectures, plan of tutorials

• Material for the course: lecture slides, examples, lab PM, oldexams

• Lists for lab registration

• Submission of lab assignments

• Quiz

• Results (pass/fail) of the labs

http://lisam.liu.se


Videos on Control System Lectures

• Videos by Brian Douglas are available on YouTube

• At the end of some lectures links to related videos will be given

• Videos are NOT intended to replace lectures

• Videos provide examples and are seen as a mean for a deeperinsight in the topic


Quiz

• Available in Lisam in the menu on the left

• Quiz is intended as a tool for the students to check which topicsfrom the lectures are clear and which topics need to be furtherinvestigated

• Quiz can help the teacher for feedback from the lectures

• Students are free to answer (but participation is advised)

• No credits for answering the quiz

• Some questions from the quiz will be given in the exam


Quiz

From course evaluation 2018:

Studenterna uppskattade Quizet efter föreläsningarna på Lisam,det gick snabbt att göra och hjälpte en ta reda på vad de förstodav det som tagits upp på föreläsningarna.Även de som gjorde Quizen vid ett senare tillfälle tyckte att devar ett bra sätt att repetera det som gåtts igenom i kursen närtentaperioden närmade sig.


Feedback from 2018

0

5

10

15

20

25

30

35

40

45

UK 3 4 5

Perc

enta

ge s

tude

nts

Grade

TNG028 - October exam

2013

2014

2015

2016

2017

2018


Feedback from 2018

• Some worse results in the exam

• it was not because of a more di�cult exam• many students did not attend lectures and tutorials• about 20% students did not take �rst exam in October

• Course evaluation: exam

Studenterna tyckte att tentan var bra upplagd, utan oväntade

överraskningar. Studenterna upplevde även att användning av

boken gjorde det mer likt arbetslivet vid liknande uppgifter.


Feedback from 2018

• Spring 2018: Gyllene moroten

What is new

• Labs based on Arduino introduced 2018 ⇒ improvements

• Quiz: some more explanations in the answers


Today lecture

We will try to answer the following questions:

• What is automatic control?

• Where can we �nd automatic control?

• Why do we need automatic control?


Automatic control

Automatic control is the art to make �things� ac-complish desired objectives


Automatic control

From Wikipedia:

Automatic control is the research area and theoretical base formechanization and automation, employing methods frommathematics and engineering.


What is Automatic Control?

Control is the adjustment of some knob in response to some measureof desirability. Humans do it all the time. If the shower water is toocold, we open the hot water valve to heat it up. If the chips are notsalty enough, we shake some salt on them. If it is raining, we openthe umbrella. If there is background noise we converse in a loudervoice.

Control is taking action to �x something, to regulate something, tomake something come out in a desirable way.Biological beings do it, but when the control is done by a device builtby humans, when it is performed autonomously by machine orcomputer, it is called automatic control.From "American Automatic Control Council"


Successful examples of automatic control...

Segway

Device similar to the inverted pendulum

It is kept upright by a feedback controlsystem



Computer: hard disk controller

The reading arm must be positioned inthe right position as fast as possible whilethe disk is rotating.Without control when the arm is moved itoscillates with the consequence that ittakes longer before it stops and data canbe read.



Home: climate control

It works by comparing the actual temperaturewith the desired temperature, the systemthen operates according to this comparison.For example if the actual temperature is toohot the air conditioner is turned on.The goal is to bring the comparison betweenthe actual and desired temperatures as closeto zero as possible.



Cars

• Adaptive Cruise ControlThe regular cruise control system maintainsthe set speed of the vehicle regardless ofany external in�uences.Adaptive Cruise Control systems use sensorsto monitor the vehicles ahead, and if theybecome too close, the speed of the vehicleis decreased in order to maintain a safedistance between the cars.

• ESP - Electronic Stability Program

http://www.youtube.com/watch?v=L7oqIPj1QEc



Mobile telephony

• Mobile phones switch from one tower to anotherautomatically

• Internet: maximisation of transmission speed



Industry

• Quadrupedal pack robot

• Process is controlled to obtain high quality ofproduct with minimisation of discharge ande�ect on environmentFor example: thickness control system for metal.After the metal passes through the rollers, Xrays measure its thickness and compare it to adesired thickness. Any di�erence is adjusted bya screw-down position control that changes thegap at the rollers in which the metal passes.

http://www.youtube.com/watch?v=b2bExqhhWRI



Human body

• Our bodies self-regulate themselves all the wayfrom sweat to regulate overall temperature ,down to the mechanism generating antibodies

• medical treatment: anaesthesia, insulin pump,pace maker


Control problem

Example: adjusting the temperature of a shower

From "American Automatic Control Council"


Control problem

General feedback loop

Referencecompare Feedback

AdjustmentPhysicalSystem

Measurement

error Actuate input output

measured output

From "American Automatic Control Council"


Control problem

What is common to all these control problems?

They can all be described in the following way:

u

v

yS

u control signal, input

y measured signal, output

v disturbance

S system

Choose the input signal u so that the system (in terms of theoutput signal y) behaves as desired according to a reference signal r.


Automatic control...

Reasons for using automatic control

• Reduce workload

• Perform tasks people cannot

• Reduce the e�ects of disturbances

• Reduce the e�ect of plant variations

• Stabilize an unstable system

• Improve the performance of a system


Example: cruise control

Cruise control maintains constant speed in a car independently ofroad inclines or wind.

• input - u(t) driving/braking force

• output - y(t) speed of the car

• disturbance - v(t) inclination of the road

• reference signal - r(t) desired speed


Example: cruise control - DYNAMICS

Assumption: air resistance proportional to speed: f(y(t)) = cy(t)

Newton's law: F (t) = ma(t) ⇒ my(t) = u(t)− f(y(t))− v(t)

y(t) + cmy(t) = 1

m(u(t)− v(t)) DYNAMIC

Assume:m = 1000 kg, c = 200 Ns/mReference signal r(t) = 25m/s = 90km/h desired speed


Example: cruise control - NOMINAL CASE

Flat road v = 0 ⇒ y(t) + cmy(t) = 1

mk t ≥ 0

If

Input is chosen as a step: u(t) =

{k t ≥ 00 t < 0

thenSolution: y(t) = k

c

(1− e−

cmt)

speed asymptotically settles down at kc

⇒ desired speed can be reached with a proper choice of the input k


Example: cruise control - NOMINAL CASE

Input chosen as: u(t) =

{200 · r(t) t ≥ 00 t < 0

y(t) +200

1000y(t) =

5000

1000, t ≥ 0

Solution: y(t) = 25(1− e−0.2t

)desired speed is reached asymptotically

�� Cruise control computations


Example: cruise control - NOMINAL CASEStudy the behaviour of the car on a �at road with a constant input


Example: cruise control

Our car (m = 1000 kg, c = 200 Ns/m ) can reach the desired speedr(t) = 25 if a step input with k = 200 · r(t) = 5000 is applied.

What happens if:

• the model is not correct, i.e. m 6= 1000 kg, c 6= 200 Ns/m

• road has a slope, i.e. v(t) = mg sinϕ(t)

Is it still possible to reach the desired speed r(t) = 25 with a stepinput k = 5000?


Example: cruise control - ERRORS ON THE MODEL

Errors on the model: the wind test was wrong: c = 150 Ns/m

Model: y(t) +150

1000y(t) =

5000

1000, t ≥ 0

With the same input signal, the speed becomes:

y(t) = 33.3(1− e−0.15t

)The car reaches a speed that is too high.

The reason is that we don't take into consideration the actual speed.


Example: cruise control - ERRORS ON THE MODEL


Example: cruise control - DISTURBANCES

Disturbance depending on the slope of the road: v(t) = mg sinϕ(t)where ϕ(t)= slope of the road

Assumption: ϕ = 10◦ (uphill slope) ⇒ v(t) = mg sin(10◦) ≈ 1700

Model: y(t) +200

1000y(t) =

3300

1000, t ≥ 0

Speed: y(t) =3300

200(1− e−0.2t)

The car is slower: y(t)→ 3300200 = 16.5 6= 25 when t→∞


Example: cruise control - DISTURBANCES


What are the di�culties?

• The process is never known exactly.Cruise control example: di�erent values of the air resistancecoe�cient c.

• There are disturbances in the process.Cruise control example: slope of the road ϕ(t).


Control strategies

• Open-loop control

• Closed-loop controlfeedback control

u yS

rReg

u yS

rRegΣ

+

−

Principle of feedback: correcting actions based on the di�erencebetween desired and actual performance


Example: cruise control - FEEDBACK

Closed-loop control: to feedback velocity

A strategy is to accelerate when driving too slow and to brake whendriving too fast

u(t) = KP (r(t)− y(t))

This is called proportional control, P-control: the constant KP is theonly variable to design in the controller


Example: cruise control with disturbances - FEEDBACK


Outline of the course

• Mathematical models I: time-domain

Synthesis I: PID

• Mathematical models II: frequency-domain

Synthesis II: lead-lag compensation

• Mathematical models III: state-space description

Synthesis III: state-feedback, pole placement, LQ


Summary

Important concepts

• Control problem: input, output, reference signal, disturbance

• Control strategies: open-loop and closed-loop control

• System: di�erential equation

Remember to answer the quiz!

Documents

Reglerteknik, TNG028 - Lecture 1 - Linköping Universitywebstaff.itn.liu.se/~annlo98/TNG028/lectures/TNG028_Fo1.pdfTNG028 - Lecture 1 Anna Lombardi September 2, 2019 Lectures (13x2