t10kt mw sm lesson 1 course plan

8/10/2019 T10KT MW SM Lesson 1 Course Plan

1/37


2/37

T10KT Main Workshop, Dec. 2-12, 2014. IIT Kharagpur

Course Objectives, Overview

Lecture/Tutorial/Lab Plan

2/37


3/37


Course Objectives

The student should be able to state, explain and illustrate a

set of key concepts related to Control Systems qualitatively

in the context of an engineering application.

Key Concept Example : Negative feedback

State variable

X-ability

Compensation Sampled data model

3/37


4/37


Course Objectives

a) The student should be able to give brief description of a

common practical control system including its componentsand qualitatively state the constraints and performance

objectives

Common Practical Example : The bathroom cistern

Water temperature/flow control in a hot and cold

mixing faucet

Air temperature/flow control in a room/car

Control of voltage in a power supply

Motion control of a crane

4/37


5/37


6/37


Course Objectives

The student should be able to demonstrate key abilities,

related to a control system.Key concepts :

Modeling simple physical systems

Computing transient response to standard

inputs

Determining stability

Stating performance specifications in time and

frequency domains Designing simple compensators

Implementation of the compensator

6/37


7/37T10KT Main Workshop, Dec. 2-12, 2014. IIT Kharagpur

Course Objectives

The student should be able to design numerical or physical

experiments and gather, interpret, analyze resulting data fordesign/analysis of a control system.

Tasks :

Plan experiment to build models

Implement the experiment

Gather and analyse data to build models

Assess, compare and choose specifications of control

system components Determine reasonable closed loop system

specifications

Design and implement a simple compensator

7/37



Additional Objectives

a) Determine related technical specifications of control

applications and their components from performancerequirements and constraints.

b) Design controllers from technical specifications of

control systems.

c) Evaluate and compare different controller designs for thesame system.

d) Validate control system performance by interpreting

system operational data obtained using given controller.

e) Give descriptions of applications of control system

concepts to non-engineering problems.

8/37



Course Overview - 42 hours

Basic Concepts of Control - 4 hours

Models and Response of Linear Systems - 14 hours

Linear Systems Analysis - 8 hours

Linear Control Design - 12 hours

Implementation - 4 hours

9/37



Course May Not Discuss

Industrial Automation and Control

Control System Components

Nonlinear Models and Response

Unmodelled dynamics

Multivariable control

Real-time control software

Computer aided design of control systems

Optimal /adaptive/robust control

10/37



The student should be able to :

a) Define the control problem and give examplesb) State various types of control and give examples

c) State the main advantages of closed loop control over

open loop control and explain why closed loop control is

universally applied for technical systems with examplesd) For some common practical control systems from

common engineering domains,

1) Indicate reference and control inputs, measured andcontrolled outputs, sources of disturbance and noise

2) State main objectives, constraints, performance

parameters for the control system11

Basic Concepts of Control : Objectives



Basic Concepts of Control : Objectives

Given a closed loop practical control system, the student

should be able to :a) Identify the feedback loops and their hierarchy, if any

b) Explain the difference between Servo and Supervisory

Control

c) Give examples of industrial control systemsd) Describe the different levels of a hierarchical control

system and their typical functions, with examples

12/37



Introduction and significance of Control Systems

Closed and open loop control A typical feedback control loop

Signals in a control loop : Set point, Control , Disturbance,

Feedback, Feedforward, Output, Noise

Component models and their uncertainties

Typical performance issues and implementation

challenges of practical control systems.

Servo and supervisory control

Multi-level (Levels (0-3)) hierarchical structure of a

practical control application with examples

Basic Concepts : Overview

13/37


14/37



Models and Response : Objectives

a) Sketch Polar/Bode/Nichols plots (magnitude and phase)

for systems with real and complex pole-zeros.

b) Also to estimate a transfer function from a Bode plot

c) Estimate f requency domain properties like margin

bandwidth etc.

d) Relate system frequency domain properties to timedomain response

Control design is very often done in frequency domain

Therefore one has to develop appreciation of system

properties in terms of gain and phase plots in

One also needs to know how frequency responses can

be obtained experimentally and model buil t from that

15/37



Models and Response : Objectives

a) Draw block diagram of the system. Identify inputs,

outputs, state variables of each component block

indicating assumptions involved.

b) Derive linear i/o models for individual blocks. Use

approximations wherever needed

c) From a block diagram representation of a system, derivetransfer functions between signals using block diagram

algebra/Masons gain formula.

For complex systems involving subsystems modelling

has to be done physical block by block

Often the models need to be simplified through steps

such as linearization, low frequency approximation etc.

16/37



Models and Response : Objectivesa) Obtain linear state space models of components and from

these obtain linear state space models of the overall

closed loop system.b) Obtain alternate canonical state space models,

eigenvalues and eigenvectors

c) Relate state variable models with i/o models

d) Obtain time response of state space models to arbitraryfinite inputs with intial conditions.

Physics-based modelling naturally involve state variables

Canonical state space models are easy to develop andanalyse from input-output models

Eigenvalues/vectors help compute transient response

State space models are useful for studying internal

system behaviours17/37



Brief review of differential equations, Laplace transform and

state variable models. Pole-zero, degree, order, type. Superposition. Zero state and zero input response.

Response to standard inputs with arbitrary initial conditions.

Convolution. Steady state and transient response specifications

Numerical computation of response for arbitrary inputs.

Numerical accuracy and stability.

Models and Response : Overview

18/37


19/37



Models and Response: Overview

State Space models: Interrelations with input-output

models, similarity transformation, canonical forms.Eigenvalues and eigenvectors, Modes of a system. System

response to arbitrary inputs using state space model.

Modeling Approximations of Practical Systems:Linearization, Dominant pole modelling, Switched and PWM

systems, Time delay systems

20/37



System Analysis: Objectives

Given the system model, the student should be able to:

1) Define and explain the concepts of equilibrium point and

stability.2) Distinguish between asymptotic/uniform/exponential

local/global stabil ity. Define limit cycles.

3) Describe stability conditions for LTI systems. Internal

stability

4) Explain Routh criterion of stability for LTI systems

Stability is fundamental concept. But many aspects of

it are missing in LTI systems. A simple generalexposit ion is therefore to be presented first.

Routh criterion is a standard and useful topic for many

design approaches

21/37

S t A l i Obj ti


22/37


System Analysis : Objectives

1) State and explain Nyquist criterion of Stability using polar,

Bode and Nichols plots

2) Check for closed loop stability using these criteria.

3) Compute indices of relative stability such gain/phase/disc

margins,

4) Compute stability margins for multi-loop systems and inpresence time delays in the loop

Meeting frequency domain relative stability

specifications is a common requirement for control

design.

Many control systems are multi-loop and involve time

delays

22/37

S t A l i Obj ti


23/37


System Analysis : Objectives

1) Compute root loci for variation in controller gain or some

other parameter.2) Effects of addition of pole and zeros at selected locations

on the root loci

3) Check for closed loop system specifications with root loci

using dominant pole approximations where applicable

When system models are available, root loci provide

easy ways to choose compensator structure and

parameters particularly under dominant poleapproximations.

23/37

S t A l i Obj ti


24/37


System Analysis: Objectives

1) Define controllability, give examples of controllable and

uncontrollable systems, check for controllability.

2) Relate uncontrollable modes with pole-zero cancellations

in transfer functions.

3) Similarly for observability.

Important for understanding the feasibility of reachingchosen states, avoiding internal instability, estimating

state vectors from a given set of measurements

Planning for sensors and actuators

Understanding the internal realization of a system witha given transfer function

Recognising areasonable specif ication from one that is

not

24/37

S t A l i O i


25/37


Concept of stability, equilibrium points, types of stability

(local/global, asymptotic/uniform/exponential) with

examples.

LTI system stability

Routh criterion of stabili ty and its application to determine

ranges of controller parameters Nyquist criterion of stability

Achieving stability margins using Nyquist, Bode and

Nichols plot. Stability margins for multi-loop systems. Relation with

transient response.

System Analysis: Overview

25/37

S t A l i O i


26/37


Stability, controllability, observability of state variable

models. Realizations for pole-zero cancellations in transfer

functions

System Analysis: Overview

26/37


27/37


28/37

O i C t l D i


29/37


Overview: Control Design

Performance specifications, steady state, transient,

frequency domain, stability margins, sensitivity and

complementary sensitivity. Specifications for typical

applications

Internal Model Principle for asymptotic tracking and

disturbance rejection Model matching and pole placement using output

feedback

Root locus design with time domain specifications

Loop shaping: Lead/Lag compensation with frequencydomain specifications

PID control tuning.

29/37


30/37

Objectives : Implementation


31/37


Objectives : Implementation

The student should be able to :

1) List the set of components to implement a control system

for common practical plants2) Choose a sampling rate of signals. Discretize the

controller

3) Implement the digital controller including input-out

interfacing and programming

4) Assess the effect of the computational delay and

numerical approximation error of the digital

implementation Critical to understand this for implementation of

control

31/37

Overview: Control ler Implementation


32/37


Overview: Control ler Implementation

Sampling of signals, Slow and fast sampling effects,

Discretization of continuous time dynamic models

Numerical issues and Computational delay

Digital implementation: Digital processor, Data acquisition,

Programming, tools, software validation

MIL/SIL/PIL/HIL Testing

32/37

Lecture


33/37


Lecture

Approximately 20 mins of instructional discussions

including

Objectives

Introduction, motivation, significance

Scope

Presentation structuring and highlights

Evaluation

Approximately 50 minutes of class room lecture including

Theory, examples, experience sharing, application facts,references etc.

Approximately 20 minutes of Q&A

33/37

Tutorial


34/37


Tutorial

Practice Questions from standard sources for

Skill buildingEvaluation

To be referred to

Conceptual numericals to

Support theory

Demonstrate practical application

Assignment

To beprovided earlier day

To be discussed during Tutorial

34/37

Laboratory


35/37


Laboratory

Optional but recommended to

provide an exposure to practice of control systems

design and implementation be able to illustrate essential part of the course with

simple inexpensive equipment

experience problems not thoroughly dealt with in the

course such as nonlinearities

In self or team learning modes gain hands-on experience to

innovate on resource limitations

select components, instruments interpret technical literature

plan experiments

document results and draw inferences

35/37

Morals of the Story


36/37


What you feedback is what you control

When you cannot actuate you cannot controlWhat you can measure/estimate you can compensate for

Models are always approximate

Model accuracy in the control bandwidth is critical

Stabil ity is barely basic performance

Instabili ty decides limiting performance

One cannot reduce tracking errors in all frequency bands

One cannot reject disturbances in the control bandwidthLinear Control can work for Nonlinear Plants

SISO control can work for MIMO plants

Morals of the Story


37/37

Thanks for your attention.

Any feedback ?

t10kt mw sm lesson 1 course plan

Documents