CONTROL SYSTEMS - Ankara Üniversitesi
Transcript of CONTROL SYSTEMS - Ankara Üniversitesi
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CONTROL SYSTEMS
Doç. Dr. Murat Efe
WEEK 3
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This week’s agenda
2/17
Linear Differential EquationsObtaining Transfer FunctionsBlock DiagramsAn Introduction to Stability forTransfer FunctionsConcept of Feedback and Closed LoopBasic Control Actions, P-I-D Effects
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P-2 Linear Differential Equations
Why do we need differential equations?
To characterize the dynamicsTo obtain a model (which may not be unique)To be able to analyze the behaviorFinally, to be able to design a controller
Model may depend on your perspective and the goals of the designSimplicity versus Accuracy tradeoff arises
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When is a dynamics linear?
SYSTEMu1(t) y1(t)
SYSTEMu2(t) y2(t)
SYSTEMu1(t)+ u2(t) y1(t)+y2(t)
The system is linear if the principle ofsuperposition applies
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Linear Time Invariant (LTI) SystemsLinear Time Varying (LTV) Systems
A differential equation is linear if the coefficientsare constants or functions only of the independentvariable (e.g. time below).
LTI
LTV
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Nonlinear Systems
A system is nonlinear if the principle ofsuperposition does not apply
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A More Realistic Example - 2DOF Robot
Dynamics is characterized by
where
ControlInputs
u
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Linearization of z=f (x)
Consider z=f (x) is the system(x0,z0) is the operating point
Perform Taylor series expansion around theoperating point
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Only if these terms are negligibly small!
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Linearization of z=f (x,y)
Consider z=f (x,y) is the system(x0,y0,z0) is the operating point
Perform Taylor series expansion around theoperating point
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Only if these terms are negligibly small!
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P-2 Obtaining Transfer Functions
Consider the system, whose dynamics is given bythe following differential equation
where, x is the output, u is the input
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Assume all initial conditions are zero and take theLaplace transform. Remember
Real Differentiation
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We get
Transfer function is G(s)
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Note that while studying with transferfunctions all initial conditions are assumedto be zero
What does a transfer function tell us?
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TF states the relation between input and outputTF is a property of system, no matter what the input isTF does not tell anything about the structure of the systemTF enables us to understand the behavior of the systemTF can be found experimentally by studying the response of the system for various inputsTF is the Laplace transform of g(t), the impulse response of the system
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Transfer function (TF)
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Transfer function (TF)
Above TF, i.e. G(s), is nth orderWe assume that nm
If a0=1, the denominator polynomial is said to be
monicIf b0=1, the numerator polynomial is said to be
monic
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P-2 Block Diagrams
Tools we will mainly use (Matlab-Simulink)
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P-2 An Introduction to Stability forTransfer Functions
Consider
Rewrite this as
s = zi for i=1,2,…,m are
the zeros of the system
s = pi for i=1,2,…,n are
the poles of the system
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If the real parts of the poles are negative,then the transfer function is stable
Re( pi)<0 Re(pi)>0 TF Stable
Stability in terms of TF poles
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What is the meaning of this?Poles with zero imaginary parts
x
Im
Re
s-plane
t
h(t)
x
Im
Re
s-plane
t
h(t)
Re( pi)<0
Re( pi)>0
Stable
Unstable
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What is the meaning of this?Poles with nonzero imaginary parts
x
Im
Re
s-plane
t
h(t)
x
Im
Re
s-plane
t
h(t)
Re( pi)<0
Re( pi)>0
Stable
Unstable
x
x
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What is the meaning of this?Poles on the imaginary axis
x
Im
Re
s-plane
t
h(t)
x
Im
Re
s-plane
t
h(t)
Re( pi)=0
Re( pi)=0x
Neither stable nor unstable
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A TF is said to be stable if all the roots ofthe denominator have negative real parts
Poles determine the stability of a TF
Zeros may be stable or unstable as well,but the stability of the TF is determinedby the poles
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P-2 Concept of Feedback and Closed Loop
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What are the advantages of feedback?
Superposition!
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Effect of disturbance is suppressed considerably
Variations on P(s) and C(s) do not affect the closed loop TF. Think about the case when F(s)=1