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              Modeling in the Time
                    Domain
•   How to find a mathematical model, called a state-space
    representation, for a linear, time-invariant system

•   How to convert between transfer function and state-space
    models

•   How to linearize a state-space representation




                                                    Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                      Copyright © 2004 by John Wiley & Sons. All rights reserved.
2

                           Introduction

Classical (frequency-domain) technique:
•   Modeling of systems using linear, time-invariant differential equations
    and subsequent transfer functions


State-space (time-domain) technique:
•   More powerful tool than classical techniques
•   Can be used to represent nonlinear systems, systems with nonzero
    initial conditions, time-varying systems, multiple-input multiple-
    output systems




                                                          Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                            Copyright © 2004 by John Wiley & Sons. All rights reserved.
3

                  State-Space Approach
1.   We select a particular subset of all possible system variables and call the
     variables in this subset state variables.

2.   For an nth-order system, we write n simultaneous, first-order differential
     equations in terms of the state variables. We call this system of simultaneous
     differential equations state equations.

3.   If we know the initial condition of all of the state variables at t0 as well as the
     system input for t≥t0, we can solve the simultaneous differential equations for
     the state variables for t≥t0.

4.   We algebraically combine the state variables with the system's input and find
     all of the other system variables for t≥t0. We call this algebraic equation the
     output equation.

5.   We consider the state equations and the output equations a viable representation
     of the system. We call this representation of the system a state-space
     representation.


                                                                   Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                                     Copyright © 2004 by John Wiley & Sons. All rights reserved.
4
Example:




We select i(t) and q(t), as the two state variables.




 We transform this equation into 2 first order equations in terms of i(t) and q(t)




                                                            Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                              Copyright © 2004 by John Wiley & Sons. All rights reserved.
5


From these two state variables, we can solve for all other network variables.

                                                   … output equation




                                                      state-space representation.




  !!! State variables must be linearly independent which means that no
  state variable can be chosen if it can be expressed as a linear combination
  of the other state variables.



                                                           Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                             Copyright © 2004 by John Wiley & Sons. All rights reserved.
6

The state equations




can be written in matrix form as

                          where




 The output equation               can be written in matrix form as




            where



                                          Control Systems Engineering, Fourth Edition by Norman S. Nise
                                            Copyright © 2004 by John Wiley & Sons. All rights reserved.
7

    The General State-Space Representation

A system is represented in state space by the following equations:
                        •
                       x = Ax + Bu
                       y = Cx + Du




                                                            Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                              Copyright © 2004 by John Wiley & Sons. All rights reserved.
8




Example of a second order system:

                     •
                     x = Ax + Bu
                     y = Cx + Du




                                    Control Systems Engineering, Fourth Edition by Norman S. Nise
                                      Copyright © 2004 by John Wiley & Sons. All rights reserved.
9

      Applying the State-Space Representation

State-vector selection:

 1.   A minimum number of state variables must be selected as components
      of the state vector. This minimum number of state variables is sufficient
      to describe completely the state of the system.

      (Note: Typically, the minimum number equals the order of the
      differential equation describing the system or to the number of
      independent energy-storage elements in the system)

 2.   The components of the state vector must be linearly independent.

      (Note: Variables related by derivative are linearly independent)




                                                            Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                              Copyright © 2004 by John Wiley & Sons. All rights reserved.
10

Problem Given the electrical network, find a state-space representation
if the output is the current through the resistor.




 Solution
 Select the state variables by writing the derivative equation for all energy-
 storage elements, that is, the inductor and the capacitor




  next step is to express ic and vL as linear combinations of the state variables
  vc and iL, and the input, v(t).



                                                            Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                              Copyright © 2004 by John Wiley & Sons. All rights reserved.
11

                                              State variables




After substitution we obtain:




                                Control Systems Engineering, Fourth Edition by Norman S. Nise
                                  Copyright © 2004 by John Wiley & Sons. All rights reserved.
12
The output equation:



 Final state-space representation:




                                     Control Systems Engineering, Fourth Edition by Norman S. Nise
                                       Copyright © 2004 by John Wiley & Sons. All rights reserved.
13

Problem Find the state equations for the translational mechanical system




Solution
•    It is more convenient when working with mechanical systems to obtain the
     state equations directly from the equations of motion rather than from the
     energy-storage elements.

•    State variables will be the position and velocity of each point of linearly
     independent motion.




                                                             Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                               Copyright © 2004 by John Wiley & Sons. All rights reserved.
14




We select x1, x2, v1, and v2 as state variables
                      dx1 / dt = v1
                      dx2 / dt = v2
                      dv1 / dt = d 2 x1 / dt 2
                      dv2 / dt = d 2 x2 / dt 2

State equations:




                                                  Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                    Copyright © 2004 by John Wiley & Sons. All rights reserved.
15




Control Systems Engineering, Fourth Edition by Norman S. Nise
  Copyright © 2004 by John Wiley & Sons. All rights reserved.
16

    Converting a Transfer Function to State Space
•     We will show how to convert a transfer function to a state-space representation

•     First. we select a set of state variables, called phase variables, where each
      subsequent state variable is defined to be the derivative of the previous state
      variable.

    Consider:

                - we choose output y(t) and its (n-1) derivatives as the state variables




                                                                    Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                                      Copyright © 2004 by John Wiley & Sons. All rights reserved.
17




Control Systems Engineering, Fourth Edition by Norman S. Nise
  Copyright © 2004 by John Wiley & Sons. All rights reserved.
18

Converting a transfer function with constant term in numerator




                                                      Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                        Copyright © 2004 by John Wiley & Sons. All rights reserved.
19
Converting a transfer function with polynomial in numerator




                                                       Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                         Copyright © 2004 by John Wiley & Sons. All rights reserved.
20
Example: Converting a transfer function with polynomial in numerator




                                                      Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                        Copyright © 2004 by John Wiley & Sons. All rights reserved.
21




Control Systems Engineering, Fourth Edition by Norman S. Nise
  Copyright © 2004 by John Wiley & Sons. All rights reserved.
22

   Converting from State Space to a Transfer
                   Function



Taking the Laplace transform of   :




Taking the Laplace transform      :




                                      Control Systems Engineering, Fourth Edition by Norman S. Nise
                                        Copyright © 2004 by John Wiley & Sons. All rights reserved.
23

                        Linearization


•   state –space representation can be used to represent systems with
    nonlinearities


•   state –space representation can be linearized for small perturbations
    about an equilibrium point




                                                            Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                              Copyright © 2004 by John Wiley & Sons. All rights reserved.
24
Example




          Let




                Control Systems Engineering, Fourth Edition by Norman S. Nise
                  Copyright © 2004 by John Wiley & Sons. All rights reserved.
25
In order to find the transfer function we must linearize the nonlinear state-space
representation




 Let equilibrium point   x1 = 0, x2 = 0




                                                                Control Systems Engineering, Fourth Edition by Norman S. Nise
                                                                  Copyright © 2004 by John Wiley & Sons. All rights reserved.

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03 elec3114

  • 1. 1 Modeling in the Time Domain • How to find a mathematical model, called a state-space representation, for a linear, time-invariant system • How to convert between transfer function and state-space models • How to linearize a state-space representation Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 2. 2 Introduction Classical (frequency-domain) technique: • Modeling of systems using linear, time-invariant differential equations and subsequent transfer functions State-space (time-domain) technique: • More powerful tool than classical techniques • Can be used to represent nonlinear systems, systems with nonzero initial conditions, time-varying systems, multiple-input multiple- output systems Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 3. 3 State-Space Approach 1. We select a particular subset of all possible system variables and call the variables in this subset state variables. 2. For an nth-order system, we write n simultaneous, first-order differential equations in terms of the state variables. We call this system of simultaneous differential equations state equations. 3. If we know the initial condition of all of the state variables at t0 as well as the system input for t≥t0, we can solve the simultaneous differential equations for the state variables for t≥t0. 4. We algebraically combine the state variables with the system's input and find all of the other system variables for t≥t0. We call this algebraic equation the output equation. 5. We consider the state equations and the output equations a viable representation of the system. We call this representation of the system a state-space representation. Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 4. 4 Example: We select i(t) and q(t), as the two state variables. We transform this equation into 2 first order equations in terms of i(t) and q(t) Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 5. 5 From these two state variables, we can solve for all other network variables. … output equation state-space representation. !!! State variables must be linearly independent which means that no state variable can be chosen if it can be expressed as a linear combination of the other state variables. Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 6. 6 The state equations can be written in matrix form as where The output equation can be written in matrix form as where Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 7. 7 The General State-Space Representation A system is represented in state space by the following equations: • x = Ax + Bu y = Cx + Du Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 8. 8 Example of a second order system: • x = Ax + Bu y = Cx + Du Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 9. 9 Applying the State-Space Representation State-vector selection: 1. A minimum number of state variables must be selected as components of the state vector. This minimum number of state variables is sufficient to describe completely the state of the system. (Note: Typically, the minimum number equals the order of the differential equation describing the system or to the number of independent energy-storage elements in the system) 2. The components of the state vector must be linearly independent. (Note: Variables related by derivative are linearly independent) Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 10. 10 Problem Given the electrical network, find a state-space representation if the output is the current through the resistor. Solution Select the state variables by writing the derivative equation for all energy- storage elements, that is, the inductor and the capacitor next step is to express ic and vL as linear combinations of the state variables vc and iL, and the input, v(t). Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 11. 11 State variables After substitution we obtain: Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 12. 12 The output equation: Final state-space representation: Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 13. 13 Problem Find the state equations for the translational mechanical system Solution • It is more convenient when working with mechanical systems to obtain the state equations directly from the equations of motion rather than from the energy-storage elements. • State variables will be the position and velocity of each point of linearly independent motion. Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 14. 14 We select x1, x2, v1, and v2 as state variables dx1 / dt = v1 dx2 / dt = v2 dv1 / dt = d 2 x1 / dt 2 dv2 / dt = d 2 x2 / dt 2 State equations: Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 15. 15 Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 16. 16 Converting a Transfer Function to State Space • We will show how to convert a transfer function to a state-space representation • First. we select a set of state variables, called phase variables, where each subsequent state variable is defined to be the derivative of the previous state variable. Consider: - we choose output y(t) and its (n-1) derivatives as the state variables Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 17. 17 Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 18. 18 Converting a transfer function with constant term in numerator Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 19. 19 Converting a transfer function with polynomial in numerator Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 20. 20 Example: Converting a transfer function with polynomial in numerator Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 21. 21 Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 22. 22 Converting from State Space to a Transfer Function Taking the Laplace transform of : Taking the Laplace transform : Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 23. 23 Linearization • state –space representation can be used to represent systems with nonlinearities • state –space representation can be linearized for small perturbations about an equilibrium point Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 24. 24 Example Let Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
  • 25. 25 In order to find the transfer function we must linearize the nonlinear state-space representation Let equilibrium point x1 = 0, x2 = 0 Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.