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Unformatted text preview: 6.241 Dynamic Systems and Control Lecture 9: Transfer Functions Readings: DDV, Chapters 10, 11, 12 Emilio Frazzoli Aeronautics and Astronautics Massachusetts Institute of Technology March 2, 2011 E. Frazzoli (MIT) Lecture 9: Transfer Functions Mar 2, 2011 1 / 13 Asymptotic Stability (Preview) We have seen that the unforced state response ( u = 0) of a LTI system is easily computed using the A matrix in the statespace model: x [ k ] = A k x [0] , or x ( t ) = e At x (0) . A system is asymptotically stable if lim t + x ( t ) = 0, for all x . Assume A is diagonalizable, i.e., V 1 AV = , and let r = Vx be the vector of model coordinates. Then, r i [ k ] = k i r i [0] , or r i ( t ) = e i t r i (0) , i = 1 ,..., n . Clearly, for the system to be asymptotically stable,  i  < 1 (DT) or Re ( i ) < (CT) for all i = 1 ,..., n . It turns out that this condition extends to the general (nondiagonalizable) case. More on this later in the course. E. Frazzoli (MIT) Lecture 9: Transfer Functions Mar 2, 2011 2 / 13 (Timedomain) Response of LTI systems summary Based on the discussion in previous lectures, the solution of initial value problems (i.e., the response) for LTI systems can be written in the form: k 1 y [ k ] = CA k x [0] + C A k i 1 Bu [ i ] + Du [ t ] i =0 or t y ( t ) = C exp( At ) x (0) + C exp( A ( t )) Bu ( ) d + Du ( t ) . However, the convolution integral (CT) and the sum in the DT equation are hard to interpret, and do not offer much insight. In order to gain a better understanding, we will study the response to elementary inputs of a form that is particularly easy to analyze: the output has the same form as the input....
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This note was uploaded on 01/12/2012 for the course ECE 6.241j taught by Professor Prof.emiliofrazzoli during the Spring '11 term at MIT.
 Spring '11
 Prof.EmilioFrazzoli

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