linear_systems_2009_11_02_01

linear_systems_2009_11_02_01 - 12 1 Linear Systems with...

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Unformatted text preview: 12 - 1 Linear Systems with Inputs and Outputs S. Lall, Stanford 2009.11.02.01 12. Linear Systems with Inputs and Outputs • Systems with inputs and outputs • Solution • Impulse and step matrices • Mass-spring example • Discretization of continuous-time linear systems • Example: forces applied to a mass • Example: computing the state • Solution of discrete-time LDS • Convolution and impulse response • Block Toeplitz matrices • Example: controlling a hovercraft • Comments on controlling a hovercraft 12 - 2 Linear Systems with Inputs and Outputs S. Lall, Stanford 2009.11.02.01 The Key Points of This Section • if we have a continuous-time linear dynamical system ˙ x ( t ) = Ax ( t ) + Bu ( t ) y ( t ) = Cx ( t ) + Du ( t ) we can discretize it to make a discrete-time LDS in the form x ( t + 1) = Ax ( t ) + Bu ( t ) y ( t ) = Cx ( t ) + Du ( t ) which gives the behavior at sample times • discrete-time systems are just like continuous-time ones; • they have a modal decomposition • stability is determined by eigenvalues of A ; but we need | λ | < 1 not Re( λ ) < • they map u to y via convolution • for control and estimation, we can form least-squares problems using the block Toeplitz matrix which maps u to y 12 - 3 Linear Systems with Inputs and Outputs S. Lall, Stanford 2009.11.02.01 Inputs & outputs Continuous-time time-invariant LDS has form ˙ x = Ax + Bu y = Cx + Du • Ax is called the drift term (of ˙ x ) • Bu is called the input term (of ˙ x ) picture, with B ∈ R 2 × 1 : x ( t ) Ax ( t ) ˙ x ( t ) (with u ( t ) = 1 ) ˙ x ( t ) (with u ( t ) =- 1 . 5 ) B 12 - 4 Linear Systems with Inputs and Outputs S. Lall, Stanford 2009.11.02.01 Interpretations ˙ x = Ax + Bu y = Cx + Du write ˙ x = Ax + b 1 u 1 + ··· + b m u m , where B = [ b 1 ··· b m ] • state derivative is sum of autonomous term ( Ax ) and one term per input ( b i u i ) • each input u i gives another degree of freedom for ˙ x (assuming columns of B inde- pendent) write ˙ x = Ax + Bu as ˙ x i = ˜ a T i x + ˜ b T i u , where ˜ a T i , ˜ b T i are the rows of A , B • i th state derivative is linear function of state x and input u 12 - 5 Linear Systems with Inputs and Outputs S. Lall, Stanford 2009.11.02.01 Solution The solution is x ( t ) = e tA x (0) + integraldisplay t e ( t- τ ) A Bu ( τ ) dτ y ( t ) = Ce tA x (0) + integraldisplay t Ce ( t- τ ) A Bu ( τ ) dτ + Du ( t ) • check via differentiation • at time t , current state x ( t ) and output y ( t ) depend on past input ( u ( τ ) for τ ≤ t ) • that is, mapping from input to state and output is causal (with fixed initial state) 12 - 6 Linear Systems with Inputs and Outputs S. Lall, Stanford 2009.11.02.01 Impulse matrix The impulse matrix is h ( t ) = Ce tA B + Dδ ( t ) with x (0) = 0 , y = h * u , i.e. , y i ( t ) = m summationdisplay j =1 integraldisplay t h ij ( t- τ ) u j ( τ ) dτ interpretations: • h ij ( t ) is impulse response from j th input to i...
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This note was uploaded on 08/23/2010 for the course EE 263 taught by Professor Boyd,s during the Fall '08 term at Stanford.

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linear_systems_2009_11_02_01 - 12 1 Linear Systems with...

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