Tutorial 11 SS modelling 1

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Oct 30, 2023

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Tutorial 11: state-space modelling State-space models are used for MIMO systems Multiple input multiple output Particularly useful for modelling systems with initial conditions Also useful for computer analysis as is matrix based State-space model comprises of four matrices A , B , C , D A represents system characteristics B represents system input C represents system output D represents initial conditions Order of system dictates number of state variable & equations… 2 nd order = two state variables & two state equations etc State variables are assigned by the engineer Show the link between current state & next state State-space model is a matrix version of system equations Mathematically identical Develop the state-space model for the following system; assume no initial conditions 30 𝑠𝑠 2 + 6𝑠𝑠 + 30 What do we know? System shown in Laplace (s-domain) Must map back to time domain System is 2 nd order Two state variables Two state equations No initial conditions but must include D D =[0] Step 1: map to time domain 𝑠𝑠 2 𝑌𝑌 ( 𝑠𝑠 ) 𝑑𝑑 2 𝑦𝑦 𝑑𝑑𝑡𝑡 2 ̈𝑦𝑦 𝑠𝑠𝑌𝑌 ( 𝑠𝑠 ) 𝑑𝑑𝑦𝑦 𝑑𝑑𝑡𝑡 ̇𝑦𝑦 𝑌𝑌 𝑠𝑠 → 𝑦𝑦 𝑠𝑠 2 𝑌𝑌 𝑠𝑠 + 6𝑠𝑠𝑌𝑌 𝑠𝑠 + 30𝑌𝑌 𝑠𝑠 = 30𝑈𝑈 ( 𝑠𝑠 ) ̈𝑦𝑦 𝑡𝑡 + 6 ̇𝑦𝑦 𝑡𝑡 + 30𝑦𝑦 𝑡𝑡 = 30𝑢𝑢 ( 𝑡𝑡 )
Step 2: create two state variables 𝑥𝑥 1 𝑎𝑎𝑎𝑎𝑑𝑑 𝑥𝑥 2 Step 3 : Assign state variables In this example… ̈𝑦𝑦 𝑡𝑡 + 6 ̇𝑦𝑦 𝑡𝑡 + 30𝑦𝑦 𝑡𝑡 = 30𝑢𝑢 ( 𝑡𝑡 ) we can choose from ̈𝑦𝑦 , ̇𝑦𝑦 , 𝑦𝑦 Let us assign… 𝑥𝑥 1 ( 𝑡𝑡 ) = 𝑦𝑦 ( 𝑡𝑡 ), 𝑥𝑥 2 ( 𝑡𝑡 ) = ̇𝑦𝑦 (t) Step 4 : assign next states of 𝑥𝑥 1 𝑎𝑎𝑎𝑎𝑑𝑑𝑥𝑥 2 𝐼𝐼𝐼𝐼 𝑐𝑐𝑢𝑢𝑐𝑐𝑐𝑐𝑐𝑐𝑎𝑎𝑡𝑡 𝑠𝑠𝑡𝑡𝑎𝑎𝑡𝑡𝑐𝑐 𝑖𝑖𝑠𝑠 𝑥𝑥 1 𝑡𝑡 = 𝑦𝑦 𝑡𝑡 , 𝑡𝑡𝑡𝑐𝑐 𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏 𝑠𝑠𝑡𝑡𝑎𝑎𝑡𝑡𝑐𝑐 𝑖𝑖𝑠𝑠 ̇ 𝑥𝑥 1 ( 𝑡𝑡 ) = ̇𝑦𝑦 ( 𝑡𝑡 ) This is the current state of the system 𝐼𝐼𝐼𝐼 𝑐𝑐𝑢𝑢𝑐𝑐𝑐𝑐𝑐𝑐𝑎𝑎𝑡𝑡 𝑠𝑠𝑡𝑡𝑎𝑎𝑡𝑡𝑐𝑐 𝑖𝑖𝑠𝑠 𝑥𝑥 2 ( 𝑡𝑡 ) = ̇𝑦𝑦 𝑡𝑡 , 𝑡𝑡𝑡𝑐𝑐 𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏 𝑠𝑠𝑡𝑡𝑎𝑎𝑡𝑡𝑐𝑐 𝑖𝑖𝑠𝑠 ̇ 𝑥𝑥 2 ( 𝑡𝑡 ) = ̈𝑦𝑦 ( 𝑡𝑡 ) ̇ 𝑥𝑥 1 ( 𝑡𝑡 ) = ̇𝑦𝑦 ( 𝑡𝑡 ) ̇ 𝑥𝑥 2 ( 𝑡𝑡 ) = ̈𝑦𝑦 ( 𝑡𝑡 ) This is the next state of the system Step 5 : Establish the two state equations State equation 1: ̇ 𝑥𝑥 1 ( 𝑡𝑡 ) = ̇𝑦𝑦 ( 𝑡𝑡 ) 𝑡𝑜𝑜𝑜𝑜𝑐𝑐𝑜𝑜𝑐𝑐𝑐𝑐 , 𝑎𝑎𝑠𝑠 𝑥𝑥 2 ( 𝑡𝑡 ) = ̇𝑦𝑦 ̇ 𝒏𝒏 𝟏𝟏 ( 𝒏𝒏 ) = 𝒏𝒏 𝟐𝟐 ( 𝒏𝒏 ) State equation 2: Make ̈𝑦𝑦 ( 𝑡𝑡 ) the subject ̈𝑦𝑦 𝑡𝑡 = 6 ̇𝑦𝑦 𝑡𝑡 − 30𝑦𝑦 𝑡𝑡 + 30𝑢𝑢 ( 𝑡𝑡 ) (don’t forget ̇ 𝑥𝑥 2 𝑡𝑡 ̈𝑦𝑦 𝑡𝑡 & 𝑥𝑥 2 ( 𝑡𝑡 ) ̇𝑦𝑦 (t) ) ̇ 𝑥𝑥 2 ( 𝑡𝑡 ) = 6 𝑥𝑥 2 ( 𝑡𝑡 ) 30 𝑥𝑥 1 ( 𝑡𝑡 ) + 30𝑢𝑢 ( 𝑡𝑡 ) Reorder ̇ 𝒏𝒏 𝟐𝟐 ( 𝒏𝒏 ) = −𝟑𝟑𝟑𝟑𝒏𝒏 𝟏𝟏 ( 𝒏𝒏 ) − 𝟔𝟔𝒏𝒏 𝟐𝟐 ( 𝒏𝒏 ) + 𝟑𝟑𝟑𝟑𝟑𝟑 ( 𝒏𝒏 ) We need to establish the equations for the next state, i.e., the equations for ̇ 𝑥𝑥 1 𝑡𝑡 & ̇𝑥𝑥 2 ( 𝑡𝑡 )
Step 6 : Establish state-space model We need to express our two state equations in a matrix format Step 6A : Construct matrix A – system characteristic ̇ 𝑥𝑥 1 ̇ 𝑥𝑥 2 = 0 1 30 6 . 𝑥𝑥 1 𝑥𝑥 2 ( 𝑡𝑡 ) If we multiply out we get ̇ 𝑥𝑥 1 = 0 ∗ 𝑥𝑥 1 𝑡𝑡 + (1 ∗ 𝑥𝑥 2 𝑡𝑡 ) = 𝒏𝒏 𝟐𝟐 𝒏𝒏 ̇ 𝑥𝑥 2 = 30 ∗ 𝑥𝑥 1 𝑡𝑡 + ( 6 ∗ 𝑥𝑥 2 𝑡𝑡 ) = − 𝟑𝟑𝟑𝟑𝒏𝒏 𝟏𝟏 𝒏𝒏 − 𝟔𝟔𝒏𝒏 𝟐𝟐 𝒏𝒏 Step 6B : Add matrix B – system input ( 30𝑢𝑢 ( 𝑡𝑡 ) ) ̇ 𝑥𝑥 1 ̇ 𝑥𝑥 2 = 0 1 30 6 . 𝑥𝑥 1 𝑥𝑥 2 𝑡𝑡 + 0 30 𝑢𝑢 ( 𝑡𝑡 ) Performing addition we get ̇ 𝑥𝑥 1 = 𝑥𝑥 2 𝑡𝑡 + 𝟑𝟑 ̇ 𝑥𝑥 2 = 30 𝑥𝑥 1 𝑡𝑡 6 𝑥𝑥 2 𝑡𝑡 + 𝟑𝟑𝟑𝟑𝟑𝟑 ( 𝒏𝒏 ) Step 6C : Construct matrix C – system output ( 𝑥𝑥 1 ( 𝑡𝑡 ) = 𝑦𝑦 ( 𝑡𝑡 )) y t = 1 0 . 𝑥𝑥 1 𝑥𝑥 2 ( 𝑡𝑡 ) If we multiply out we get 𝑦𝑦 𝑡𝑡 = 1 ∗ 𝑥𝑥 1 𝑡𝑡 + 0 ∗ 𝑥𝑥 2 𝑡𝑡 ∴ 𝒚𝒚 𝒏𝒏 = 𝒏𝒏 𝟏𝟏 𝒏𝒏 Step 6D : Construct matrix D – initial conditions (none in this example) 𝐷𝐷 = [0] ̇ 𝑥𝑥 1 ̇ 𝑥𝑥 2 = 0 1 30 6 . 𝑥𝑥 1 𝑥𝑥 2 𝑡𝑡 + 0 30 𝑢𝑢 ( 𝑡𝑡 ) y t = 1 0 . 𝑥𝑥 1 𝑥𝑥 2 ( 𝑡𝑡 ) 𝐷𝐷 = [0] A B C D
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