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Progress Report during secondment in Prague

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1 Progress Report during secondment in Prague
Xueji Zhang / March 11, 2015 Progress Report during secondment in Prague

2 Outline Research Modeling of a clamped-clamped beam
Finite Element Method Analytical solution: standing wave equation LQR control of FE model of the beam Collocated control with root-locus method Robust control of FE model of the beam (FSC course) πΎπ‘–π‘Ÿπ‘β„Žβ„Žπ‘œπ‘“π‘“βˆ’πΏπ‘œπ‘£π‘’ plate equation derivation with Hamilton’s principle Ph.D. Training Cooperative Control of multi-agent systems (Flexible Structure Control: included in the research section) (Linear Matrix Inequality in Control: to share after finalizing)

3 A.1. Euler-Bernoulli beam: Finite Element Method

4 Bernoulli beam element

5 Strain Energy Strain energy: Then,

6 Kinetic Energy Kinetic Energy: Then,

7 Assembly and modes extraction
Characteristic Equation:

8 C-C beam mode shapes (Solved with MATLAB)
# of elements = 40; First 4 modes: Natural frequency: Mode Shapes:

9 A.2. Euler-Bernoulli beam: Partial Differential Equation (PDE) model with standing wave solution

10 Analytical solution Governing equation of motion for Bernoulli beam: Standing wave equation: Clamped-Clamped Boundary Condition:

11 Mathematical solution
With boundary condition,

12 Shape of 𝝓 𝑛 πœ™ 𝑛 π‘₯ = cos π‘˜ 𝑛 π‘₯ βˆ’ cosh π‘˜ 𝑛 π‘₯ βˆ’ cos π‘˜ 𝑛 βˆ’ cosh π‘˜ 𝑛 sin π‘˜ 𝑛 βˆ’ sinh π‘˜ 𝑛 [ sin π‘˜ 𝑛 π‘₯ βˆ’ sinh π‘˜ 𝑛 π‘₯ ]

13 B. LQR control of the beam(SPIE2015 paper)
πœ• 2 𝑀 πœ• 𝑑 2 π‘₯,𝑑 =βˆ’ πœ• 4 𝑀 πœ• 𝑑 4 π‘₯,𝑑 +𝑒 π‘₯,𝑑 , 𝑀 π‘₯,0 = 𝑀 0 π‘₯ , πœ•π‘€ πœ•π‘‘ π‘₯,0 = 𝑀 0 (π‘₯), 0<π‘₯<1, 𝑑β‰₯0. B.C. : πœ•π‘€ πœ•π‘₯ 0,𝑑 = πœ•π‘€ πœ•π‘₯ 1,𝑑 =0=𝑀 0,𝑑 =𝑀(1,𝑑)

14 LQR formulation min 𝑒(βˆ™,𝑑) 𝐽 𝑧 0 ;𝑒(βˆ™,𝑑 )= 0 ∞ (<𝑦,𝑦>+ <𝑒,ℛ𝑒>)𝑑𝑑 𝑠𝑒𝑏𝑗𝑒𝑐𝑑 π‘‘π‘œ 𝑧 βˆ™,𝑑 =π’œπ‘§ βˆ™,𝑑 +ℬ𝑒(βˆ™,𝑑) 𝑦 βˆ™,𝑑 =π’žπ‘§ βˆ™,𝑑 𝑧 βˆ™,0 = 𝑧 0 𝑧 βˆ™,𝑑 = 𝑀 βˆ™,𝑑 𝑀 βˆ™,𝑑 , π’œ= 𝑂 𝐼 βˆ’ 𝑑 4 𝑑 π‘₯ 4 0 , ℬ= 𝑂 𝐼 , π’ž=I

15 Results: Convolution Kernel π“š(𝒙,𝝃) : 𝑒 π‘₯,𝑑 =βˆ’ 0 1 π“š(𝒙,𝝃) 𝑀 πœ‰,𝑑 π‘‘πœ‰ Decentralization properties are shown in next slides

16 Numerical evaluation: π“š 𝒙,𝝃 , 𝒙= 𝟏 πŸ‘ , 𝑡=πŸ“, 𝟏𝟎, πŸπŸ“, 𝟐𝟎 π“š 𝒙,𝝃 β‰ˆ 𝒏=𝟏 𝑡 𝜢 𝒏 𝝓 𝒏 (𝒙) 𝝓 𝒏 (𝝃)
𝑒 π‘₯,𝑑 =βˆ’ 0 1 π“š(𝒙,𝝃) 𝑀 πœ‰,𝑑 π‘‘πœ‰

17 Numerical evaluation: π“š 𝒙,𝝃 , 𝒙= 𝟏 𝟐 , 𝑡=πŸ“, 𝟏𝟎, πŸπŸ“, 𝟐𝟎 π“š 𝒙,𝝃 β‰ˆ 𝒏=𝟏 𝑡 𝜢 𝒏 𝝓 𝒏 (𝒙) 𝝓 𝒏 (𝝃)
𝑒 π‘₯,𝑑 =βˆ’ 0 1 π“š(𝒙,𝝃) 𝑀 πœ‰,𝑑 π‘‘πœ‰

18 Numerical evaluation: π“š 𝒙,𝝃 , 𝒙= 𝟐 πŸ‘ , 𝑡=πŸ“, 𝟏𝟎, πŸπŸ“, 𝟐𝟎 π“š 𝒙,𝝃 β‰ˆ 𝒏=𝟏 𝑡 𝜢 𝒏 𝝓 𝒏 (𝒙) 𝝓 𝒏 (𝝃)
𝑒 π‘₯,𝑑 =βˆ’ 0 1 π“š(𝒙,𝝃) 𝑀 πœ‰,𝑑 π‘‘πœ‰

19 LQR formulation for FE model
min 𝑒(𝑑) 0 ∞ [ 𝑦 𝑑 𝑇 𝑦 𝑑 + 𝑒 𝑑 𝑇 𝑅𝑒(𝑑)]𝑑𝑑 𝑠𝑒𝑏𝑗𝑒𝑐𝑑 π‘‘π‘œ π‘₯ 𝑑 =𝐴π‘₯ 𝑑 +𝐡𝑒(𝑑) 𝑦 𝑑 =𝐢π‘₯ 𝑑 π‘₯ 0 = π‘₯ 0 . Herein π‘₯(𝑑)= 𝒒 π’Ž (𝑑) 𝒒 π’Ž (𝑑) ⟹ Static feedback: 𝑒=βˆ’ 𝑅 βˆ’1 𝐡 𝑇 𝑃π‘₯=βˆ’πΉπ‘₯

20 Extracted from 𝐹 (𝑒=βˆ’ 𝑅 βˆ’1 𝐡 𝑇 𝑃π‘₯=βˆ’πΉπ‘₯)
𝑓 1𝑧 : π‘€βŸΌπ‘“π‘œπ‘Ÿπ‘π‘’

21 Extracted from 𝐹 (𝑒=βˆ’ 𝑅 βˆ’1 𝐡 𝑇 𝑃π‘₯=βˆ’πΉπ‘₯)
𝜏 2πœƒ : πœƒ βŸΌπ‘‘π‘œπ‘Ÿπ‘žπ‘’π‘’

22 Simulations (Simulation time = 1 s)
Distributed Sensors Decentralized control

23 C. MIMO control of beam with root-locus (IEEE CDC2015 in processing)
Improve FE model (compared with model in SPIE paper) Element Nr=1000; Model Order Reduction: modal truncation up to first 20 modes Open-loop video: Open-loop.avi Vel Feedback in the middle position: OneVelFb.avi Angular Vel in the middle position: OneAngularVelFb.avi

24 C. MIMO control of beam with root-locus (IEEE CDC2015 in processing)
Improve FE model (compared with model in SPIE paper) Element Nr=1000; Model Order Reduction: modal truncation up to first 20 modes Open-loop video: OpenLoop.avi Vel Feedback in the middle position: OneVelFb.avi Angular Vel in the middle position: OneAngularVelFb.avi Technical findings: One sensor can β€˜eliminate’ at most 1 vibration mode; Placement of one single sensor depends on which modes need to damp Distributed Vel FB damp lower modes first: VelFb_every_node_rootlocus.avi Distributed Angular Vel damp higher modes first: AngularVelFb_every_node_rootlocus.avi Research ongoing: density and scalability

25 D. Robust Control of a clamped-clamped beam (FSC)
Parameter uncertainty in FE model Additive uncertainty model: 𝐺= 𝐺 0 +βˆ† π‘Š π‘Ž , 𝐺 0 nominal plant

26 Filter design

27 Performance: validation of the 15th-order controller

28 E. πΎπ‘–π‘Ÿπ‘β„Žβ„Žπ‘œπ‘“π‘“βˆ’πΏπ‘œπ‘£π‘’ plate governing equation derivation: Hamilton’s principle
Dynamics_Hamiton_Splitted.pdf

29 F. Ph.D. course: Cooperative control of multi-agent systems
5-agent integrator model: π‘₯ 𝑖 = 𝑒 𝑖 Graph topology (info flow): 𝐸= Consensus protocol: 𝑒 𝑖 = 𝑗 𝑒 𝑖𝑗 ( π‘₯ 𝑗 βˆ’ π‘₯ 𝑖 ) Laplacian matrix: 𝐿= βˆ’1 βˆ’1 0 βˆ’ βˆ’ βˆ’1 βˆ’ Global dynamics: 𝒙 =βˆ’πΏπ’™, 𝒙=[ π‘₯ 1 π‘₯ 2 π‘₯ 3 π‘₯ 4 π‘₯ 5 ] 𝑇

30 Simulink model

31 Simulation results: (average) consensus

32 Small toy-project: mass-spring-damper system synchronization

33 More advanced project (only if time permitting)
Parallel parking for 5 mobile cars: nonlinear dynamics involved I/O feedback linearization Leader-following stabilization problem

34 G. Other literature study
Bassam Bamieh's framework: Distributed Control of Spatially Invariant Systems. IEEE Transactions on Automatic Control, Vol. 47, pp , 2002. Raffaello D'Andrea's framework: Distributed Control Design for Spatially Interconnected Systems. IEEE Transactions on Automatic Control, Vol. 48, pp , 2003. Simple control law A. Positive position feedback (PPF) B. Direct velocity feedback C. Acceleration feedback D. Integral force feedback E. Piezoelectric Shunt damping

35 H. Directions?


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