| Topic 1 |
Introduction
Motivation
Basic linear system response
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| Topic 2 |
Basic root locus
Basic aircraft control concepts
Basic control approaches
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| Topic 3 |
Frequency response methods
Analysis
Synthesis
Performance
Stability
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| Topic 4 |
Stability in the frequency domain
Nyquist stability theorem
Examples
Appendix
This is the basis of future robustness tests
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| Topic 5 |
Control design using Bode plots
Performance issues
Synthesis
Lead/Lag examples
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| Topic 6 |
State-space systems
What are state-space models?
Why should we use them? How are they related to the transfer functions used in classical control design and how do we develop a state-space model? What are the basic properties of a state-space model, and how do we analyze these?
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| Topic 7 |
State-space systems (cont.)
What are state-space models?
Why should we use them?
How are they related to the transfer functions used in classical control design and how do we develop a state-space model?
What are the basic properties of a state-space model, and how do we analyze these?
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| Topic 8 |
State-space systems (cont.)
What are the basic properties of a state-space model, and how do we analyze these?
State-space (SS) to transfer function (TF)
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| Topic 9 |
State-space systems (cont.)
What are the basic properties of a state-space model, and how do we analyze these?
Time domain interpretations
System modes
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| Topic 10 |
State-space systems (cont.)
System zeros
Transfer function matrices for multiple-input and multiple-output (MIMO) systems
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| Topic 11 |
State-space systems (cont.)
State-space model features
Observability
Controllability
Minimal realizations
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| Topic 12 |
State-Space Systems (cont.)
State-space model features
Controllability
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| Topic 13 |
State-space systems (cont.)
Full-state feedback control
How do we change the poles of the state-space system?
Or, even if we can change the pole locations
Where do we change the pole locations to?
How well does this approach work?
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| Topic 14 |
State-space systems (cont.)
Full-state feedback control
How do we change the poles of the state-space system?
Or, even if we can change the pole locations
Where do we put the poles?
- Heuristics
- Linear quadratic regulator (LQR)
How well does this approach work?
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| Topic 15 |
State-space systems (cont.)
Open-loop estimators
Closed-loop estimators
Observer theory (no noise) — Luenberger
Estimation theory (with noise) — Kalman
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| Topic 16 |
State-space systems (cont.)
Closed-loop control using estimators and regulators
Dynamics output feedback
"Back to reality"
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| Topic 17 |
Deterministic linear quadratic regulator (LQR)
Optimal control and the Riccati equation
Weight selection
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| Topic 18 |
Optimal estimators
Applied optimal control (Chapter 12) — Bryson and Ho
Applied optimal estimation — Gelb
Optimal estimation of dynamic systems — Crassidis and Junkins
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| Topic 19 |
Feedback control systems
Stengel (Chapter 6)
Question: How well do the large gain and phase margins discussed for LQR map over to dynamics output feedback (DOFB) using LQR and linear quadratic estimator (LQE) (called linear quadratic Gaussian (LQG))?
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| Topic 20 |
Closed-loop system analysis
Bounded gain theorem
Robust stability
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| Topic 21 |
Robustness analysis
Model uncertainty
Robust stability (RS) tests
RS visualizations
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| Topic 22 |
Feedback control systems (cont.)
Robust stability (RS)
Nominal performance (NP)
Robust performance (RP)
Small gain theorem
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| Topic 23 |
MIMO systems
Singular value decomposition
Multivariable frequency response plots
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| Topic 24 |
Feedback control systems (cont.)
H∞ synthesis
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