Table of Contents1. Getting Started 1.1 Using the Package for the First Time 1.2 Structure of the Application 1.3 Robustness of Numerical Methods 2. Introduction 2.1 Quick Reference Solutions of the Lyapunov and Sylvester Matrix Equations Solutions of the Algebraic Riccati Equations Reduction to Controller-Hessenberg and
Observer-Hessenberg Forms Controllability and Observability Tests Pole Assignment Feedback Stabilization Design of the Reduced-Order State Estimator (Observer) Model Reduction Model Identification Miscellaneous Matrix Decompositions and Functions 2.2 An Industrial Application: Controlling the Drum Boiler 2.2.1 The State-Space Model of a Drum Boiler 2.2.2 System Responses, Stability, and Poles 2.2.3 Testing the Controllability 2.2.4 The Design of the LQR Controller 2.2.5 The Controller Design Using Constrained Feedback
Stabilization 2.2.6 The Observer Design 3. Matrix Equations and Control Applications 3.1 Lyapunov Equations 3.2 Riccati Equations 3.2.1 The Schur Methods for the Riccati Equations 3.2.2 The Inverse-Free Generalized Eigenvector and Schur
Methods for the Riccati Equations 3.2.3 The Matrix Sign-Function Methods for the Riccati Equations 3.2.4 The Newton Methods for the Riccati Equations 3.2.5 LQR and LQG Designs Using Riccati Equations 4. Block Hessenberg Forms 4.1 Controller-Hessenberg Forms 4.2 Observer-Hessenberg Forms 4.3 Controllability and Observability Tests Using
Block Hessenberg Forms 5. Pole Assignment and Stabilization by State Feedback 5.1 Pole Assignment Methods 5.1.1 The Recursive Algorithms 5.1.2 The Explicit and Implicit QR Algorithms 5.1.3 The Schur Method 5.2 Partial Pole Assignment 5.3 Constrained Feedback Stabilization 5.4 Lyapunov Feedback Stabilization 6. State Estimation 6.1 Full-Order State Estimation 6.2 Reduced-Order State Estimator 6.2.1 Reduced-Order State Estimator via Pole Assignment 6.2.2 Reduced-Order State Estimator via Sylvester-Observer
Equation 7. Model Reduction 7.1 Cholesky Factors of the Controllability and Observability Gramians 7.2 Model Reduction Using Schur and Square-Root Methods 8. Model Identification 8.1 Time-Domain System Identification 8.1.1 Identification Using Markov Parameters 8.1.2 Identification Using Input-Output Data (Subspace
System Identification Method) 8.2 Frequency Domain System Identification 9. Generalized Eigenvalue Problem 9.1 Generalized Eigenvalue Problem 9.2 Generalized Schur Decomposition References Appendix. Collection of Control Systems for Case Studies A.1 Continuous-Time Models A.1.1 The Absorption Column A.1.2 The F-8 Aircraft A.1.3 The L-1011 Aircraft A.1.4 The Tubular Ammonia Reactor A.1.5 The Fluid Catalytic Reactor A.1.6 The Binary Distillation Column A.1.7 The Drum Boiler A.1.8 The Flight Control System A.1.9 The Automobile Gas Turbine A.1.10 The CH-47 Helicopter A.1.11 The Magnetic Tape A.1.12 The Electric Power System A.1.13 The J-100 Jet Engine A.1.14 The "Smart" Highway A.1.15 The Generator Axle in a Power Plant A.2 Discrete-Time Models A.2.1 The Catalytic Cracker A.2.2 The Chemical Plant A.2.3 The Paper Machine A.2.4 The Steam Power System
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