Focusing on linear systems, this text incorporates MATLAB, with an emphasis on the ideas behind the computation and the interpretation of the results. It is suitable for undergraduate students of linear systems and multivariable system design.

1. Introduction; 1.1 Introduction; 1.2 Overview; 2. Mathematical Descriptions of Systems; 2.1 Introduction; 2.1.1 Causality and Lumpedness; 2.2 Linear Systems; 2.3 Linear Time-Invariant (LTI) Systems; 2.4 Linearization; 2.5 Examples; 2.5.1 RLC Networks; 2.6 Discrete-Time Systems; 3. Linear Algebra; 3.1 Introduction; 3.2 Basis, Representation, And Orthonormalization; 3.3 Linear Algebraic Equations; 3.4 Similarity Transformation; 3.5 Diagonal Form And Jordan Form; 3.6 Functions Of A Square Matrix; 3.7 Lyapunov Equation; 3.8 Some Useful Formula; 3.9 Quadratic Form and Positive Definiteness; 3.10 Singular Valve Decomposition; 3.11 Norms of Matrices; 4. State-Space Solutions And Realizations; 4.1 Introduction; 4.2 Solution Of LTI State Equations; 4.2.1 Discretization; 4.2.2 Solution of Discrete-Time Equations; 4.3 Equivalent State Equations; 4.3.1 Canonical Forms; 4.3.2 Magnitude Scaling In Op-Amp Circuits; 4.4 Realizations; 4.5 Solution Of Linear Time-Varying (LTV) Equations; 4.5.1 Discrete-Time Case; 4.6 Equivalent Time-Varying Equations; 5. Stability; 5.1 Introduction; 5.2 Input-Output Stability Of LTI Systems; 5.2.1 Discrete-Time Case; 5.3 Internal Stability; 5.3.1 Discrete-Time Case; 5.4 Lyapunov Theorem; 5.5 Stability Of LTV Systems; 6. Controllability And Observability; 6.1 Introduction; 6.2 Controllability; 6.2.1 Controllability Indices; 6.3 Observability; 6.3.1 Observability Indices; 6.4 Canonical Decomposition; 6.5 Conditions In Jordan-Form Equations; 6.6 Discrete-Time State Equations; 6.6.1 Controllability To The Origin And Reachability; 6.7 Controllability After Sampling; 6.8 LTV State Equations; 7. Minimal Realizations And Coprime Fractions; 7.1 Introduction; 7.2 Implications Of Coprimeness; 7.2.1 Minimal Realizations; 7.3 Computing Coprime Ffractions; 7.3.1 QR Decomposition; 7.4 Balanced Realization; 7.5 Realizations From Markov Parameters; 7.6 Degree Of Transfer Matrices; 7.7 Minimal Realizations - Matrix Case; 7.8 Matrix Polynomial Fractions; 7.8.1 Column And Row Reduceness; 7.8.2 Computing Matrix Coprime Fractions; 7.9 Realization From Matrix Coprime Fractions; 7.10 Realizations From Matrix Markov Parameters; 7.11 Concluding Remarks; 8. State Feedback And State Estimators; 8.1 Introduction; 8.2 State Feedback; 8.2.1 Solving Lyapunov Equation; 8.3 Regulation And Tracking; 8.3.1 Robust Tracking And Disturbance Rejection; 8.3.2 Stabilization; 8.4 State Estimator; 8.4.1 Reduced-Dimensional State Estimator; 8.5 Feedback From Estimated States; 8.6 State Feedback-Multivariable Case; 8.6.1 Cyclic Design; 8.6.2 Lyapunov-Equation Method; 8.6.3 Canonical-Form Method; 8.6.4 Effect Of Transfer Matrices; 8.7 State Estimators-Multivariable Case; 8.8 Feedback From Estimated States-Multivariable Case; 9. Pole Placement And Model Matching; 9.1 Introduction; 9.1.1 Compensator Equation-Classical Method; 9.2 Unity-Feedback Configuration-Pole Placement; 9.2.1 Regulation And Tracking; 9.2.2 Robust Tracking And Disturbance Rejection; 9.2.3 Embedding Internal Models; 9.3 Implementable Transfer Functions; 9.3.1 Model-Matching Two-Parameter Configuration; 9.3.2 Implementation Of Two-Parameter Compensators; 9.4 Multivariable Unity Feedback Systems; 9.4.1 Regulation And Tracking; 9.4.2 Robust Tracking And Disturbance Rejection; 9.5 Multivariable Model Marching-Two-Parameter Configuration; 9.5.1 Decoupling; 9.6 Concluding Remarks; References

"The downsizing of theory in this third edition of the text makes the book a standard linear system text for a senior or first graduate course in the subject....The standard text in linear systems."--Salah Yousif, California State University, Sacramento "Excellent text!"--P. Givi, State University of New York at Buffalo "An excellent textbook for a first year graduate course on linear control."--Wei Lin, Case Western Reserve University