Contents: 1. Introduction – Systems and the use of mathematical models; 2. Mathematical preliminaries; 3. Mathematical models for continuous time signals; 4. An introduction to laplace transforms; 5. SISO input-output models – LTI systems; 6. Introduction to bode plots; 7. An introduction to state space concepts; 8. Propagation of signal uncertainty through an LTI system – Covariance analysis; 9. An introduction to feedback control systems – The big picture; 10. Controllability – Transfering the state of a system; 11. Full state feedback – A method for altering the natural modes of a system; 12. Observability – Reconstructing the state of a system; 13. State observers – State reconstruction or estimation via feedback; 14. Fundamental system invariance properties; 15. Model based compensators and the separation principle; 16. Representing uncertainty; 17. A new paradigm for control system design; 18. State space models for time varying systems; 19. Nonlinear systems, equilibria and linearization; 20. An introduction to discrete time signals; 21. An introduction to discrete time systems – Discretization of continuous time LTI systems; 22. An introduction to Z-transforms; 23. Linear shift invariant systems with state space representations; 24. Modeling of the sampling process – Frequency domain analysis; 25. Discrete time LSI simulation of continuous time LTI systems; 26. References; 27. Index.
Presenting fourier transform, convolution, and definitions of autocorrelation and power spectral density. It also introduces concepts of probability, random variables, and stochastic processes and their applications to the analysis of linear systems.
