Handbook of Control Systems Engineering

1. Introduction and overview.- 2. Elements of systems engineering of digital control.- 3. Sensors and instrumentation.- 4. Control elements, actuators, and displays.- 5. Computer systems hardware.- 6. Computer software.- 7. Communications.- 8. Control laws without theory.- 9. Sources of system models.- 10. Continuous-time system representations.- 11. Sampled-data system representations.- 12. Conversions of continuous-time to discrete-time models.- 13. System performance indicators.- 14. BIBO stability and simple tests.- 15. Nyquist stability theory.- 16. Lyapunov stability testing.- 17. Steady state response: error constants and system type.- 18. Root locus methods for analysis and design.- 19. Desirable pole locations.- 20. Bode diagrams for frequency domain analysis and design.- 21. A special control law: deadbeat control.- 22. Controllability.- 23. Controller design by pole placement.- 24. Observability.- 25. State observers.- 26. Optimal control by multiplier-type methods.- 27. Other optimal control methods.- 28. State estimation in noise.- 29. State feedback using state estimates.- 30. System identification.- 31. Adaptive and self-tuning control.- 32. Structures of multivariable controllers.- 33. Linearization methods for nonlinear systems.- 34. Variable structures and sliding mode control.- 35. Intelligent control.- 36. Robust control.- 37. Discrete event control systems.- Appendix A. z-Transform.- A. 1 Definition and important properties.- A.2 The inverse z-transform.- A.4 Further reading.- Appendix B. Review of matrices.- B.1 Definitions and notations.- B.2 Rank.- B.3 Matrix Inverses and decompositions.- B.4 Similarity transformations.- B.6 Projection matrices.- B.7 Matrix Identities.- B.8 The Cayley-Hamilton theorem.- B.9 Functions of matrices.- B.10 Minimization.- B.11 Ackermann’s formula.- B.12 Special similarity transformations into the standard canonical forms.- B.13 Metrics for matrices.- B.14 Notation for derivatives.- B.15 Further reading.- Appendix C. Description of random processes.- C.1 Events, probabilities, and probability density functions.- C.2 Averages and moments: means and variances.- C.3 Random processes.- C.4 Spectra.- C.5 Effect of linear systems.- C.6 Gaussian processes.- C.7 Time averages and ergodicity.- C.8 Further reading.- References.