It is an ideal source of refresher material for practising control engineers, as well as being a useful additional text for students interested in all aspects of control engineering. The subject content is wide ranging, interesting and thorough, while the style of writing makes the book very readable...I have little hesitation in recommending this book to higher education lecturers, practising control engineers and especially to undergraduates and postgraduates interested in control systems engineering - Measurement and Control

• Content.- 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. Learning control.- 33. Robust control.- 34. Structures of multivariable controllers.- A.1 Definition and important properties.- A.4 Further reading.- Appendix B: Review of matrices.- BA Definitions and notations.- B.2 Rank.- B.3 Matrix inverses and decompositions.- Lower—upper factorization.- Orthonormal factorization.- Singular value decomposition.- Modal decomposition.- B.4 Similarity transformations.- B.5 Quadratic forms, positive definite matrices, etc..- B.6 Projection matrices.- B.7 Matrix identities.- B.8 The Cayley—Hamilton theorem.- B.9 Functions of matrices.- B.10 Minimization.- B.11Ackermann’s formula.- B.12 Special similarity transformations into the standard canonical forms.- The controllable canonical form.- The observable canonical form.- The Jordan canonical form.- Change of variable ordering.- B.13 Metrics for matrices.- B.14 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.- Moments.- Vector cases.- C.4 Spectra.- C.5 Effect of linear systems.- C.6 Gaussian processes.- C.7 Time averages and ergodicity.- C.8 Further reading.- References.

It is an ideal source of refresher material for practising control engineers, as well as being a useful additional text for students interested in all aspects of control engineering. The subject content is wide ranging, interesting and thorough, while the style of writing makes the book very readable...I have little hesitation in recommending this book to higher education lecturers, practising control engineers and especially to undergraduates and postgraduates interested in control systems engineering - Measurement and Control

• Content.- 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. Learning control.- 33. Robust control.- 34. Structures of multivariable controllers.- A.1 Definition and important properties.- A.4 Further reading.- Appendix B: Review of matrices.- BA Definitions and notations.- B.2 Rank.- B.3 Matrix inverses and decompositions.- Lower—upper factorization.- Orthonormal factorization.- Singular value decomposition.- Modal decomposition.- B.4 Similarity transformations.- B.5 Quadratic forms, positive definite matrices, etc..- B.6 Projection matrices.- B.7 Matrix identities.- B.8 The Cayley—Hamilton theorem.- B.9 Functions of matrices.- B.10 Minimization.- B.11Ackermann’s formula.- B.12 Special similarity transformations into the standard canonical forms.- The controllable canonical form.- The observable canonical form.- The Jordan canonical form.- Change of variable ordering.- B.13 Metrics for matrices.- B.14 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.- Moments.- Vector cases.- C.4 Spectra.- C.5 Effect of linear systems.- C.6 Gaussian processes.- C.7 Time averages and ergodicity.- C.8 Further reading.- References.

It is an ideal source of refresher material for practising control engineers, as well as being a useful additional text for students interested in all aspects of control engineering. The subject content is wide ranging, interesting and thorough, while the style of writing makes the book very readable...I have little hesitation in recommending this book to higher education lecturers, practising control engineers and especially to undergraduates and postgraduates interested in control systems engineering - Measurement and Control

• Content.- 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. Learning control.- 33. Robust control.- 34. Structures of multivariable controllers.- A.1 Definition and important properties.- A.4 Further reading.- Appendix B: Review of matrices.- BA Definitions and notations.- B.2 Rank.- B.3 Matrix inverses and decompositions.- Lower—upper factorization.- Orthonormal factorization.- Singular value decomposition.- Modal decomposition.- B.4 Similarity transformations.- B.5 Quadratic forms, positive definite matrices, etc..- B.6 Projection matrices.- B.7 Matrix identities.- B.8 The Cayley—Hamilton theorem.- B.9 Functions of matrices.- B.10 Minimization.- B.11Ackermann’s formula.- B.12 Special similarity transformations into the standard canonical forms.- The controllable canonical form.- The observable canonical form.- The Jordan canonical form.- Change of variable ordering.- B.13 Metrics for matrices.- B.14 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.- Moments.- Vector cases.- C.4 Spectra.- C.5 Effect of linear systems.- C.6 Gaussian processes.- C.7 Time averages and ergodicity.- C.8 Further reading.- References.