Control System Analysis and Identification with MATLAB® : Block Pulse and Related Orthogonal Functions (Hardcover)

· 제목 : Control System Analysis and Identification with MATLAB® : Block Pulse and Related Orthogonal Functions (Hardcover) 
· 분류 : 외국도서 > 과학/수학/생태 > 수학 > 응용수학
· ISBN : 9781138303225
· 쪽수 : 364쪽
· 출판일 : 2018-08-15

1: Block Pulse and Related Basis Functions

1.1 Block Pulse and Related Basis Functions

1.2 Orthogonal Functions and their Properties

1.3 Block Pulse Functions in Systems and Control

References

Study Problems

2: Function Approximation via Block Pulse and Related Functions

2.1 Block Pulse Functions: Properties

2.2 Function Approximation

2.3 Error Analysis for Function Approximation in BPF Domain

2.4 Conclusion

References

Study Problems

3: Block Pulse Domain Operational Matrices for Integration and Differentiation

3.1 Operational Matrix for Integration

3.2 Operational Matrices for Integration in Generalised Block Pulse Function Domain

3.3 Improvement of the Integration Operational Matrix of First Order

3.4 One-Shot Operational Matrices for Repeated Integration

3.5 Operational Matrix for Differentiation

3.6 Operational Matrices for Differentiation in Generalised Block Pulse Function Domain

3.7 One-Shot Operational Matrices for Repeated Differentiation

3.8 Conclusion

References

Study Problems

4: Operational Transfer Functions for System Analysis

4.1 Walsh Operational Transfer Function (WOTF)

4.2 Block Pulse Operational Transfer Function (BPOTF) for System Analysis

4.3 Oscillatory Phenomenon in Block Pulse Domain Analysis of First Order Systems

4.4 Nature of Expansion of the BPOTF of a First Order Plant 110

4.5 Modified BPOTF (MBPOTF) using All-Integrator Approach for System Analysis

4.6 Error due to MBPOTF Approach

4.7 Conclusion

References

Study Problems

5: System Analysis and Identification using Convolution and ‘Deconvolution’ in BPF Domain

5.1 The Convolution Process in BPF Domain

5.2 Identification of an Open Loop System via ‘Deconvolution’

5.3 Numerical Instability of the ‘Deconvolution’ Operation: Its Mathematical Basis

5.4 Identification of a Closed Loop System

5.5 Conclusion

References

Study Problems

6: Delayed Unit Step Functions (DUSF) for System Analysis and Fundamental Nature of the Block Pulse Function (BPF) Set

6.1 The Set of DUSF and the Operational Matrix for Integration

6.2 Block Pulse Function versus Delayed Unit Step Function: A Comparative Study

6.3 Stretch Matrix in DUSF Domain

6.4 Solution of a Functional Differential Equation using DUSF

6.5 Conclusion

References

Study Problems

7: Sample-and-Hold Functions (SHF) for System Analysis

7.1 Brief Review of Sample-and-Hold Functions (SHF)

7.2 Analysis of Control Systems with Sample-and-Hold using the Operational Transfer Function Approach

7.3 Operational Matrix for Integration in SHF Domain

7.4 One-Shot Operational Matrices for Repeated Integration

7.5 System Analysis using One-Shot Operational Matrices and Operational Transfer Function

7.6 Error Analysis: A Comparison between SHF and BPF

7.7 Conclusion

References

Study Problems

8: Discrete Time System Analysis using a Set of Delta Functions (DF)

8.1 A Set of Mutually Disjoint Delta Functions

8.2 Delta Function Domain Operational Matrices for Integration

8.3 One-Shot Operational Matrices for Repeated Integration

8.4 Analysis of Discrete SISO Systems using One-Shot Operational Matrices and Delta Operational Transfer Function

8.5 Conclusion

References

Study Problems

9: Non-Optimal Block Pulse Functions (NOBPF) for System Analysis and Identification

9.1 Basic Properties of Non-Optimal Block Pulse Functions

9.2 From ‘Optimal’ Coefficients to ‘Non-Optimal’ Coefficients

9.3 Function Approximation using Non-Optimal Block Pulse Functions (NOBPF)

9.4 Operational Matrices for Integration

9.5 Process of Convolution and ‘Deconvolution’

9.6 Analysis of an Open Loop System via Convolution

9.7 Identification of an Open Loop System via ‘Deconvolution’

9.8 Identification of a Closed Loop System via ‘Deconvolution’

9.9 Error Analysis

9.10 Conclusion

References

Study Problems

10: System Analysis and Identification using Linearly Pulse-Width Modulated Generalised Block Pulse Functions (LPWM-GBPF)

10.1 Conversion of a GBPF set to a Linearly Pulse-Width Modulated GBPF (LPWM-GBPF) Set

10.2 Representation of Time Functions via LPWM-GBPF set

10.3 Convolution Process in LPWM Block Pulse Function Domain

10.4 Linear Feedback System Identification using Generalised Convolution Matrix

10.5 Error Analysis

10.6 Conclusion

References

Study Problems

Appendices

Appendix A: Introduction to Linear Algebra

Appendix B: Selected MATLAB Programs

Index