
Signal Processing for Active Control
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Content
- Front Cover
- Signal Processing for Active Control
- Copyright Page
- Contents
- Series Preface
- Dedication
- Preface
- Glossary
- Chapter 1. The Physical Basis for Active Control
- 1.1. Introduction
- 1.2. Control of wave transmission
- 1.3. Control of power in infinite systems
- 1.4. Strategies of control in finite systems
- 1.5. Control of energy in finite systems
- 1.6. Control of sound radiation from structures
- 1.7. Local control of sound and vibration
- Chapter 2. Optimal and Adaptive Digital Filters
- 2.1. Introduction
- 2.2. Structure of digital filters
- 2.3. Optimal filters in the time domain
- 2.4. Optimal filters in the transfortn Domain
- 2.5. Multichannel optimal filters
- 2.6. The LMS algorithm
- 2.7. The RLS algorithm
- 2.8. Frcquency-dornain adaptation
- 2.9. Adaptive IIR filters
- Chapter 3. Single-Channel Feedforward Control
- 3.1. Introduction
- 3.2. Control of deterministic disturbances
- 3.3. Optimal control of stochastic disturbances
- 3.4. Adaptive FIR controllers
- 3.5. Frequency-domain adaptation of FIR controllers
- 3.6. Plant identification
- 3.7. Adaptive IIR controllers
- 3.8. Practical applications
- Chapter 4. Multichannel Control of Tonal Disturbances
- 4.1. Introduction
- 4.2. Optinlal control of tonal disturbances
- 4.3. Steepest-descent algorithms
- 4.4. Robustness to plant uncertainties and plant tnodel errors
- 4.5. Iterative least-squares algorithms
- 4.6. Feedback control interpretation of adaptive feedforward systems
- 4.7. Minimisation of the maximum level at any sensor
- 4.8. Applications
- Chapter 5. Multichannel Control of Stochastic Disturbances
- 5.1. Introduction
- 5.2. Optimal control in the time domain
- 5.3. Optimal control in the transfom domain
- 5.4. Adaptive algorithms in the time domain
- 5.5. The preconditioned LMS algorithm
- 5.6. Adaptive algorithms in the frequency domain
- 5.7. Application: controlling road noise in vehicles
- Chapter 6. Design and Perfomance of Feedback Controllers
- 6.1. Introduction
- 6.2. Analogue controllers
- 6.3. Digital controllers
- 6.4. Internal model control (IMC)
- 6.5. Optimal control in the titne domain
- 6.6. Optimal control in the transform domain
- 6.7. Multichannel feedback controllers
- 6.8. Robust stahility for multichannel systems
- 6.9. Optimal multichannel control
- 6.10. Application: active headrest
- Chapter 7. Adaptive Feedback Controllers
- 7.1. Introduction
- 7.2. Tirne-domain adaptation
- 7.3. Frequency-domain adaptation
- 7.4. Combined feedback and feedforward control
- 7.5. Combined analogue and digital controllers
- 7.6. Application: active headsets
- Chapter 8. Active Control of Nonlinear Systems
- 8.1. Introduction
- 8.2. Analytical descriptions of nonlinear systems
- 8.3. Neural networks
- 8.4. Adaptive feedforward control
- 8.5. Chaotic systems
- 8.6. Control of chaotic behaviour
- Chapter 9. Optimisation of Transducer Location
- 9.1. The optilnisation problcnl
- 9.2. Optimisation of secondary source and error sensor location
- 9.3. Application of genetic algorithms
- 9.4. Application of simulated annealing
- 9.5. Practical optimisation of source location
- Chapter 10. Hardware for Active Control
- 10.1. Introduction
- 10.2. Anti-aliasing filters
- 10.3. Reconstruction filters
- 10.4. Filter delay
- 10.5. Data converters
- 10.6. Data quantisation
- 10.7. Processor requirements
- 10.8. Finite-precision effects
- Appendix: Linear Algebra and the Description of Multichannel Systems
- A.l. Vectors
- A.2. Matrices
- A.3. Determinants and the inverse matrix
- A.4. Trace of a matrix and its derivatives
- A.5. Outer products and spectral density matrices
- A.6. Matrix and vector quadratic equations
- A.7. Eigenvalue/eigenvector decomposition
- A.8. Singular value decomposition
- A.9. Vector and matrix norms
- References
- Index
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