Begins with a review of digital control systems and their design and basic mathematical concepts including difference equations, the z-transform, and state-variable methods. Then applies the fundamentals of digital signal processors to such control systems, describing such state-space techniques as pole placement, state estimation, and optimal linear quadratic regulation. Also considers advanced topics, among them chaos in nonlinear control systems and fuzzy logic control. For practicing engineers, graduates, and advanced undergraduates with some background in linear systems theory and linear algebra and a familiarity with the CAE, MATLAB, and MATRIX software packages. Has been used in courses. Annotation c. by Book News, Inc., Portland, Or.
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Farzad Nekoogar is Lecturer, The University of California at Berkeley-Extension, and Senior CAE Engineer at Diasonics Corporation, Milpitas, California. He has taught Digital Control Using Digital Signal Processing to practicing engineers and teaches courses throughout the electronics industry.
08910-2
Use computer-aided engineering software to design DSPs for digital control systems.
DSPs can be used to implement controllers designed with classical frequency-domain techniques as well as more contemporary state-variable methods. Computer-aided analysis and design tools bring the whole process up to date. Digital Control Using Digital Signal Processing provides complete coverage of the field, including:
Digital Control Using Digital Signal Processing begins with a review of digital control systems and their design. Basic mathematical concepts are presented early, including difference equations, the z-transform and state-variable methods, leading to a thorough treatment of classical compensator design.
The fundamentals of digital signal processors are then applied to digital control systems. The latest state-space techniques are covered, including pole placement, state estimation, and optimal linear quadratic regulation. Advanced topics include chaos in nonlinear control systems and fuzzy logic control.
Eight appendices provide practical information about useful formulas, software tools, and sample programs.
Practicing engineers will find Digital Control Using Digital Signal Processing an invaluable resource, as will upper-division and graduate students. Some background in linear systems theory and linear algebra is required. Familiarity with CAE, MATLAB, and MATRIXx software packages will aid in implementing the analysis and design discussed here.
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