Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Apply a state-space approach to modern control system analysis and designWritten by an expert in the field, this concise textbook offers hands-on coverage of modern control system engineering. Modern Control: State-Space Analysis and Design Methods features start-to-finish design projects as well as online snippets of MATLAB code with simulations. The essential mathematics are presented along with fully worked-out examples in gradually increasing degrees of difficulty. Readers will receive “just-in-time” math background from a comprehensive appendix and get step-by-step descriptions of the latest analysis and design techniques. Coverage includes:• An introduction to control systems• State-space representations• Pole placement via state feedback• State estimators (observers)• Non-minimal canonical forms• Linearization• Lyapunov stability• Linear quadratic regulators (LQR)• Symmetric root locus (SRL)• Kalman filter• Linear quadratic gaussian control (LQG)
Publisher''s Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.
Apply a state-space approach to modern control system analysis and design
Written by an expert in the field, this concise textbook offers hands-on coverage of modern control system engineering. Modern Control: State-Space Analysis and Design Methods features start-to-finish design projects as well as online snippets of MATLAB code with simulations. The essential mathematics are presented along with fully worked-out examples in gradually increasing degrees of difficulty. Readers will receive “just-in-time” math background from a comprehensive appendix and get step-by-step descriptions of the latest analysis and design techniques.
Coverage includes:
• An introduction to control systems
• State-space representations
• Pole placement via state feedback
• State estimators (observers)
• Non-minimal canonical forms
• Linearization
• Lyapunov stability
• Linear quadratic regulators (LQR)
• Symmetric root locus (SRL)
• Kalman filter
• Linear quadratic gaussian control (LQG)
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