PID Tuning
A Modern Approach via the Weighted Sensitivity Problem
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The PID controller is the most common option in the realm of control applications and is dominant in the process control industry. Among the related analytical methods, Internal Model Control (IMC) has gained remarkable industrial acceptance due to its robust nature and good set-point responses. However, the traditional application of IMC results in poor load disturbance rejection for lag-dominant and integrating plants. This book presents an IMC-like design method which avoids this common pitfall and is devised to work well for plants of modest complexity, for which analytical PID tuning is p...
The PID controller is the most common option in the realm of control applications and is dominant in the process control industry. Among the related analytical methods, Internal Model Control (IMC) has gained remarkable industrial acceptance due to its robust nature and good set-point responses. However, the traditional application of IMC results in poor load disturbance rejection for lag-dominant and integrating plants. This book presents an IMC-like design method which avoids this common pitfall and is devised to work well for plants of modest complexity, for which analytical PID tuning is plausible. For simplicity, the design only focuses on the closed-loop sensitivity function, including formulations for the H and H2 norms. Aimed at graduate students and researchers in control engineering, this book:
Considers both the robustness/performance and the servo/regulation trade-offs
Presents a systematic, optimization-based approach, ultimately leading to well-motivated, model-based, and analytically derived tuning rules
Shows how to tune PID controllers in a unified way, encompassing stable, integrating, and unstable processes
Finds in the Weighted Sensitivity Problem the sweet spot of robust, optimal, and PID control
Provides a common analytical framework that generalizes existing tuning proposals
Considers both the robustness/performance and the servo/regulation trade-offs
Presents a systematic, optimization-based approach, ultimately leading to well-motivated, model-based, and analytically derived tuning rules
Shows how to tune PID controllers in a unified way, encompassing stable, integrating, and unstable processes
Finds in the Weighted Sensitivity Problem the sweet spot of robust, optimal, and PID control
Provides a common analytical framework that generalizes existing tuning proposals
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