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Control System software offers several Artificial Intelligence tools and commands for systematically analyzing, designing, and tuning linear control systems. You can specify your system as a transfer function, state-space, zero-pole-gain, or frequency-response model. This book develops the following topics: PID Controller Design, Designing Cascade Control System with PI Controllers , Tune 2-DOF PID Controller (Command Line) , Tune 2-DOF PID Controller (PID Tuner), PID Controller Types for Tuning , Classical Control Design , Choosing a Control Design Approach, Control System Designer Tuning Methods, Design Requirements, Feedback Control Architectures, Design Multiloop Control System, Multimodel Control Design, Bode Diagram Design, Root Locus Design, Nichols Plot Design, Edit Compensator Dynamics, Design Compensator Using Automated Tuning Methods, Analyze Designs Using Response Plots, Compare Performance of Multiple Designs, Design Hard-Disk Read/Write Head Controller, Design Compensator for Plant Model with Time Delays, Design Compensator for Systems Represented by Frequency Response Data, Design Internal Model Controller for Chemical Reactor Plant, Design LQG Tracker Using Control System Designer, State-Space Control Design, Extended and Unscented Kalman Filter Algorithms for Online State Estimation, Generate Code for Online State Estimation in MATLAB, Validate Online State Estimation in Simulink, Troubleshoot Online State Estimation, Nonlinear State Estimation Using Unscented Kalman Filter, Estimate States of Nonlinear System with Multiple, Multirate Sensors and Design Case Studies.
The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem. To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include: an introduction to PID control technology features and typical industrial implementations; chapter contributions ordered by the increasing quality of the model information used; novel PID control concepts for multivariable processes. PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text.
This volume highlights recent progress on the fundamental chemistry and mechanistic understanding of metallocofactors, with an emphasis on the major development in these areas from the perspective of bioinorganic chemistry. Metallocofactors are essential for all forms of life and include a variety of metals, such as iron, molybdenum, vanadium, and nickel. Structurally fascinating metallocofactors featuring these metals are present in many bacteria and mediate remarkable metabolic redox chemistry with small molecule substrates, including N2, CO, H2, and CO2. Current interest in understanding how these metallocofactors function at the atomic level is enormous, especially in the context of sustainably feeding and fueling our planet; if we can understand how these cofactors work, then there is the possibility to design synthetic catalysts that function similarly.