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Edited By Vance VanDoren, Ph.D., P.E., Control Engineering Magazine
Description Techniques for Adaptive Control compiles chapters from a team of expert contributors that allow readers to gain a perspective into a number
of different approaches to adaptive control. In order to do this, each contributor provides an overview of a particular product, how
it works, and reasons why a user would want it as well as an in depth explanation of their particular method.
This is one of the latest
technologies to emerge in the instrumentation and control field. These latest control methodologies offer a means to revolutionize plant
and process efficiency, response time and profitability by allowing a process to be regulated by a form of rule-based AI, without human
intervention.
Rather than the common academic-based approach that books on this subject generally take, the contributions here outline
practical applications of adaptive control technology allowing for a real look inside the industry and the new technologies available.
Audience
Instrumentation and control engineers and software developers, plant engineers, managers and technical sales staff
Students, teachers and researchers in control engineering
Contents Adaptive Tuning Methods of the Foxboro I/A System; Controller Structure; Minimum Variance Control; Control by Minimizing Sensitivity to
Process Uncertainty; Algebraic Controller Design for Load Rejection and Shaped Transient Response; Algebraic Tuning of a Controller with
Deadtime; Robust Adaptation of Feedback Controller Gain Scheduling; Feedforward Control; Adaptation of Feedforward Load Compensators;
The Exploitation of Adaptive Modelling in the Model Predictive Control Environment of Connoisseur; Model Structures; Issues for Identification;
Adaptive Modelling; Other Methods; Simulated case study on a Fluid Catalytic Cracking Unit; Adaptive Predictive Regulatory Control with
BrainWave?; The Laguerre Modelling Method; Why the Laguerre Method is Used for Identification; Why Modelling Techniques, Trade-Offs;
Formulas Used; Building the Adaptive Predictive Controller Based on a Laguerre State Space Model; The Concepts Behind MBPC; A Simple
Predictive Control Law; The Indirect Adaptiver Predictive Control Solution; Feedforward Variables used in Modelling and Control; Why
Simpler is Better; A Laguerre Based Controller for Integrating Systems; Identification and Disturbance Estimation for Integrating Systems;
The Controller; Practical Issues for Implenting Adaptive Predictive Controllers; Integration with Existing Control System Equipment;
Ensuring Successful Identification; Treating Self-Regulating as Integrating Systems; Choosing Appropriate Feedforward Variables; Determining
when the Controller Setup is Correct and Complete; Simulation Examples; Model Identification in Closed Loop; Model Identification for
Feedforward Variables in Closed Loop; Integrating and Self-Regulating System Control; Industrial Application Examples; Applications to
Batch Reactors; Advanced Control of a Steam Header Pressure, Saveall Consistency and Reel Brightness in a TMP Newsprint Mill; Adaptive
Predictive Control of a Glass Forehearth; Model-Free Adaptive Control; Model-Free Adaptive Control (MFA); MFA Control Methodology and
Applications; Expert-Based Adaptive Control - ControlSoft's INTUNE Adaptive and Diagnostic Software; Identification-Based Adaptive Control;
Expert-Based Adaptive Control, ControlSoft's INTUNE; Concluding Observations; KnowledgeScape, an Object-oriented Real-time Adaptive Modeling
and Optimization Expert Control System for the Process Industries; Intelligent Software Objects and their use in KnowledgeScape; Artificial
Intelligence and Process Control; Neural Networks; Genetic Algorithms; Crisp Rules; Fuzzy Rules; Putting it all together; Configuring
an application in KnowledgeScape; Writing crisp and expert control rules; Creating adaptive, on-line neural models of the process; Creating
genetic algorithm optimizers for the process; Results in the Minerals Processing Industry
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