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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.
- Written by a team of contributors from the industry's best-known product manufacturers and software developers
- Provides real insight into new technologies available in the industry
- Outlines practical applications of adaptive control technology
Instrumentation and control engineers and software developers, plant engineers, managers and technical sales staff
Students, teachers and researchers in control engineering
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
- No. of pages:
- © Butterworth-Heinemann 2002
- 17th October 2002
- Paperback ISBN:
- eBook ISBN:
Control Engineering Magazine