José Rodellar - ADEX Optimized Adaptive Controllers and Systems: From Research to Industrial Practice
Published: 2014-11-06 | ISBN: 3319097938 | PDF | 447 pages | 12.12 MB
This book is a simple and didactic account of the developments and practical applications of predictive, adaptive predictive, and optimized adaptive control from a perspective of stability, including the latest methodology of adaptive predictive expert (ADEX) control.
ADEX Optimized Adaptive Control Systems is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. The text begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guaranty the desired control performance. The second and third parts present strategic considerations of predictive control and related adaptive systems necessary for the proper design of driver block and adaptive mechanism and thence their technical realization. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control methodologies. Benchmark applications of these methodologies (distillation column and pulp-factory bleaching plant) are treated next with a focus on practical implementation issues. The final part of the book describes ADEX platforms and illustrates their use in the design and implementation of optimized adaptive control systems to three different challenging-to-control industrial processes:
sulfur recovery; and
temperature control of superheated steam in coal-fired power generation.
The presentation is completed by a number of appendices containing technical background associated with the main text including a manual for the ADEX COP platform developed by the first author to exploit the capabilities of adaptive predictive control in real plants.
ADEX Optimized Adaptive Control Systems provides practicing process control engineers with a multivariable optimal control solution which is adaptive and resistant to perturbation and the effects of noise. Its pedagogical features also facilitate its use as a teaching tool for formal university and Internet-based open-education-type graduate courses in practical optimal adaptive control and for self-study.
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