Self-tuning generalized predictive controllers
Author | : H. Rasmussen |
Publisher | : |
Total Pages | : 70 |
Release | : 1989 |
Genre | : |
ISBN | : |
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Author | : H. Rasmussen |
Publisher | : |
Total Pages | : 70 |
Release | : 1989 |
Genre | : |
ISBN | : |
Author | : |
Publisher | : DIANE Publishing |
Total Pages | : 26 |
Release | : 2000 |
Genre | : |
ISBN | : 1428996427 |
Author | : National Aeronautics and Space Administration (NASA) |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 26 |
Release | : 2018-06-16 |
Genre | : |
ISBN | : 9781721244249 |
Three techniques are introduced to determine the order and control weighting for the design of a generalized predictive controller. These techniques are based on the application of fuzzy logic, genetic algorithms, and simulated annealing to conduct an optimal search on specific performance indexes or objective functions. Fuzzy logic is found to be feasible for real-time and on-line implementation due to its smooth and quick convergence. On the other hand, genetic algorithms and simulated annealing are applicable for initial estimation of the model order and control weighting, and final fine-tuning within a small region of the solution space, Several numerical simulations for a multiple-input and multiple-output system are given to illustrate the techniques developed in this paper. Lin, Chaung and Juang, Jer-Nan Langley Research Center NASA/TM-2000-210619, L-17969, NAS 1.15:210619
Author | : |
Publisher | : |
Total Pages | : |
Release | : 1989 |
Genre | : |
ISBN | : |
Author | : Sung-Duck Han |
Publisher | : |
Total Pages | : 168 |
Release | : 1988 |
Genre | : |
ISBN | : |
Author | : M Mahfouf |
Publisher | : CRC Press |
Total Pages | : 300 |
Release | : 1998-08-27 |
Genre | : Medical |
ISBN | : 9780748405978 |
Predictive control is a powerful tool in dealing with those processes with large time delays. Generalized Predictive Control GPC is the most popular approach to the subject, and this text discusses the application of GPC starting with the concept of long-range predictive control and its need in medicine particularly automated drug deliveries.; The concept of adaptation is also emphasized with respect to patient-to-patient parameter variations. Subsequent chapters discuss interactions, comparisons and various aspects of GPC. The book concludes by putting into perspective the generic nature of the architecture built around GPC and which provides model-based fault diagnosis with control.
Author | : |
Publisher | : |
Total Pages | : |
Release | : 2001 |
Genre | : |
ISBN | : |
Author | : Jean-Pierre Corriou |
Publisher | : Springer Science & Business Media |
Total Pages | : 763 |
Release | : 2013-03-09 |
Genre | : Science |
ISBN | : 1447138481 |
This reference book can be read at different levels, making it a powerful source of information. It presents most of the aspects of control that can help anyone to have a synthetic view of control theory and possible applications, especially concerning process engineering.
Author | : Vladimír Bobál |
Publisher | : Springer Science & Business Media |
Total Pages | : 340 |
Release | : 2005-05-19 |
Genre | : Technology & Engineering |
ISBN | : 9781852339807 |
Practical emphasis to teach students to use the powerful ideas of adaptive control in real applications Custom-made Matlab® functionality to facilitate the design and construction of self-tuning controllers for different processes and systems Examples, tutorial exercises and clearly laid-out flowcharts and formulae to make the subject simple to follow for students and to help tutors with class preparation
Author | : Eduardo F. Camacho |
Publisher | : Springer Science & Business Media |
Total Pages | : 250 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 1447130081 |
Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.