[PDF] Computer Aided Design For Multivariable Self Tuning Controllers With Application To The Control Of A Coupled Electric Drives System eBook

Author : Vladimír Bobál
Publisher : Springer Science & Business Media
Page : 328 pages
File Size : 36,58 MB
Release : 2005-10-24
Category : Technology & Engineering
ISBN : 1846280419

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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 : C. James Taylor
Publisher : John Wiley & Sons
Page : 360 pages
File Size : 39,84 MB
Release : 2013-05-29
Category : Technology & Engineering
ISBN : 1118535510

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True Digital Control: Statistical Modelling andNon–Minimal State Space Designdevelops a true digitalcontrol design philosophy that encompasses data–basedmodel identification, through to control algorithm design,robustness evaluation and implementation. With a heritage from bothclassical and modern control system synthesis, this book issupported by detailed practical examples based on theauthors’ research into environmental, mechatronic and roboticsystems. Treatment of both statistical modelling and control designunder one cover is unusual and highlights the important connectionsbetween these disciplines. Starting from the ubiquitous proportional–integralcontroller, and with essential concepts such as pole assignmentintroduced using straightforward algebra and block diagrams, thisbook addresses the needs of those students, researchers andengineers, who would like to advance their knowledge of controltheory and practice into the state space domain; and academics whoare interested to learn more about non–minimal state variablefeedback control systems. Such non–minimal state feedback isutilised as a unifying framework for generalised digital controlsystem design. This approach provides a gentle learning curve, fromwhich potentially difficult topics, such as optimal, stochastic andmultivariable control, can be introduced and assimilated in aninteresting and straightforward manner. Key features: Covers both system identification and control systemdesign in a unified manner Includes practical design case studies and simulationexamples Considers recent research into time–variable andstate–dependent parameter modelling and control, essentialelements of adaptive and nonlinear control system design, and thedelta–operator (the discrete–time equivalent of thedifferential operator) systems Accompanied by a website hosting MATLAB examples True Digital Control: Statistical Modelling andNon–Minimal State Space Design is a comprehensive andpractical guide for students and professionals who wish to furthertheir knowledge in the areas of modern control and systemidentification.

Author : John O'Reilly
Publisher : IET
Page : 476 pages
File Size : 38,11 MB
Release : 1987
Category : Mathematics
ISBN : 9780863411175

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Very Good,No Highlights or Markup,all pages are intact.

Author :
Publisher :
Page : pages
File Size : 41,80 MB
Release : 1981
Category :
ISBN :

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Multivariable interactive processes generally require control by multivariable decoupling controllers in series with conventional single-variable controllers. The techniques that are available for the design of such multivariable controllers are relatively complex, requiring the use of a digital computer. Also, the design of numerous conventional controllers is greatly facilitated by computer-aided design programmes that reduce designing time.

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Page : pages
File Size : 50,80 MB
Release : 1985
Category :
ISBN :

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Existing self-tuners are reported to operate well for processes in which the parameters are constant but unknown. However, most industrial processes exhibit time-varying, nonlinear, and multivariable behaviour. This paper documents the theoretical development of a multivariable self-tuner, its implementation on a minicomputer, and the evaluation of its performance on a pilot plant. The multivariable self-tuner combines a recursive least-squares estimator with a pole-assignment, error-actuated controller. The basic algorithm for the estimator is extended to incorporate a variable forgetting factor in a multivariable context. This achieves a balance of the information in the estimator and ensures that, at each calculation step, the estimation is based on a constant amount of information. Hence, the estimates converge more rapidly and are more consistent. Furthermore, the algorithm prevents the covariance matrix from blowing-up, and permits the estimator to retain its ability to adapt to slow or to sudden changes in the plant dynamics. The information content of the estimator and the variable forgetting factor are scalar quantities, but the estimation error decouples the way these quantities affect their respective loops in the process. The reference-tracking controller sacrifices optimum performance in favour of robustness and generality of application, but retains the same self-tuning properties as controllers based on optimum control. The results of real-time control experiments indicate that the application of modified self-tuning methods to a system exhibiting multivariable, nonlinear, and time-varying dynamics yields satisfactory control performance.

Author : R. Koziol
Publisher : Elsevier
Page : 215 pages
File Size : 32,84 MB
Release : 2013-10-22
Category : Technology & Engineering
ISBN : 0080934625

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The electromechanical systems employed in different branches of industry are utilized most often as drives of working machines which must be fed with electric energy in a continuous, periodic or even discrete way. Some of these machines operate at constant speed, others require wide and varying energy control. In many designs the synchronous cooperation of several electric drives is required in addition to the desired dynamic properties. For these reasons the control of the cooperation and dynamics of electromechanical systems requires the use of computers.This book adopts an unusual approach to the subject in that it treats the electric drive system on the one hand as an element of a control system and on the other as an element of a complex automatic system. These two trends in the development of the automatic control of electric drives have resulted in a volume that provides a thorough overview on the variety of different approaches to the design of control systems.