Nonlinear Model Based Process Control

by R. Berber (Editor), Costas Kravaris (Editor)

Overview

The ASI on Nonlinear Model Based Process Control (August 10-20, 1997~ Antalya - Turkey) convened as a continuation of a previous ASI which was held in August 1994 in Antalya on Methods of Model Based Process Control in a more general context. In 1994, the contributions and discussions convincingly showed that industrial process control would increasingly rely on nonlinear model based control systems. Therefore, the idea for organizing this ASI was motivated by the success of the first one, the enthusiasm expressed by the scientific community for continuing contact, and the growing incentive for on-line control algorithms for nonlinear processes. This is due to tighter constraints and constantly changing performance objectives that now force the processes to be operated over a wider range of conditions compared to the past, and the fact that many of industrial operations are nonlinear in nature. The ASI intended to review in depth and in a global way the state-of-the-art in nonlinear model based control. The list of lecturers consisted of 12 eminent scientists leading the principal developments in the area, as well as industrial specialists experienced in the application of these techniques. Selected out of a large number of applications, there was a high quality, active audience composed of 59 students from 20 countries. Including family members accompanying the participants, the group formed a large body of92 persons. Out of the 71 participants, 11 were from industry.

Product Details

ISBN-13:	9789401061407
Publisher:	Springer Netherlands
Publication date:	02/12/2012
Series:	NATO Science Series E: , #353
Edition description:	Softcover reprint of the original 1st ed. 1998
Pages:	896
Product dimensions:	6.10(w) x 9.25(h) x 0.07(d)

Table of Contents

I. Nonlinear Control Based on Linear Models.- Practical Approaches to Nonlinear Control: A Review of Process Applications.- Multiple Model Adaptive Control (MMAC): Using a Bank of Linear Models to Control a Nonlinear System.- Self-scheduling MPC using LPV models.- II. Nonlinear Model Based Controller Synthesis.- Insights into the Relationships between Linear and Nonlinear Model Based Control and Issues for Further Research.- Nonlinear Model-Based Control of Nonminimum-Phase Processes.- Nonlinear Model-Algorithmic Control: A Review and New Developments.- Windup and Directionality Compensation in Nonlinear Model-Based Control.- Internally Stable Linear and Nonlinear Algorithmic Internal Model Control of Unstable Systems.- Approximate I/O-Linearization of Nonlinear Systems.- Elementary Nonlinear Decoupling (END), A General Approach to Model Based Control of Nonlinear Multivariable Processes.- Control of Nonlinear Differential Algebraic Equation Systems: An Overview.- Promises and Limitations of Functional Expansions in Model-Based Control.- Nonlinear Feedback Control of Parabolic PDE Systems.- III. On-line Optimization Approaches for Nonlinear Control.- Contractive Model Predictive Control with Local Linearization for Nonlinear Systems.- Feedback Linearization + Contractive MPC: Stability Analysis / Application to a Polymerization Process.- Nonlinear Model Predictive Control Schemes with Guaranteed Stability.- A Computationally Efficient Nonlinear Model Predictive Control Algorithm with Guaranteed Stability.- Optimization Approaches to Control-Integrated Design of Industrial Batch Reactors.- IV. Nonlinear State and Parameter Estimation.- Software Sensors and Adaptive Linearizing Control of Bioreactors.- Input Sequences for Nonlinear Modeling.- Towards Multiscale Dynamic Data Reconciliation.- Multi-Scale Aspects in Linear and Nonlinear Estimation and Control.- V. Industrial Applications.- Nonlinear Control with Linear Controllers: Transformations, Calculated Gains and Model Scheduling.- Control of a Steam Boiler by Elementary Nonlinear Decoupling (END).- Reduction of PVC Batch Time by Optimal Control of Free Radical Concentration.- Kappa Number Profile Control for Continuous Digesters.- Artificial Neural Networks for Nonlinear Control of Industrial Processes.- Appendices.- I. Titles of Poster Presentations.- II. Keeping up with Tradition: Lectures and Events at the Workshop - A Cartoon Summary.- III. List of Participants.- IV. Group Picture of all Participants.- V. Group Picture of Main Lecturers and Invited Contributors.

Editorial Reviews

The August 1997 workshop convened as a continuation of a previous ASI held in August 1994 on methods of model based process control. The 27 papers are arranged in five parts covering the major themes presented at the workshop. The questions of how to use linear models to effectively control nonlinear processes is addressed first. Classical gain scheduling techniques are reviewed, followed by two new approaches which involve multiple models. The second part on nonlinear model based controller synthesis methods includes investigations of stability, robustness, constraint handling, and non- minimum phase issues on recent and new approaches, as well as new classes of problems. Emphasizing constraint handling and stability issues, part III covers on line optimization approaches. Part IV treats nonlinear state and parameter estimation, which are significant for the development of a reliable model. Industrial implementations of nonlinear model based control are grouped into the final part. Annotation c. by Book News, Inc., Portland, Or.

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