Nonlinear Model Based Process Control -

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Résumé :
The increasingly competitive environment within which modern industry has to work means that processes have to be operated over a wider range of conditions in order to meet constantly changing performance targets. Add to this the fact that many industrial operations are nonlinear, and the need for on-line control algorithms for nonlinear processes becomes clear. Major progress has been booked in constrained model-based control and important issues of nonlinear process control have been solved. The present book surveys the state of the art in nonlinear model-based control technology, by writers who have actually created the scientific profile. A broad range of issues are covered in depth, from traditional nonlinear approaches to nonlinear model predictive control, from nonlinear process identification and state estimation to control-integrated design. Recent advances in the control of inverse response and unstable processes are presented. Comparisons with linear control are given, and case studies are used for illustration.

Sommaire:
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.