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Three books are reviewed: Intuitive Probability and Random Processes Using Matlab by Steven Kay; Relay Feedback: Analysis, Identification and Control by Q.-G. Wang et al.; and Processing Modelling for Control - A Unified Framework Using Standard Black-box Techniques by Benoit Codrons.

A nonlinear controller design for a packed-bed reactor is presented. The scheme employs a two-tier approach in which, first, a low-order nonlinear model is developed and, subsequently, a feedback linearizing control law is synthesized. The reduced-order model treats transport mechanisms in the reactor as a nonlinear wave which propagates through the bed. Application of input−output “linearizing” control yields linear dynamics over a wide range of operating conditions. The practical issues of implementing the resultant digital, implicit, nonlinear control law on an actual system are addressed. Closed-loop simulations are used to illustrate the robustness properties of the nonlinear controller. In addition, the relative strengths of this approach over traditional linear control are identified.

This paper compares the performance of two different inferential schemes when applied to an experimental packed-bed reactor. The first scheme, proposed initially by Brosilow, is designed based on Kalman filter estimation. The second less traditional design uses an estimator computed from the Partial Least Squares regression method (PLS). The second approach was found to give superior performance when the nonlinear system under study is operated is a wide range of operating points. Due to the nonlinearity of the system it is essential to address the issue of robustness of the proposed schemes. This is formally done in this work using Structured Singular Value Theory. For the robustness analysis it is crucial to develop a realistic but not overly conservative uncertainty description. Since the PLS estimator uses a large number of measurements, a robust design based on the uncertainty associated with each one of the measurements would be very conservative. To overcome this problem a lumped uncertainty description is proposed which is identified directly from experiments.