Chemical engineers assemble the theoretical and practical research on the design, analysis, and application of nonlinear process control strategies, much easier of late because of model- based approaches and more inexpensive and powerful computers. They outline the issues driving the research and several classic techniques, and provide a detailed introduction to nonlinear process modeling. Then they describe the two leading approaches of input/output linearization and nonlinear predictive control, show how to design state observers that permit control even if on-line measurements of all state variables cannot be obtained, and discuss new techniques for developing empirical models using artificial neural networks. Annotation c. by Book News, Inc., Portland, Or.