Nonlinear Control in Changing Operating Conditions
| Author: | Juuso Esko, University of Oulu, Finland |
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| Topic: | 3.2 Cognition and Control ( AI, Fuzzy, Neuro, Evolut.Comp.) |
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| Session: | Soft Computing for Control |
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| Keywords: | adaptive control, nonlinear control, predictive control, intelligent control, model-based control, fuzzy set systems, multivariable systems |
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Abstract
Operating conditions are often changing so strongly that the changes in nonlinearities must be taken into account. A practical solution comprises several intelligent systems: intelligent analyzers make the adaptation easier by providing informative measurements for the controller, and high-level control supervises the adaptation procedure. Linguistic equation (LE) controllers combine various control strategies, and their compact matrix-based implementation is essential in building multilevel control systems including adaptation, prediction and several control strategies. Dynamic simulation with LE models is a very fast and reliable method for controller tuning. Applications provide good examples of a smart adaptive application consisting of practical and interactive small-scale intelligent systems.
