An adaptive controller is presented that is able to perform effectively in the presence of nonlinearities and of model uncertainty typical of industrial processes. The controller incorporates a minimum variance part and a caution part. The latter is independent of the estimated model and becomes dominant in the case of a large mismatch between plant and estimated model. Application to a simulated nonlinear continuous stirred-tank reactor demonstrates its effectiveness, even when other adaptive controllers give unsatisfactory performance.
If you can't find a tool you're looking for, please click the link at the top of the page to "Go to old article view". Alternatively, view our Knowledge Base articles for additional help. Your feedback is important to us, so please let us know if you have comments or ideas for improvement.