In [14], the method of designing type-2 fuzzy neural adaptive (inverse) controller has been studied in order to control on-line an example of a nonlinear dynamical system of flying robot.
The modified algorithms are applied successfully to control on-line the temperature of an electric oven.
To solve this problem, we propose a novel control framework that integrates the concepts of self-tuning control, on-line experiments, and linear discriminant analysis (LDA).
The proposed control scheme has its philosophical basis established in simultaneous time frequency control, on-line system identification, and adaptive control.
However, very little effort has been put into designing feedback laws to close the loop and control on-line adaptation to achieve desired performance.
The superiority of microfluidic reaction with regard to precise synthetic-condition control, on-line sample characterization, as well as parallel operation has been demonstrated based on the study of CdSe, CdS, and so on [12].
The good prediction of the ANN model, as well as the optimized data using ANNi-GAs, makes it possible to control on-line the operation of the system, increasing the value of COP.
Having its philosophical bases established in simultaneous time-frequency control, on-line system identification, and adaptive control, the chaos synchronization scheme incorporates multiresolution analysis, adaptive filters, and filtered-x Least Mean Square algorithm as its physical features.
An analytical method based on near infrared (NIR) spectroscopy was developed as a PAT tool to control on-line an API (active pharmaceutical ingredient) manufacturing crystallization step during which the API and residual solvent contents need to be precisely determined to reach the predefined seeding point.
This allows for flexible control, on-line correction, and coordination of movements [2].
This thus provides a possibility for an OPT to be controlled on-line during operation.
