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Energy flow control system based on neural compensator in the feedback path for autonomous energy source

Grzesiak L.M., Sobolewski J.

Bulletin of the Polish Academy of Sciences. Technical Sciences

2006

Vol. 54, nr 3

335-340

In this paper an artificial neural network, which realizes a nonlinear adaptive control al-gorithm, has been applied in a control system of variable speed generating system. The speed is adjusted automatically as a function of load power demand. The controller employs a single layer neural network to estimate the unknown plant nonlinearities online. Optimization of the controller is difficult because the plant is nonlinear and no stationary. Furthermore, it deals with the situation where the plant becomes uncontrollable without any restrictive assumptions. In contrast to previous work [1] on the same subject, the number of neural networks has been reduced to only one network. The number of the neurons in a network structure as well as choosing certain design parameters was specified a priori. The computer test results have been presented to show performance of proposed neural controller.

Use of neural networks for dynamic modelling and predictive control of power plant systems

Lazar C., Carari S., Vrabie D., Ivana D.

Systems Science

2005

Vol. 31, no 1

37-44

Boiler drum is a critical power plant component having nonlinearities and a non-minimum phase response but, despite this fact, control structures with PID controllers are usually used in industrial applications. In the last decades, important efforts have been made to improve the closed loop performance of the drum level controller by using on-line self-tuning approaches. In this paper, such a method of on-line adaptation is presented based on a neuro-predictive technique of the authors of [4], [5]. In order to implement the neuro-predictive procedure a neural model was developed for drum level process. By means of simulation, a comparison between the obtained drum level controller's operation and that of a classic controller of the type PI under similar conditions is carried out.