Recent developments in neural network PID autotuning

PID controllers are widely used in industrial applications. Because the plant can be time variant, methods of autotuning of this type of controllers, are of great economical importance, see (Astrom, 1996). Since 1942, with the work of Ziegler and Nichols (Ziegler and Nichols, 1942), several methods have been proposed in the literature. Recently, a new technique using neural networks was proposed (Ruano et al., 1992). This technique has been shown to produce good tunings as long as certain limitations are met.

Analysis of underwater acoustic data via 3-D segmentation

The analysis of seabed structure is important in a wide variety of scientific and industrial applications. In this paper, underwater acoustic data produced by bottom-penetrating sonar (Topas) are analyzed using unsupervised volumetric segmentation, based on a three dimensional Gibbs-Markov model. The result is a concise and accurate description of the seabed, in which key structures are emphasized. This description is also very well suited to further operations, such as the enhancement and automatic recognition of important structures. Experimental results demonstrating the effectiveness of this approach are shown, using Topas data gathered in the North Sea off Horten, Norway.

Sintonia automática de controladores PID: uma abordagem neuro - genética

Dissertação de dout. em Electrónica e Computação, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2004