A Nonlinear Adaptive Controller: A Comparison between Fuzzy Logic Control and Neurocontrol

This paper explores, from a surface-fitting viewpoint, two algorithmswhich are often applied in the field intelligent control: fuzzyself-organizing controllers and neural networks. Both methodologiesadapt internal model parameters in response to the plant's input-outputmapping. However, while the convergence of single-layer neuralnetworks has been studied in great detail, very few theoremshave been proved about self-organizing fuzzy logic controllers.In this paper, it is shown that B-splines can provide a frameworkfor choosing the shape of the fuzzy sets. Then the operatorschosen to implement the underlying fuzzy logic are examined,showing how they can produce ‘smooth’ control surfaces.It is now possible to make a direct comparison between fuzzylogic controllers and feedforward neural networks, demonstratingthat, in a forward-chaining mode, storing the plant's behaviourin terms of weights or rule confidences is equivalent. Finally,three training rules for the self-organizing fuzzy controllerare derived.     

The Approximation of a Composite B?zier Cubic Curve by a Composite B?zier Quadratic Curve

In the context of the computer representation of textual characters,we describe an algorithm for approximating a composite B?ziercubic curve by a composite B?rier quadratic curve. The knotsor breakpoints of the approximating function are determinedsuch that the error of approximation does not exceed a specifiedvalue. The number of breakpoints, and hence the number of arcsof the approximation, is not in general optimal but can be expectedto be ‘small’. The work is clearly relevant alsoto other application areas.     

Molecular Dynamics simulation of aqueous ZnC12 solutions

An important medium for ore transport within the Earth is by hydrothermal fluids. To understand ore transportation processes by hydrothermal fluids it is necessary to determine the clustering of dissolved ionic species in aqueous solution. We have chosen sphalerite, an important zinc containing mineral, as an example. We describe the results of Molecular Dynamics simulations to predict which chlorozinc complexes will occur at the pressures and temperatures found in the Earth's crust. Potentials have been derived for zinc-water and zinc-chloride interactions using density functional calculations. Although the DFT calculations provide good gas-phase clusters, the resulting potentials do not work well when modelling aqueous solutions. We therefore describe attempts to modify the potential to compensate for these effects. We show that at low chloride concentrations the dominant species are Zn(H₂O)²⁺ ₆, and ZnC1(H₂O)⁺ ₅. At higher temperatures there are a significant number of clusters which contain more than one zinc with bridging chloride ions. In aqueous solutions with a high chloride concentration the dominant species are Zn(H₂O)²⁺ ₆, ZnC1₂(H₂O)⁰ ₄ and ZnC1₃(H₂O)^? ₃. There are almost no clusters containing more than one zinc.