Trajectory tracking control is used to effect desired trajectories of a device. In order to more precisely track specified trajectories, or be able to follow more general trajectories, many tracking control algorithms have been proposed. A representative cross-section of these schemes, and their implementations are discussed. A flexible robotic tracking control testbed has been developed which allows implementation of the various schemes.
The influence of grain size on the mechanical properties and limit strains of materials has been studied in the tensile test, hydraulic bulging and in-plane stretching, using 1.0-mm thick brass, aluminium and steel sheets. The limit strains of the materials, as well as the mechanical properties of the brass sheets, were found to be closely related to the square root of the grain diameter. The values of the uniaxial work-hardening exponent for the brass, aluminium and St1403 steel were found to be larger than the biaxial -values. The results of the limit strains obtained from in-plane stretching and hydraulic bulging were found to be related.
This paper proposes a model for the growth of flank wear in milling. It incorporates the predominant mechanisms of wear which are abrasion and diffusion and also accounts for thermal fatigue and the effect of the number of teeth. The results obtained are compared to actual data and are shown to be in good agreement.
This paper concerns to the influence of tool wear and shape accuracy on different tool engagements, resulting from milling of threedimensional contours. The aim is to achieve cutting conditions depending on the contour. The results obtained shall be considered at creation of the milling paths, concerning proper to geometrical and technological cutting conditions. The possibilities of 3- and 5-axes milling and modern cutting materials for die and mould manufacturing are discussed. CAD/CAM-systems used today operate only by means of geometry. This process can be optimized, if these systems consider the cutting conditions too.
This paper presents three cluster-seeking algorithms - K-means, Revised K-means and Isodata - for formation of part families and machine cells. These algorithms are based on the concept of pattern recognition and are capable of producing variable size, mutually independent groups of parts and/or machines without excluding exceptional components. These algorithms are compared with existing grouping algorithms, and examples are used to demonstrate the effect of clustering criteria on the final solutions. It has been found that the Isodata algorithm is more efficient and more flexible than existing machine/components matrix manipulation techniques.
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