This paper focuses on viable position estimation schemes for timing belt drives where the position of the carriage (load) is to be calculated via reference models accepting input from a position sensor on the actuator of the timing belt. A detailied analysis on the source of transmission errors is presented a number of relevant mathematical modeis are developed utilizing a priori knowledge on the process. The paper illustrates that such schemes are very effective when the drive system is not subjected to external loads es well as widely changing operating conditions such as ambient temperature, belt tension.
The accurate contral of CNC machine axis requires relatively expensive direct measurement sensors. In this paper, artificial neural network based position error estimators are comparatively evaluated as a part of a low-cost (but high performance) manufacturing system. Such schemes are very effective when the system is rot subjected to external loads as well as widely changing operating conditions such as ambient temperature.
Due to significant advancements in optical navigation technology, optical mouse sensors (OMS) are increasingly employed as low-cost motion sensora in personal computing and robot navigation. This paper proposes a new test bed to study the long-term measurement characteristics of emerging OMS devices. With the utilization of this set-up, the attributes of a high-resolution OMS (Agilent ADNS-2051) are investigated under various critical operating conditions like changing surface velocity and the pattern. The paper illustrates that despite the problems addressed, the positioning accuracy of an OMS could be quite sufficient for some basic process control apptications.
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