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Experimental results demonstrate a significant performance improvement in terms of control input variance while maintaining the motion accuracy.
Control input variance is one of the important criteria in machining because it affects the surface roughness, machining precisions and consumed energy.
This paper presents a nonlinear controller design for biaxial feed drive systems for reducing the control input variance while maintaining the motion accuracy.
The controller guarantees stability, and for an input variance of 10%, the average deviation of the temperature from the set point was found to be less that 0.25%.
Hence, we try many experiments with the input variance in the range of [10,70] and choose the best one for each of the algorithms.
Results show that the layout of the merge influences bag throughput and when the physical configuration is in a preferred position, input variance has no effect on bag throughput performance.
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The estimation procedure used was the maximum likelihood based on an input variance-covariance matrix.
RNA input variances were normalized against the levels of the L19 housekeeping gene.
These subplots were used to calculate the input variances for studying the sampling design alternatives (Table 2).
RNA input variances were normalized against the levels of the L19 housekeeping gene, which encodes a ribosomal protein.
Stability and robustness of the proposed controller regarding system inputs variance have also been tested by applying asynchronous setpoints of both inputs of the process.
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