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As such an internal model of first-order fed by the tracking error is constructed.
The serial parallel estimation model is given and a filter error included tracking error and modeling error is constructed to design the weights updating law of neural networks (NNs).
The system uncertainty is approximated by a composite adaptive LWL neural networks (NNs), in which a prediction error is constructed by using a series-parallel identification model, and NN weights are updated by both the tracking error and the prediction error.
To take into account the prediction uncertainty, a probability distribution model of the prediction error is constructed using the kernel density estimation method.
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In order to optimize the parameters of the nonlinear PID controller using ACO algorithm, an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm.
The final model for all traits based on minimizing the mean squared error was constructed from 1200 trees at an interaction depth of 5 and a shrinkage parameter of 0.0075.
Considering that the same features from two neighboring stations coincide after pairwise registration, a dual quaternion-based error norm, which is associated with the sum of the position errors, is constructed.
Finally the objective function (fleft( {x,y,z} right)) representing assessment errors is constructed.
Furthermore, a more general and unified iterative algorithm called the Mann perturbed iterative algorithm with mixed errors is constructed as well in Hilbert spaces.
Then, by utilizing TRMCEs, the mapping relationships between tool path and the numerical control (NC) command without and with considering the geometric errors are constructed respectively.
Specifically, iterative neural updating laws, based on prediction errors, are constructed, which enable the accurate identification of the unknown dynamics for each vehicle, not only in steady state but also in transient state.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com