feedforward


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feedforward

 [fēd-for´werd]
the anticipatory effect that one intermediate in a metabolic or endocrine control system exerts on another intermediate further along in the pathway; such effect may be positive or negative.

feedforward

/feed-for·ward/ (fēd-for´ward) the anticipatory effect that one intermediate in a metabolic or endocrine control system exerts on another intermediate further along in the pathway; such effect may be positive or negative.

feedforward

(fēd″for′wĭrd)
Anticipatory motor impulses sent before movement to prepare the musculoskeletal system for postural adjustments. The feedforward mechanism is thought to help prepare muscles to perform required tasks.

feedforward

the anticipatory effect that one intermediate in a metabolic or endocrine control system exerts on another intermediate further along in the pathway; such effect may be positive or negative.
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References in periodicals archive ?
q]) and the feedforward compensatory currents [mathematical expression not reproducible].
With each model change, the controller must be recalibrated and redeployed, which may involve adjustments to both the feedforward and feedback portions of the controller.
Applying the feedforward network yielded already satisfying classification performance, however the network lacks a possibility to reproduce on what basis classification decisions are made, as it is not focused on proving that results lie in certain confidence intervals [14].
where the superscripts * and FF denote the target (set-point) values and the feedforward command values.
As shown in the graph, the BP neural network is generally referred to the three layer feedforward network or the three layer perceptron.
1 depicts the general scheme for feedforward control along with feedback trim, but can be called a hybrid structure since it can be used as a control scheme for plant structures with and without [P.
Jiang, "Multiple-targets tracking algorithm for a class of nonlinear systems with feedforward compensations," Neurocomputing, vol.
A fault diagnosis system was presented by Bayir and Bay for a serial wound starter motor based on a multilayer feedforward artificial neural network [12].
Extreme Learning Machine (ELM) [16] is a useful learning model for training single hidden layer feedforward networks (SLFNs).
The case of the combination of dynamic output feedback with feedforward reference compensation (also referred to as two-degee-of-freedom dynamic compensation) was studied in [22] and [29].
On the other hand, compliant locomotion strategies permit excellent control of interaction forces, yet require accurate feedforward planning and control to achieve comparable tracking performance.