When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participa...

Abstract--This paper addresses the feedforward/output feedback control problem for single-input singleoutput minimum-phase nonlinear processes. Combination of dynamic feedforward/static state feedback laws and state observers is employed to synthesize nonlinear dynamic feedforward/output feedback controllers that completely eliminate the effect of measurable disturbances and induce a desired in...

The present study tested two hypotheses about apraxia of speech (AOS), framed in the DIVA model (Guenther, Ghosh, & Tourville, 2006). The DIVA model assumes that speech targets are regions in auditory space, and combines two mechanisms to reach those targets: feedback control and feedforward control. The Feedforward System Deficit (FF) hypothesis states that feedforward control is impaired in A...

Process adjustment strategy is an important part of the process improvement methods, which is also called engineering process control (EPC), and it is often integrated with statistical process control (SPC) to improve the process control performance. While feedback control is used to compensate for the output deviation, feedforward control is a proactive control strategy based on a direct measu...

In this paper, we propose a feedforward compensation method to enhance the performance of the lateral guidance system of heavy vehicles on automated highway systems (AHS). The feedforward controller blends well with the linear robust feedback controller. The proposed feedforward compensation is motivated by the analogy between a vehicle lateral control system on curved roads and a mechanical sy...

A model-based design and tuning procedure is proposed for feedforward controllers, which accounts for model uncertainties in SISO systems. Proper relationships for the analysis of feedforward–feedback control systems show that tuning the feedforward controller is not completely independent from the feedback-loop spectral characteristics. Similarly, fine tune of the associated feedback controlle...

It is often assumed that the action of cortical feedback connections is slow and modulatory, whereas feedforward connections carry a rapid drive to their target neurons. Recent results from our laboratory showed a very rapid effect of feedback connections on the visual responses of neurons in lower order areas. We wanted to determine whether such a rapid action is mediated by fast conducting ax...

One of the well-known recurrent neural networks is the Elman network. Recently, it has been used in applications of system identification. The network has feedforward and feedback connections. It can be trained essentially as a feedforward network by means of the basic backpropagation algorithm, but its feedback connections have to be kept constant. For training success, it is important to sele...

We demonstrate the advantages of feedforward loops using a Boolean network, which is one of the discrete dynamical models for transcriptional regulatory networks. After comparing the dynamical behaviors of network embedded feedback and feedforward loops, we found that feedforward loops can provide higher temporal order (coherence) with lower entropy (randomness) in a temporal program of gene ex...