Feed forward (control)

This requires a mathematical model of the system so that the effect of disturbances can be properly predicted.

[3] Some prerequisites are needed for control scheme to be reliable by pure feed-forward without feedback: the external command or controlling signal must be available, and the effect of the output of the system on the load should be known (that usually means that the load must be predictably unchanging with time).

In contrast, 'cruise control' adjusts the output in response to the load that it encounters, by a feedback mechanism.

With feed-forward or feedforward control, the disturbances are measured and accounted for before they have time to affect the system.

If the driver is included in the system, then they do provide a feedback path by observing the direction of travel and compensating for errors by turning the steering wheel.

[7][8] Historically, the use of the term feedforward is found in works by Harold S. Black in US patent 1686792 (invented 17 March 1923) and D. M. MacKay as early as 1956.

While MacKay's work is in the field of biological control theory, he speaks only of feedforward systems.

MacKay and other early writers who use the term feedforward are generally writing about theories of how human or animal brains work.

[9] Black also has US patent 2102671 invented 2 August 1927 on the technique of feedback applied to electronic systems.

The discipline of feedforward controls was largely developed by professors and graduate students at Georgia Tech, MIT, Stanford and Carnegie Mellon.

Meckl and Seering of MIT and Book and Dickerson of Georgia Tech began the development of the concepts of Feedforward Control in the mid-1970s.

The discipline of Feedforward Controls was well defined in many scholarly papers, articles and books by the late 1980s.

[7][10][11][12] The benefits of feedforward control are significant and can often justify the extra cost, time and effort required to implement the technology.

Other benefits of feedforward control include reduced wear and tear on equipment, lower maintenance costs, higher reliability and a substantial reduction in hysteresis.

[16] Control systems capable of learning and/or adapting their mathematical model have become more practical as microprocessor speeds have increased.

[citation needed] In physiology, feed-forward control is exemplified by the normal anticipatory regulation of heartbeat in advance of actual physical exertion by the central autonomic network.

Feed-forward control can be likened to learned anticipatory responses to known cues (predictive coding).

Feedback regulation of the heartbeat provides further adaptiveness to the running eventualities of physical exertion.

Feedforward systems are also found in biological control of other variables by many regions of animals brains.

[citation needed] Even in the case of biological feedforward systems, such as in the human brain, knowledge or a mental model of the plant (body) can be considered to be mathematical as the model is characterized by limits, rhythms, mechanics and patterns.

Feed-forward loops (FFLs), a three-node graph of the form A affects B and C and B affects C, are frequently observed in transcription networks in several organisms including E. coli and S. cerevisiae, suggesting that they perform functions that are important for the functioning of these organisms.

Kalir, Mangan, and Alon, 2005 show that the regulatory system for flagella in E. coli is regulated with a Type 1 coherent feedforward loop.

[24] For instance, the regulation of the shift from one carbon source to another in diauxic growth in E. coli can be controlled via a type-1 coherent FFL.

Diauxic growth in glucose and lactose is regulated by a simple regulatory system involving cAMP and the lac operon.

This prevents the cell from shifting to growth on arabinose based on short term fluctuations in glucose availability.

Incoherent feedforward loops, in which the two paths from the input to the output node have different signs result in short pulses in response to an ON signal.

In this system, input A simultaneous directly increases and indirectly decreases synthesis of output node C. If the indirect path to C (via B) is slower than the direct path a pulse of output is produced in the time period before levels of B are high enough to inhibit synthesis of C. Response to epidermal growth factor (EGF) in dividing mammalian cells is an example of a Type-1 incoherent FFL.

Several theoretical and experimental studies including those discussed here show that FFLs create a mechanism for biological systems to process and store information, which is important for predictive behavior and survival in complex dynamically changing environments.

In computing, feed-forward normally refers to a perceptron network in which the outputs from all neurons go to following but not preceding layers, so there are no feedback loops.

In the early 1970s, intercity coaxial transmission systems, including L-carrier, used feed-forward amplifiers to diminish linear distortion.