Analysis of the step and ramp response of a feedback gain-control system

1978 ◽  
Vol 2 (2) ◽  
pp. 47
Author(s):  
G.R. Hoffman
Keyword(s):  
Control System ◽  
Gain Control ◽  
Feedback Gain ◽  
Ramp Response

Suppression of dynamic instabilities in erbium-doped fiber amplifiers with a combined gain control system

2002 ◽  
Vol 27 (13) ◽  
pp. 1117 ◽  
Author(s):  
Sergey V. Sergeyev ◽  
Evgeny Vanin ◽  
Sergei Popov
Keyword(s):  
Control System ◽  
Gain Control ◽  
Fiber Amplifiers ◽  
Erbium Doped

Modal Control of Underactuated Systems

2010 ◽  
Author(s):  
D. Dane Quinn ◽  
Vineel Mallela
Keyword(s):  
Control System ◽  
Mechanical System ◽  
Mechanical Systems ◽  
Degree Of Freedom ◽  
Feedback Gain ◽  
Underactuated Systems ◽  
Modal Control ◽  
Underactuated Mechanical Systems ◽  
Sensors And Actuators ◽  
Sensor Actuator

This work addresses the modal control of underactuated mechanical systems, whereby the number of actuators is less than the degree-of-freedom of the underlying mechanical system. The performance of the control system depends on the structure of the feedback gain matrix, that is, the coupling between sensors and actuators. This coupling is often not arbitrary, but the topology of the sensor-actuator network can be a fixed constraint of the control system. This work examines the influence of this structure on the performance of the overlying control system.

On Selection of Control Parameters for H∞ Output Feedback

2005 ◽  
Author(s):  
Chang-Ching Chang ◽  
Chi-Chang Lin
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Output Feedback ◽  
Delay Time ◽  
Output Feedback Control ◽  
Feedback Gain ◽  
Control Force ◽  
Control Parameters ◽  
Structural Responses ◽  
Control Forces

In this paper, an H∞ direct output feedback control algorithm through minimizing the entropy, a performance index measuring the tradeoff between H∞ optimality and H2 optimality, is employed to design the control system in reducing structural responses due to dynamic loads such as earthquakes. The control forces are obtained from the multiplication of direct output measurements by a pre-calculated time-invariant feedback gain matrix. To achieve optimal control performance, the strategy to select both control parameters γ and α is extensively investigated. The decrease of γ or increase of α results in better control effectiveness, but larger control force requirement. For a single degree-of-freedom (SDOF) damped structure, exact solutions of output feedback gains and control parameters are derived. It can be proved analytically that the LQR control is a special case of the proposed H∞ control. Direct velocity feedback control is effective in reducing structural responses with very small number of sensors and controllers compared with the DOFs of the structure. In active control of a real structure, control force execution time delay cannot be avoided. Relatively small delay time not only can render the control ineffective, but also may cause system instability. In this study, explicit formulas to calculate maximum allowable delay time and critical control parameters are derived for the design of a stable control system. Some solutions are also proposed to increase the maximum allowable delay time.

scholarly journals Rapid visuomotor feedback gains are tuned to the task dynamics

2017 ◽  
Vol 118 (5) ◽  
pp. 2711-2726 ◽  
Author(s):  
Sae Franklin ◽  
Daniel M. Wolpert ◽  
David W. Franklin
Keyword(s):  
Control System ◽  
Force Field ◽  
Feedback System ◽  
Sensorimotor Control ◽  
Motor Memory ◽  
Feedback Gain ◽  
Adaptation Process ◽  
Fourfold Increase ◽  
Lateral Resistance ◽  
Left And Right

Adaptation to novel dynamics requires learning a motor memory, or a new pattern of predictive feedforward motor commands. Recently, we demonstrated the upregulation of rapid visuomotor feedback gains early in curl force field learning, which decrease once a predictive motor memory is learned. However, even after learning is complete, these feedback gains are higher than those observed in the null field trials. Interestingly, these upregulated feedback gains in the curl field were not observed in a constant force field. Therefore, we suggest that adaptation also involves selectively tuning the feedback sensitivity of the sensorimotor control system to the environment. Here, we test this hypothesis by measuring the rapid visuomotor feedback gains after subjects adapt to a variety of novel dynamics generated by a robotic manipulandum in three experiments. To probe the feedback gains, we measured the magnitude of the motor response to rapid shifts in the visual location of the hand during reaching. While the feedback gain magnitude remained similar over a larger than a fourfold increase in constant background load, the feedback gains scaled with increasing lateral resistance and increasing instability. The third experiment demonstrated that the feedback gains could also be independently tuned to perturbations to the left and right, depending on the lateral resistance, demonstrating the fractionation of feedback gains to environmental dynamics. Our results show that the sensorimotor control system regulates the gain of the feedback system as part of the adaptation process to novel dynamics, appropriately tuning them to the environment. NEW & NOTEWORTHY Here, we test whether rapid visuomotor feedback responses are selectively tuned to the task dynamics. The responses do not exhibit gain scaling, but they do vary with the level and stability of task dynamics. Moreover, these feedback gains are independently tuned to perturbations to the left and right, depending on these dynamics. Our results demonstrate that the sensorimotor control system regulates the feedback gain as part of the adaptation process, tuning them appropriately to the environment.

Design and performance of an automatic gain control system for the high-energy x-ray timing experiment

1991 ◽  
Author(s):  
Michael R. Pelling ◽  
Richard E. Rothschild ◽  
Daniel R. MacDonald ◽  
Robert H. Hertel ◽  
Edward S. Nishiie
Keyword(s):  
Control System ◽  
Automatic Gain Control ◽  
Gain Control ◽  
High Energy ◽  
X Ray ◽  
And Performance
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