Parallel loop recovery with quiescent compensation for high performance feedback control of systems with imperfect actuators

2019 ◽  
Vol 17 (3) ◽  
pp. 201-215
Author(s):  
Y. V. O’Brien ◽  
J. F. O’Brien
Keyword(s):  
Feedback Control ◽  
Performance Feedback ◽  
High Performance ◽  
Parallel Loop

Concurrent Design of Vibration Absorbers and Input Shapers

2004 ◽  
Vol 127 (3) ◽  
pp. 329-335 ◽  
Author(s):  
Joel Fortgang ◽  
William Singhose
Keyword(s):  
Feedback Control ◽  
Computer Simulations ◽  
Performance Feedback ◽  
High Performance ◽  
Experimental Results ◽  
Input Shaping ◽  
Concurrent Design ◽  
Vibration Absorbers ◽  
External Disturbances

Systems with flexible dynamics often vibrate due to external disturbances, as well as from changes in the reference command. Feedback control is an obvious choice to deal with these vibrations, but in many cases, it is insufficient or difficult to implement. A technique that does not rely on high performance feedback control is presented here. It utilizes a combination of vibration absorbers and input shapers. Vibration absorbers have been used extensively to reduce vibration from sinusoidal disturbances, but they can also be implemented to reduce the response from transient functions. Input shaping has proven beneficial for reducing vibration that is caused by changes in the reference command. However, input shaping does not deal with vibration excited by external disturbances. In this paper, vibration absorbers and input shapers are designed sequentially and concurrently to reduce vibration from both the reference command and from external disturbances. The usefulness of this approach is demonstrated through computer simulations and experimental results.

Chaos Control in Single Mode Approximation of T-AFM Systems Using Nonlinear Delayed Feedback Based on Sliding Mode Control

2007 ◽  
Author(s):  
Hoda Sadeghian ◽  
Mehdi Tabe Arjmand ◽  
Hassan Salarieh ◽  
Aria Alasty
Keyword(s):  
Feedback Control ◽  
High Performance ◽  
Sliding Mode ◽  
Chaotic Behavior ◽  
Single Mode ◽  
Delayed Feedback ◽  
Delayed Feedback Control ◽  
Model Parameters ◽  
Unstable Periodic Orbits ◽  
Single Mode Approximation

The taping mode Atomic Force Microscopic (T-AFM) can be properly described by a sinusoidal excitation of its base and nonlinear potential interaction with sample. Thus the cantilever may cause chaotic behavior which decreases the performance of the sample topography. In this paper a nonlinear delayed feedback control is proposed to control chaos in a single mode approximation of a T-AFM system. Assuming model parameters uncertainties, the first order Unstable Periodic Orbits (UPOs) of the system is stabilized using the sliding nonlinear delayed feedback control. The effectiveness of the presented methods is numerically verified and the results show the high performance of the controller.

Nonlinear Compensation for High Performance Feedback Systems With Actuator Imperfections

2013 ◽  
Author(s):  
Cameron L. Mock ◽  
Zachary T. Hamilton ◽  
Dustin Carruthers ◽  
John F. O’Brien
Keyword(s):  
Performance Feedback ◽  
High Performance ◽  
Vibration Suppression ◽  
Actuator Saturation ◽  
Design Method ◽  
Nonlinear Feedback ◽  
Feedback Systems ◽  
Performance Requirements ◽  
Common Causes ◽  
And Performance

Measures to reduce control performance for greater robustness (e.g. reduced bandwidth, shallow loop roll-off) must be enhanced if the plant or actuators are known to have nonlinear characteristics that cause variations in loop transmission. Common causes of these nonlinear behaviors are actuator saturation and friction/stiction in the moving parts of mechanical systems. Systems with these characteristics that also have stringent closed loop performance requirements present the control designer with an extremely challenging problem. A design method for these systems is presented that combines very aggressive Nyquist-stable linear control to provide large negative feedback with nonlinear feedback to compensate for the effects of multiple nonlinearities in the loop that threaten stability and performance. The efficacy of this approach is experimentally verified on a parallel kinematic mechanism with multiple uncertain nonlinearities used for vibration suppression.

scholarly journals The role of performance feedback consistency in aspiration level adaptation: Evidence from a European grocery retailer

2019 ◽  
Vol 45 (1) ◽  
pp. 18-29
Author(s):  
Burak Cem Konduk
Keyword(s):  
Performance Feedback ◽  
High Performance ◽  
Past Research ◽  
Aspiration Level ◽  
Performance Targets ◽  
Aspiration Levels ◽  
Organizational Attention ◽  
And Performance ◽  
The Impact

This study investigates whether and how the impact of drivers of aspiration levels changes across the cases of consistent and inconsistent performance feedback within the context of a retailer. Analysis of internal corporate data shows that while past aspiration level and performance–aspiration gap positively influence the current aspiration level in the case of inconsistent feedback, performance feedback consistency changes only the impact of performance relative to peers. This study replicates past research in a different industry and country due to limited empirical evidence, introduces real-world complexity into aspiration theory, pinpoints performance–aspiration gap as the primary performance feedback, introduces a new sign for the impact of performance relative to peers, and reconciles its previously detected mixed impact. The findings suggest that organizational attention has an inward focus in the case of inconsistent feedback. The results also point out that leaders can trigger change through a performance outcome that lags behind the corresponding aspiration level rather than the performance of peers and eventually move their organizations toward high performance targets by starting with feasible rather than stretch goals.

scholarly journals A Quantum-Behaved Neurodynamic Approach for Nonconvex Optimization with Constraints

Algorithms ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 138
Author(s):  
Zheng Ji ◽  
Xu Cai ◽  
Xuyang Lou
Keyword(s):  
Neural Network ◽  
Nonconvex Optimization ◽  
Performance Feedback ◽  
High Performance ◽  
Optimization Problems ◽  
Inequality Constraints ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
Transmission Shaft ◽  
Particle Swarm Method

This paper presents a quantum-behaved neurodynamic swarm optimization approach to solve the nonconvex optimization problems with inequality constraints. Firstly, the general constrained optimization problem is addressed and a high-performance feedback neural network for solving convex nonlinear programming problems is introduced. The convergence of the proposed neural network is also proved. Then, combined with the quantum-behaved particle swarm method, a quantum-behaved neurodynamic swarm optimization (QNSO) approach is presented. Finally, the performance of the proposed QNSO algorithm is evaluated through two function tests and three applications including the hollow transmission shaft, heat exchangers and crank–rocker mechanism. Numerical simulations are also provided to verify the advantages of our method.

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