On Computing the Equilibrium of the Averaged System for the Self-Tuning Regulator

1990 ◽  
Author(s):  
Stephen Phillips ◽  
Robert Kosut
Keyword(s):  
The Self ◽  
Self Tuning

scholarly journals Brane cosmology and the self-tuning of the cosmological constant

2019 ◽  
Vol 2019 (10) ◽  
pp. 007-007 ◽  
Author(s):  
A. Amariti ◽  
C. Charmousis ◽  
D. Forcella ◽  
E. Kiritsis ◽  
F. Nitti
Keyword(s):  
Cosmological Constant ◽  
The Self ◽  
Brane Cosmology ◽  
Self Tuning

Generalisation of the self-tuning regulator

1975 ◽  
Vol 11 (2) ◽  
pp. 40 ◽  
Author(s):  
D.W. Clarke ◽  
P.J. Gawthrop
Keyword(s):  
The Self ◽  
Self Tuning

A study on water level control of PWR steam generator at low power and the self-tuning of its fuzzy controller

1995 ◽  
Vol 74 (1) ◽  
pp. 43-51 ◽  
Author(s):  
Nanju Na ◽  
Keechoon Kwon ◽  
Changshik Ham ◽  
Zeungnam Bien
Keyword(s):  
Low Power ◽  
Water Level ◽  
Steam Generator ◽  
Fuzzy Controller ◽  
The Self ◽  
Level Control ◽  
Self Tuning

Control of piezoelectric friction dampers in smart base-isolated structures using self-tuning and adaptive fuzzy proportional–derivative controllers

2016 ◽  
Vol 28 (10) ◽  
pp. 1287-1302 ◽  
Author(s):  
Abbas-Ali Zamani ◽  
Saeed Tavakoli ◽  
Sadegh Etedali
Keyword(s):  
Control Strategies ◽  
Near Field ◽  
The Self ◽  
Feedback Signal ◽  
Far Field ◽  
Friction Dampers ◽  
Adaptive Fuzzy ◽  
Self Tuning ◽  
Base Displacement ◽  
Proportional Derivative Controller

To adjust the contact force of piezoelectric friction dampers for a benchmark base-isolated structure, a self-tuning fuzzy proportional–derivative controller and an adaptive fuzzy proportional–derivative controller are developed. Considering three candidate signals, namely, the isolation displacement, isolation velocity, and roof acceleration, the best feedback signal for the self-tuning fuzzy proportional–derivative controller is selected based on the Pareto-optimal front. The performance of the self-tuning fuzzy proportional–derivative controller during both near-field and far-field earthquakes is enhanced using an adaptive fuzzy proportional–derivative controller, in which the output gain of the self-tuning fuzzy proportional–derivative controller is adaptively tuned according to the kind of entering earthquake. The control objective is to reduce the isolation system deformations without significant increase in superstructure accelerations during far-field and near-field earthquake excitations. Membership functions and fuzzy control rules are simultaneously tuned using a multi-objective cuckoo search algorithm. Considering 14 real-data earthquakes, simulation results show that the proposed controllers perform better than other reported control strategies in terms of simultaneous reduction of the maximum base displacement and superstructure accelerations. Also, they provide acceptable responses in terms of the inter-story drifts, root mean squared of base displacement, and the floor acceleration. Opposite to other reported control strategies, piezoelectric friction dampers controlled by the self-tuning fuzzy proportional–derivative controller and adaptive fuzzy proportional–derivative controller never enter the saturation area.

scholarly journals A Simulation Study on the Optimal Control of Lock and Dam Gate Openings by the Self-Tuning Controller

1987 ◽  
Vol 31 ◽  
pp. 299-304
Author(s):  
Reynaldo R. Medina ◽  
Kenji Jinno ◽  
Toshihiko Ueda ◽  
Akira Kawamura
Keyword(s):  
Optimal Control ◽  
Simulation Study ◽  
The Self ◽  
Self Tuning

Positioning System with Progressive Wave-Type Ultrasonic Motor under Self-Tuning Fuzzy Control

1995 ◽  
Vol 7 (1) ◽  
pp. 63-68 ◽  
Author(s):  
Junji Fukumi ◽  
◽  
Takuya Kamano ◽  
Takayuki Suzuki ◽  
Yu Kataoka ◽  
...  
Keyword(s):  
Feedback Loop ◽  
Fuzzy Controller ◽  
Lower Layer ◽  
Tracking Error ◽  
Ultrasonic Motor ◽  
The Self ◽  
Positioning System ◽  
Wave Type ◽  
Nonlinear Characteristics ◽  
Self Tuning

This paper considers the use of a self-tuning fuzzy controller for a positioning system with a progressive wavetype ultrasonic motor. The system consists of a feedback loop with a conventional controller and a self tuning fuzzy controller. The objective of the self tuning fuzzy controller is to restrain the adverse effect of nonlinear characteristics of the motor and to improve the tracking performance. The self-tuning fuzzy controller is functionally divided into two layers. The fuzzy rules are automatically adjusted by a tuning algorithm so that the tracking error is minimized in the upper layer. In lower layer, the output signal of the self tuning fuzzy controller is obtained by fuzzy reasoning procedure. After the tuning process is completed, the tracking error almost converges to zero, and the ultrasonic motor is no longer controlled by the fixed gain feedback controller but by the self-tuning fuzzy controller. The effectiveness of the proposed self-tuning fuzzy controller is demonstrated by an experiment.

Experimental Study of Active Vibration Control of a Flexible Beam System Using Iterative Learning Algorithm

2015 ◽  
Vol 660 ◽  
pp. 356-360 ◽  
Author(s):  
Mohd Sazli Saad ◽  
Hishamuddin Jamaluddin ◽  
Intan Zaurah Mat Darus ◽  
Irfan Abd Rahim
Keyword(s):  
Learning Algorithm ◽  
Active Vibration Control ◽  
Iterative Learning ◽  
The Self ◽  
Flexible Beam ◽  
Beam System ◽  
Control Schemes ◽  
Self Tuning ◽  
Active Vibration ◽  
Flexible Beam System

Experimental studies are conducted on active vibration control using self-tuning proportional integral derivative and self-tuning proportional iterative learning algorithm control schemes to suppress vibration on a flexible beam via real-time computer control. An experimental rig is developed to investigate controller performance when a change in the dynamic behavior of the flexible beam system occurs. The performance of the self-tuning control schemes is validated experimentally and compared with that of conventional control schemes through the use of an iterative learning algorithm. Experimental results clearly reveal the effectiveness and robustness of the self-tuning control schemes over conventional control schemes.

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