scholarly journals Experimental Investigation of Adaptive Control Applied to HSFD Supported Rotors

1999 ◽  
Author(s):  
A. El-Shafei ◽  
M. El-Hakim
Keyword(s):  
Experimental Investigation ◽  
Adaptive Control ◽  
Reference Model ◽  
Computer Control ◽  
Adaptive Controller ◽  
Superior Performance ◽  
Order System ◽  
Squeeze Film ◽  
Run Up ◽  
Model Reference Adaptive

This paper describes the experimental application of adaptive control to Hybrid Squeeze Film Damper (HSFD) supported rotors. The HSFD has been shown to be an adaptive damper capable of providing infinite damper configurations between short and long damper configurations. Previously, theoretical investigations of the adaptive control of HSFD concentrated on the development of the model reference adaptive control (MRAC) method, as well as development of a nonlinear reference model. Simulations of the performance of the adaptive controller during run-up and coast-down indicated the superior performance of the adaptive controller. In this paper, the adaptive controller is tested on a multi-mode rotor. A test rig is designed and developed using computer control. A simple reference model is investigated consisting of a second order system. Three forms for adaptation gain are studied. The results of the experimental investigation illustrated the performance capabilities of the adaptive controller applied to the HSFD, and moreover indicated the possibility of simple design for the adaptive controller.

Experimental Investigation of Adaptive Control Applied to HSFD Supported Rotors

2000 ◽  
Vol 122 (4) ◽  
pp. 685-692 ◽  
Author(s):  
A. El-Shafei ◽  
M. El-Hakim
Keyword(s):  
Experimental Investigation ◽  
Adaptive Control ◽  
Reference Model ◽  
Computer Control ◽  
Adaptive Controller ◽  
Superior Performance ◽  
Order System ◽  
Squeeze Film ◽  
Run Up ◽  
Model Reference Adaptive

This paper describes the experimental application of adaptive control to Hybrid Squeeze Film Damper (HSFD) supported rotors. The HSFD has been shown to be an adaptive damper capable of providing infinite damper configurations between short and long damper configurations. Previously, theoretical investigations of the adaptive control of HSFD concentrated on the development of the model reference adaptive control (MRAC) method, as well as development of a nonlinear reference model. Simulations of the performance of the adaptive controller during run-up and coast-down indicated the superior performance of the adaptive controller. In this paper, the adaptive controller is tested on a multi-mode rotor. A test rig is designed and developed using computer control. A simple reference model is investigated consisting of a second order system. Three forms for adaptation gain are studied. The results of the experimental investigation illustrated the performance capabilities of the adaptive controller applied to the HSFD, and moreover indicated the possibility of simple design for the adaptive controller. [S0742-4795(00)01603-3]

Multimode Adaptive Control for Tank Gun Control System Based on Tracking Differentiator

2011 ◽  
Vol 383-390 ◽  
pp. 79-85
Author(s):  
Dong Yuan ◽  
Xiao Jun Ma ◽  
Wei Wei
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
High Speed ◽  
Control Method ◽  
Reference Model ◽  
Gun Control ◽  
Math Model ◽  
Tracking Differentiator ◽  
Switch Control ◽  
Model Reference Adaptive

Aiming at the problems such as switch impulsion, insurmountability for influence caused by nonlinearity in one tank gun control system which adopts double PID controller to realize the multimode switch control between high speed and low speed movement, the system math model is built up; And then, Model Reference Adaptive Control (MRAC) method based on nonroutine reference model is brought in and the adaptive gun controller is designed. Consequently, the compensation of nonlinearity and multimode control are implemented. Furthermore, the Tracking Differentiator (TD) is affiliated to the front of controller in order to restrain the impulsion caused by mode switch. Finally, the validity of control method in this paper is verified by simulation.

Enhanced Model Reference Adaptive Control Using Smith Predictor

2013 ◽  
Vol 367 ◽  
pp. 363-368
Author(s):  
R. Karthikeyan ◽  
C. Bhargav ◽  
Karthik Koneru ◽  
G. Syam ◽  
Shikha Tripathi
Keyword(s):  
Adaptive Control ◽  
Fuzzy Logic Controller ◽  
Dead Time ◽  
Reference Model ◽  
Model Reference Adaptive Control ◽  
Vital Role ◽  
Smith Predictor ◽  
Model Reference ◽  
Time Effects ◽  
Model Reference Adaptive

The main aim of a control system is to repress the instabilities caused by nonlinearities of the system. Dead time is considered to be one of the most significant nonlinearities of a system. Dead time compensators play a vital role in reducing the dead time effects on the processes only to a minute extent. This paper proposes a method to overcome this problem by using Enhanced Model Reference Adaptive Control (MRAC) incorporating Smith Predictor. MRAC belongs to class of adaptive servo system in which desired performance is expressed with the help of a reference model. Enhanced MRAC consists of a fuzzy logic controller which provides adaptation gain to MRAC without human interference. A dead time compensator incorporated in the enhanced MRAC solves the problem of instabilities caused by dead time to a greater extent.

Design and flight testing of closed-loop simple adaptive control for a biplane micro air vehicle

2019 ◽  
Vol 234 (6) ◽  
pp. 677-689
Author(s):  
Shuvrangshu Jana ◽  
Mayur Shewale ◽  
Susheel Balasubramaniam ◽  
Harikumar Kandath ◽  
M Seetharama Bhat
Keyword(s):  
Adaptive Control ◽  
System Dynamics ◽  
System Performance ◽  
Closed Loop ◽  
Flight Test ◽  
Adaptive Controller ◽  
Micro Air Vehicle ◽  
Plant Performance ◽  
Superior Performance ◽  
Air Vehicle

This article presents the implementation of closed-loop simple adaptive control on fixed-wing micro air vehicle dynamics to improve flight performance characteristics. It is known that to retain the micro air vehicle system performance during the entire flight regime is difficult due to model uncertainties, large parameter variation and wind disturbances compared to flight velocity. An adaptive controller can adapt to the uncertainties but the complexity involved in their implementation is high due to unavailability of required sensor information and computational resources on a micro air vehicle platform. Lack of flight test results in the open literature incorporating adaptive control so far can be partially attributed to this complexity. In this case, adaptive control architecture is implemented in such a way that only the uncertainties in the system dynamics are taken care of by the adaptive control and desired nominal plant performance is achieved by the basic controller. The proposed adaptive controller architecture is implemented in real flight test, and improvement of tracking performance over a proportional–integral–derivative controller is demonstrated which illustrates superior performance to conventional architectures. The proposed design approach can be implemented easily to an existing system, and system performance can be enhanced in the presence of unmodelled and uncertain system dynamics.

An Adaptively Controlled Electrohydraulic Servo-Mechanism: Part 1: Adaptive Controller Design

1987 ◽  
Vol 201 (3) ◽  
pp. 175-180 ◽  
Author(s):  
K A Edge ◽  
K R A Figueredo
Keyword(s):  
Adaptive Control ◽  
Controller Design ◽  
Control Design ◽  
Adaptive Controller ◽  
Adaptive Control System ◽  
Sampled Data ◽  
Robust Controller ◽  
Servo Mechanism ◽  
Control Scheme ◽  
Model Reference Adaptive

A systematic model reference adaptive control design scheme is presented. The control scheme is developed and analysed within the framework of a sampled data system with a parameter adaptive algorithm designed on the basis of hyper stability theory. A number of supervisory functions are used to supplement the basic adaptive control system in order to enhance robust controller action.

Adapting Dynamic Braking of AC Motors to Varying Wheel/Rail Adhesion Condition

2013 ◽  
Author(s):  
Husain Ahmad ◽  
Mehdi Ahmadian
Keyword(s):  
Reference Model ◽  
Excitation Frequency ◽  
Adaptive Controller ◽  
Rolling Stock ◽  
Accurate Estimation ◽  
Model Reference ◽  
Braking Distance ◽  
Estimation And Control ◽  
Dynamic Braking ◽  
Model Reference Adaptive

Model reference adaptive control (MRAC) is developed to control the electrical excitation frequency of AC traction motors under various wheel/rail adhesion conditions during dynamic braking. More accurate estimation and control of train braking distance can allow more efficient braking of rolling stock, as well as spacing trains closer together for Positive Train Control (PTC). In order to minimize the braking distance of a train, dynamic braking forces need to be maximized for varying wheel/rail adhesion. The wheel/rail adhesion coefficient plays an important role in safe train braking. Excessively large dynamic braking can cause wheel lockup that can damage the wheels and rail, or may lead to large coupler forces, possibly causing derailment or broken components. In this study, a multibody formulation of a locomotive and three railcars is used to develop a model reference adaptive controller for adjusting the voltage excitation frequency of an AC motor such that the maximum dynamic braking is achieved, without locking up the wheels. A relationship between creep forces, creepages, and motor braking torque is established. This relationship is used to control the motor excitation frequency in order to closely follow the reference model that aims at achieving maximum allowable adhesion during dynamic braking. The results indicate that MRAC significantly improves braking distance while maintaining better wheel/rail adhesion and coupler dynamics during dynamic braking.

The Adaptive Ship Motion Control Based on Fuzzy Neural Network

2011 ◽  
Vol 135-136 ◽  
pp. 989-994 ◽  
Author(s):  
Guan Shan Hu ◽  
Hai Rong Xiao
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Motion Control ◽  
Reference Model ◽  
Tracking System ◽  
Good Control ◽  
Ship Motion ◽  
Network Systems ◽  
Model Reference ◽  
Model Reference Adaptive

Given the uncertainty of parameters and the random nature of disturbance, a ship motion, is a complicated control problem. This paper has researched adaptive neural network systems and its application to ship’s motion control. In paper, Ship’s mathematical model is researched. Aimed at ship mathematical motion model, the model reference adaptive auto pilot is first designed based on the analysis of the model reference adaptive control theory. We used fuzzy logic and neural networks to design the feedback controller, used multilayer perceptron neural network to design the reference model and the ship course identification model network. Based on the fuzzy control and neural network, an intelligent adaptive control algorithm was presented in the paper. In consideration of the forces and moments from the environmental disturbance, such as winds, waves, currents, etc., Simulation experiments are carried out by using Matlab’s Simulink toolbox. The simulating result indicates the designed adaptive controller can get a good control performance for ship course tracking system.

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