scholarly journals Comparative analysis of Direct and Indirect Model Reference Adaptive Control by Extended Kalman Filter

2021 ◽  
Vol 3 (3) ◽  
pp. 154-168
Author(s):  
R Vinothkanna ◽  
M Duraipandian
Keyword(s):  
Adaptive Control ◽  
System Dynamics ◽  
Hybrid Systems ◽  
Reference Model ◽  
Adaptive Controllers ◽  
Hybrid Modelling ◽  
The Face ◽  
Gain Adjustment ◽  
Model Reference Adaptive ◽  
Dynamic Gain

Considerations about the increasing complexity of technological systems have stimulated the interest in hybrid systems that can successfully manage switching behaviour or approach nonlinearity. Hybrid systems are made up of two parts: a constant dynamics component and a switching mechanism. This article investigates the effectiveness of direct and indirect model adaptive control approaches for any common tool for hybrid modelling and approximation nonlinear systems. A reference model may be linear or partially refined, specifies the desired loop system behavior that the adaptive controllers are capable of achieving in the face of unknown system dynamics regardless of the system dynamics. Individual control gains are obtained for each subsystem and it is also carefully tuned to the altered behavior of each system. Through the application of dynamic gain adjustment, singularities in the principle of certainty equivalence are avoided indirectly. The state of the reference model is asymptotically monitored for both techniques by assuming that a shared Lyapunov feature is available for the switched reference model.

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.

Adaptive Control of Mechanical Gas Face Seals With Rotor Runout and Static Stator Misalignment

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Haojiong Zhang ◽  
Robert G. Landers ◽  
Brad A. Miller
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Equations Of Motion ◽  
Control Technique ◽  
Estimation Errors ◽  
Adaptive Controllers ◽  
Gas Leakage ◽  
Robust Model ◽  
Robust Adaptive ◽  
Model Reference Adaptive

This paper presents a control methodology that utilizes a robust model reference adaptive control technique to regulate the dynamic behavior of a coned mechanical gas face seal system in a flexibly mounted stator configuration. Individual adaptive controllers are designed for the three stator rigid body degrees of freedom based on the linear portions of their respective equations of motion. The force and moments generated within the gas film are estimated using Kalman filter-based estimators and directly cancelled in the control algorithm using offset control signals. The estimation errors are considered as bounded disturbances to the seal system and are taken into account by the robust adaptive controllers. Simulation results show that the controllers effectively stabilize the stator motion and control the stator tilts to synchronously track the rotor runout with near-zero relative misalignment magnitude and phase shift, thus, minimizing gas leakage.

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.

Robust Fixed Point Transformations in the Model Reference Adaptive Control of a Three DoF Aeroelastic Wing

2013 ◽  
Vol 300-301 ◽  
pp. 1505-1512 ◽  
Author(s):  
József Kázmér Tar ◽  
Imre J. Rudas ◽  
János F. Bitó ◽  
Krisztián Kósi
Keyword(s):  
Fixed Point ◽  
Reference Model ◽  
Tracking Error ◽  
External Control ◽  
Underactuated System ◽  
Control Parameters ◽  
Model Reference ◽  
Adaptive Controllers ◽  
Point Transformations ◽  
Model Reference Adaptive

The Model Reference Adaptive Controllers (MRAC) of dynamic systems have the purpose of simulating the dynamics of a reference system for an external control loop while guaranteeing precise tracking of a prescribed nominal trajectory. Such controllers traditionally are designed by the use of some Lyapunov function that can guarantee global and sometimes asymptotic stability but pays only little attention to the primary design intent, has a great number of arbitrary control parameters, and also is a complicated technique. The Robust Fixed Point Transformations (RFPT) were recently introduced as substitutes of Lyapunov’s technique in the design of adaptive controllers including MRACs, too. Though this technique guarantees only stability (neither global nor asymptotic), it works with a very limited number of control parameters, directly concentrates on the details of tracking error relaxation, and it is very easily can be designed. In the present paper this novel technique is applied for the MRAC control of a 3 Degrees-of-Freedom (DoF) aeroelastic wing model that is an underactuated system the model-based control of which attracted much attention in the past decades. To exemplify the efficiency of the method via simulations it is applied for PI and PID-type prescribed error relaxation for a reference model the parameters of which considerably differ from that of the actual system.

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.

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.

The Model Reference Adaptive Control of the DC Electric Drive System

2014 ◽  
Vol 875-877 ◽  
pp. 2030-2035 ◽  
Author(s):  
Marian Gaiceanu ◽  
Cristian Eni ◽  
Mihaita Coman ◽  
Romeo Paduraru
Keyword(s):  
Adaptive Control ◽  
Reference Model ◽  
Sliding Mode ◽  
Tracking Error ◽  
Model Reference Adaptive Control ◽  
Drive System ◽  
Mode Switching ◽  
Sigmoid Function ◽  
Model Reference ◽  
Model Reference Adaptive

Due to the parametric and structural uncertainty of the DC drive system, an adaptive control method is necessary. Therefore, an original model reference adaptive control (MRAC) for DC drives is proposed in this paper. MRAC ensures on-line adjustment of the control parameters with DC machine parameter variation. The proposed adaptive control structure provides regulating advantages: asymptotic cancellation of the tracking error, fast and smooth evolution towards the origin of the phase plan due to a sliding mode switching k-sigmoid function. The reference model can be a real strictly positive function (the tracking error is also the identification error) as its order is relatively higher than one degree. For this reason, the synthesis of the adaptive control will use a different type of error called augmented or enhanced error. The DC machine with separate excitation is fed at a constant flux. This adaptive control law assures robustness to external perturbations and to unmodelled dynamics.

scholarly journals Support vector regression and model reference adaptive control for optimum control of nonlinear drying process

TAPPI Journal ◽  
2016 ◽  
Vol 15 (2) ◽  
pp. 111-126 ◽  
Author(s):  
C. Karthik ◽  
K. Valarmathi ◽  
M. Rajalakshmi
Keyword(s):  
Adaptive Control ◽  
Support Vector Regression ◽  
Reference Model ◽  
Design Procedure ◽  
Model Reference Adaptive Control ◽  
Support Vector ◽  
System Control ◽  
Paper Machine ◽  
Model Reference ◽  
Model Reference Adaptive

In this paper, a support vector regression (SVR)-based system identification and model reference adaptive control (MRAC) strategy for stable nonlinear process input-output form is designed. In order to implement the proposed control structure, SVR-based identification methods are clearly addressed. The control of a moisture process on the paper machine illustrates the proposed design procedure and the properties of the SVR-based model identification-adaptive reference model for the nonlinear system. MRAC is widely used in linear system control areas, and neural networks (NN) are often used to extend MRAC to nonlinear areas. Some drawbacks of NN with MRAC are slow speed in learning, weak generalization ability, and a local minima tendency. To overcome this problem, SVR is used instead of NN. With the support vector regressor, a stable controller-parameter adjustment mechanism is constructed by using the model reference adaptive theory. Simulation results show that the proposed approach could reach desired performance.

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]

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