A NOVEL MULTIPLE REFERENCE MODEL ADAPTIVE CONTROL APPROACH FOR MULTIMODAL AND DYNAMIC SYSTEMS

2008 ◽  
Vol 36 (2) ◽  
Keyword(s):  
Adaptive Control ◽  
Dynamic Systems ◽  
Reference Model ◽  
Control Approach ◽  
Multiple Reference

Fuzzy Multiple Reference Models Adaptive Control of Induction Motors

2011 ◽  
Vol 354-355 ◽  
pp. 1285-1288
Author(s):  
Hua Xue ◽  
Yu Fei Wang
Keyword(s):  
Adaptive Control ◽  
Reference Model ◽  
Dynamic Performance ◽  
Model Parameters ◽  
Reference Models ◽  
Parameter Variations ◽  
Speed Change ◽  
High Dynamic ◽  
Suitable Reference ◽  
Multiple Reference

A new method of fuzzy multiple reference models adaptive control(FMRMAC) for dealing with significant and unpredictable system parameter variations is presented. In this method, different suitable reference model is chosen by fuzzy rules when changes occurred to the model parameters. A successful application to the speed servo system of dynamic model of induction motor (IM) shows this method works well with high dynamic performance under the condition of command speed change and load torque disturbance.

Study on Fuzzy Multiple Reference Model Adaptive Control Strategies

2014 ◽  
Vol 962-965 ◽  
pp. 2932-2938
Author(s):  
Shu Xing Peng ◽  
Hua Xue ◽  
Dong Dong Li
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Reference Model ◽  
Control Strategies ◽  
Dynamic Performance ◽  
Control Precision ◽  
High Dynamic ◽  
Suitable Reference ◽  
And Control ◽  
Multiple Reference

A new fuzzy multiple reference model adaptive control method combined with fuzzy select and conventional adaptive control is presented. To overcome the control difficulties which due to significant and unpredictable system parameter variations, fuzzy logic rules are designed to choose the suitable reference model. The new method is applied to control the speed servo system of dynamic model of BLDCM, and the simulation results show it works well with high dynamic performance and control precision under the condition of great change in reference speed and load torque.

scholarly journals Adaptive Control of a Reverse Logistic Inventory Model with Uncertain Deteriorations and Disposal Rates

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Ahmad Alshamrani
Keyword(s):  
Adaptive Control ◽  
Nonlinear System ◽  
Asymptotic Stability ◽  
Numerical Solution ◽  
Reference Model ◽  
Inventory System ◽  
System Of Differential Equations ◽  
Controlled System ◽  
Control Approach ◽  
Reverse Logistic

An adaptive control of a reverse logistic inventory system with unknown deterioration and disposal rates is considered. An adaptive control approach with a feedback is applied to track the inventory levels toward their goal levels. Also, the updating rules of both deterioration and disposal rates are derived from the conditions of asymptotic stability of the reference model. Important characteristics of the adaptive inventory system are discussed. The adaptive controlled system is modeled by a nonlinear system of differential equations. Finally, the numerical solution of the controlled system is discussed and displayed graphically.

Model-Reference Based Adaptive Control for Enhancing Lateral Stability of Car-Trailer Systems

2016 ◽  
Author(s):  
Smitha Vempaty ◽  
Eungkil Lee ◽  
Yuping He
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Reference Model ◽  
Model Reference Adaptive Control ◽  
Operating Conditions ◽  
Model Parameters ◽  
Lateral Stability ◽  
Model Reference ◽  
Control Approach ◽  
Model Reference Adaptive

This paper presents a model reference adaptive control (MRAC) approach to enhance the lateral stability of car-trailer systems. To this end, a 3 degrees of freedom (DOF) linear yaw-plane car-trailer model was developed as a “reference model”. The yaw rate of leading and trailing units of the reference model were used as the target states to control and stabilize a virtual vehicle plant represented by a 5 DOF linear yaw-roll car-trailer model. A Lyapunov-based controller was designed to handle the lateral stability of the car-trailer dynamical system. The model parameters and operating conditions of the system were predefined while designing the controller. The effectiveness of the adaptive controller for improving the lateral stability of car-trailer systems was demonstrated under a simulated multiple cycle sine-wave steering input maneuver. It was observed that the lateral stability of car-trailer system was improved by controlling respective yaw rates of the car and the trailer, using model reference adaptive control approach in conjunction with Lyapunov stability criterion.

scholarly journals Geometric L1 Adaptive Attitude Control for a Quadrotor Unmanned Aerial Vehicle

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Prasanth Kotaru ◽  
Ryan Edmonson ◽  
Koushil Sreenath
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Reference Model ◽  
Adaptive Controller ◽  
Control Approach ◽  
L1 Adaptive Control ◽  
Attitude Tracking ◽  
Aerial Vehicle ◽  
L1 Adaptive Controller

Abstract In this paper, we study the quadrotor unmanned aerial vehicle (UAV) attitude control on special orthogonal group (SO(3)) in the presence of unknown disturbances and model uncertainties. L1 adaptive control for UAVs using Euler angles/quaternions is shown to exhibit robustness and precise attitude tracking in the presence of disturbances and uncertainties. However, it is well known that dynamical models and controllers that use Euler angle representations are prone to singularities and typically have smaller regions of attraction while quaternion representations are subject to the unwinding phenomenon. To avoid such complexities, we present a geometric L1 adaptation control law to estimate the uncertainties. A model reference adaptive control approach is implemented, with the attitude errors between the quadrotor model and the reference model defined on the manifold. Control laws for the quadrotor and reference models are developed directly on SO(3) to track the desired trajectory while rejecting the uncertainties. Control Lyapunov function-based analysis is used to show the exponential input-to-state stability of the attitude errors. The proposed L1 adaptive controller is validated using numerical simulations. Preliminary experimental results are shown comparing a geometric proportional-derivative controller to the geometric L1 adaptive controller. Experimental validation of the proposed controller is carried out on an Autel X-star quadrotor.

ADAPTIVE CONTROL OF AN ACTIVE SUSPENSION FOR NONLINEAR TIME VARYING VEHICLE PLANT

2000 ◽  
Vol 24 (3-4) ◽  
pp. 525-546
Author(s):  
Rao V. Dukkipati ◽  
Satya S. Vallurupalli
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Reference Model ◽  
Model Simulation ◽  
A Priori ◽  
Optimal Performance ◽  
Time Varying ◽  
Control Approach ◽  
Dynamic Variations ◽  
Suspension Model

This paper presents a new adaptive control approach to general multi-degrees-of-freedom suspension models. The control concept diverts from the widely applied optimal control to adaptive control. The basic idea involves obtaining optimal performance of any nonlinear time varying suspension model by adaptively following a predefined reference model. Optimal performance is achieved by an adaptive control law, which involves feed forward, feedback and auxiliary controller parameters. Model reference adaptive control is used to derive adaptation laws for the controller. The proposed control scheme is computationally fast and does not require a priori knowledge of complex nonlinear dynamic variations and time varying parameters of the model. Simulation results for a two-degree of freedom nonlinear suspension model subjected to random asphalt road input are presented. The time and frequency domain results indicate good performance of adaptive controller even for large dynamic variations of model.

Adaptive Control Method for Unstable Impulse Processes in Cognitive Maps Based on Reference Model

2015 ◽  
Vol 47 (3) ◽  
pp. 11-23 ◽  
Author(s):  
Victor D. Romanenko ◽  
Yuriy L. Milyavskiy ◽  
Alexey A. Reutov
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Reference Model ◽  
Cognitive Maps

Adaptive control of time-varying non-linear plants by speed-gradient algorithms

2019 ◽  
pp. 37-44 ◽  
Author(s):  
O. P. Tomchina ◽  
D. N. Polyakhov ◽  
O. I. Tokareva ◽  
A. L. Fradkov
Keyword(s):  
Adaptive Control ◽  
Adaptive Systems ◽  
Reference Model ◽  
Maximum Deviation ◽  
Model Parameters ◽  
Time Varying ◽  
System Solution ◽  
Non Linear ◽  
Initial Uncertainty ◽  
Speed Gradient

Introduction: The motion of many real world systems is described by essentially non-linear and non-stationary models. A number of approaches to the control of such plants are based on constructing an internal model of non-stationarity. However, the non-stationarity model parameters can vary widely, leading to more errors. It is only assumed in this paper that the change rate of the object parameters is limited, while the initial uncertainty can be quite large.Purpose: Analysis of adaptive control algorithms for non-linear and time-varying systems with an explicit reference model, synthesized by the speed gradient method.Results: An estimate was obtained for the maximum deviation of a closed-loop system solution from the reference model solution. It is shown that with sufficiently slow changes in the parameters and a small initial uncertainty, the limit error in the system can be made arbitrarily small. Systems designed by the direct approach and systems based on the identification approach are both considered. The procedures for the synthesis of an adaptive regulator and analysis of the synthesized system are illustrated by an example.Practical relevance: The obtained results allow us to build and analyze a broad class of adaptive systems with reference models under non-stationary conditions.

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