Discrete Model Reference Adaptive Control Research Articles

Comparison between model reference discrete time indirect and direct adaptive controls

The discrete time Model Reference Adaptive Control (MRAC) techniques have some important properties. They can be used successfully to the control of different type of Single Input and Single Output (SISO) systems: Linear Time Invariant (LTI) systems with unknown parameters and Linear Parameter Varying (LPV) systems. This method can be considered also as a nonlinear control design, where the system parameters will be updated in each iteration.

Maximum Power Point Tracking Using DRCC and MRAC With Modified Mit Rules For PV Cells

This paper is about improving the maximum power point tracking by using the Discrete time Ripple Correlation Control and Model Reference Adaptive Control with MIT rules. MPPT technologies have been used in photo-voltaic systems to deliver the maximum power output to the load under changes of solar insolation and solar panel’s temperature. Where as in the existing models combined feature of ripple correlation control (RCC), and the model reference adaptive control (MRAC) are used in Photovoltaic systems to reduce pertabations.This paper includes the improved version of both RCC and MRAC ,a model two layer architecture which provides promising increase in tracking efficiency and accuracy. The performance of the pro-posed technique was observed and developed by MATLAB/simulink software.

Discrete variable structure model reference adaptive control using only input-output measurements

Designing an adequate controller for a plant with an arbitrary relative degree is still an active area of research. In this paper, a discrete variable structure model reference adaptive control using only input-output measurements (DVS-MRAC-IO) for not strictly positive real systems with a relative degree of two is proposed. In order to show the effectiveness of the proposed controller, a detailed stability analysis is studied using Lyapunov theory. Further, a straightforward generalization of DVS-MRAC-IO for systems with arbitrary relative degree is presented. Numerical results are used to show the effectiveness of the proposed methods.

Discrete Model Reference Adaptive Control for Gimbal Servosystem of Control Moment Gyro with Harmonic Drive

The double-gimbal control moment gyro (DGCMG) demands that the gimbal servosystem should have fast response and small overshoot. But due to the low and nonlinear torsional stiffness of harmonic drive, the gimbal servo-system has poor dynamic performance with large overshoot and low bandwidth. In order to improve the dynamic performance of gimbal servo-system, a model reference adaptive control (MRAC) law is introduced in this paper. The model of DGCMG gimbal servo-system with harmonic drive is established, and the adaptive control law based on POPOV super stable theory is designed. The MATLAB simulation results are provided to verify the effectiveness of the proposed control algorithm. The experimental results indicate that the MRAC could increase the bandwidth of gimbal servo-system to 3 Hz and improve the dynamic performance with small overshoot.

Adaptive Control System of Milling Machine

In this paper, the discrete model reference adaptive control (MRAC) system of milling machine is discussed. Firstly, the discrete Model of milling machine is presented. Based on it the design of the adaptive control is made, and the rule of discrete model reference adaptive control is proven. The results of simulation show that adaptive control has favorable performances.

Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

Simulating Discrete Time Model Reference Adaptive Control System with Great Initial Error

Simulating Discrete Time Model Reference Adaptive Control System with Great Initial Error

Stability and accuracy analysis of a discrete model reference adaptive controller without and with time delay

AbstractAdaptive control techniques can be applied to dynamical systems whose parameters are unknown. We propose a technique based on control and numerical analysis approaches to the study of the stability and accuracy of adaptive control algorithms affected by time delay. In particular, we consider the adaptive minimal control synthesis (MCS) algorithm applied to linear time‐invariant plants, due to which, the whole controlled system generated from state and control equations discretized by the zero‐order‐hold (ZOH) sampling is nonlinear. Hence, we propose two linearization procedures for it: the first is via what we term as physical insight and the second is via Taylor series expansion. The physical insight scheme results in useful methods for a priori selection of the controller parameters and of the discrete‐time step. As there is an inherent sampling delay in the process, a fixed one‐step delay in the discrete‐time MCS controller is introduced. This results in a reduction of both the absolute stability regions and the controller performance. Owing to the shortcomings of ZOH sampling in coping with high‐frequency disturbances, a linearly implicit L‐stable integrator is also used within a two degree‐of‐freedom controlled system. The effectiveness of the methodology is confirmed both by simulations and by experimental tests. Copyright © 2009 John Wiley & Sons, Ltd.

Design of Reconfigurable Flight Controller Using Discrete Model Reference Adaptive Scheme

In this paper, an adaptive control algorithm using system identification is proposed for an aircraft fault tolerant control system. A discrete state-space system is reformulated to be the ARX model which has the advantage in handing variable structure systems. Discrete model reference adaptive control is used to make the output of fault system follow the output of reference model. To validate the performance of the proposed control scheme, numerical simulations are performed for the high performance aircraft with control surface damage.

Convergence and frequency-domain analysis of a discrete first-order model reference adaptive controller

SUMMARY We study the convergence properties of a direct model reference adaptive control system by applying techniques from numerical analysis. In particular, a first-order discrete system coupled to a minimal control synthesis algorithm discretized by the one-step one-stage zero-order-hold sampling is studied. This results in a strongly non-linear dynamic system owing to the adaptive mechanism where stability at steady state, i.e. at the operating point, equates to successful control. This paper focuses on the convergence analysis of the overall dynamical system for understanding accuracy, stability and performance at steadystate. The local stability of the steady state solution is considered by linearizing the system in the neighbourhood of an operating point when the input is a step function. This analysis allows us to specify two gain space domains which define the region of local stability. Moreover, both the accuracy and the frequency-domain analyses give insight into the range of adaptive control weightings that results in optimal performance of the minimal control synthesis algorithm and also highlights a possible approach to a priori selection of the time step and adaptive weighting values. The effectiveness of the proposed analysis is further demonstrated by simulations and experiments on a first-order plant. Copyright # 2006 John Wiley & Sons, Ltd.

Smart Active Suspension to Counteract Dynamic Load Changes during Critical Maneuvers.

This paper presents an adaptive control approach to a general multi-degrees-offreedom suspension model. A half car model, which involves bounce and pitch degrees of freedom for sprung mass and bounce degree of freedom for the unsprung mass is considered. 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. The controller is designed for the first time to compensate for Squat and Nose-diving in the pitch mode of the vehicle during acceleration and deceleration maneuvers respectively. Discrete Model reference Adaptive Control (DMRAC) with parameter estimation is used to derive adaptation laws for the controller. The proposed control scheme is found to be computationally fast and does not require a priori knowledge of complex and nonlinear dynamic model and time varying parameters of the model. Simulation results for half-car model with all nonlinear suspension components subjected to deterministic input are presented. The results indicate good performance of adaptive controller even for large parametric variations in the model due to critical acceleration and deceleration maneuvers.

EVALUATION OF DISCRETE ADAPTIVE FAIL-SAFE ACTIVE SUSPENSION

Hardware implementation of discrete adaptive control for a full scale vehicular single degree of freedom (SDOF) active suspension has been discussed in this paper. This paper describes an experimental evaluation of full scale fail-safe adaptive active (SDOF) suspension system that has been performed for the first time. A servo hydraulic force actuator is installed along with passive suspension components to form a fail-safe active suspension. A discrete model reference adaptive control (DMRAC) approach with recursive least square (RLS) estimation and covariance modification has been used for the software/hardware based digital control. A real time computer controlled adaptive active suspension software which shows the experimental response and animation of the results has been developed.

Discrete Adaptive Active Suspension for Hardware Implementation

SUMMARY This paper presents a discrete adaptive control approach for an active suspension. The study involves formulation of an active suspension as a digital controller problem involving the time delays. A nonlinear time varying (NTV), single input single output (SISO) suspension model is considered for the analysis. A discrete model reference adaptive control (DMRAC) approach with recursive least square (RLS) estimation is used to form the controller. The controller is designed to maintain the static equilibrium irrespective of dynamic load variations as a disturbance force on the model. Simulation results for deterministic and stochastic inputs are presented to substantiate the approach. Results indicate good performance of adaptive controller even for large dynamic variations of the model and has the potential for a successful hardware implementation.

Discrete model reference adaptive control of continuous-time linear multi-input multi-output systems via multirate sampled-data controllers

The use of multirate sampled-data controllers for linear multivariable time-invariant systems with unknown parameters is investigated. Such controllers contain periodically time-varying elements and a multirate sampling mechanism with different sampling periods at each system input. Their application to unknown continuous-time linear multi-input, multi-output systems results in a sampled closedloop system for which an arbitrary discrete-time transfer function matrix can be assigned, as is shown in the present paper. The contribution of the present paper is twofold: the use of multirate sampled-data controllers in the area of model reference adaptive control; and the application, for the first time, of periodically varying controllers for model reference adaptive control of multi-input, multi-output systems.

Digital Adaptive Control of Rotary System with Unknown Nonlinear Friction

This paper is concerned with the design of a discrete time Model Reference Adaptive Control System (WACS) for motion control under unknown nonlinear friction. Static and Coulomb friction forces are represented by a deadzone element for the input, which is active at low velocities. and disturbance. which may take different values depending on the motion direction. respectively. Then, the WAes for the nonlinear friction is a cascade combination of a nonlinear block which contains the deadzone and the disturbance term and a linear dynamic block. Experimental results from a rotary servo system demonstrate the effectiveness of the proposed WAeS

Robust Design of Discrete Time Model Reference Adaptive Control Systems

This paper proposes a robust design of the discrete time model reference adaptive control system in the presence of modeling errors and shows the results of the feasibility test applied to position control of a DC-motor. In this scheme, the dominant parameters of the discrete time plant-model expressed in terms of δ-operator are estimated by an adaptive law with dead zone and then the current estimates are used to determine the controller parameters by calculation. In the synthesis of the control input, the output error is fed back through a fixed compensator to reduce the tracking error due to the parameter adjustment-mismatch. Stability of the adaptive system is analytically proved to be guaranteed by setting the width of the dead zone of adaptive law appropriately. The feasibility test has verified that the proposed scheme can realize satisfactory control performance in spite of the presence of modeling errors.

A discrete adaptive field-oriented induction motor drive

A discrete model reference adaptive controller (MRAC) is designed and implemented. This MRAC makes the performance of the field-oriented induction motor drives insensitive to parameter changes. Only the information of the reference model and the plant output are required. Hence, the proposed controller is easy to implement practically. For designing the proposed adaptive controller, the dynamic model of the drive system is estimated from the sampled input-output data using the stochastic modeling technique. The theoretical basis of the adaptive control is derived and simulation is made. The hardware of the drive system and the microprocessor-based adaptive controller are discussed. Some experimental results are given to demonstrate the effectiveness of the proposed controller. >

Unification of Continuous and Discrete Model Reference Adaptive Control

A moving average skip sampling technique is previously proposed by authors( Qu Zhihua and Zhang Qiren,1986). It seems to be generalised to implications for either a continuous system or a discrete one. From this point, an unified approach for continuous MRAC and discrete MRAC is given in this paper.

Stability of discrete model reference adaptive control — revisited

We demonstrate that the model reference adaptive controller is robust with respect to small model/plant mismatch. The sign and a lower bound on the high frequency gain are known and the control parameters are constrained to belong to a compact set which contains the parameters of a stabilizing controller. Data normalization and deadzones do not play a role in the analysis. A constructive proof is used to develop bounds for the allowable gain of the model mismatch. When the algorithm state is far from equilibrium the signals are measured by a decaying exponential. The rate of convergence is estimated. An expression which can be used to calculate the size of an overbounding set is developed. Its size scales uniformly with respect to the external disturbances, the inverse of the adaptive gain and the reference. The ideal case is obtained as these tend to zero. This result holds true even when there is a model mismatch.

Discrete-time model reference adaptive control for plants having deterministic disturbances

Based on the second method of Lyapunov, a globally stable discrete model reference adaptive controller design method with unknown deterministic disturbances is derived. The basic idea is to parameterize the disturbances by a ramp function using two parameters. It includes the SISO and MIMO cases. A state variable filter (SVF) is added to ensure that the proposed method is applicable to a plant with moderate measurement noise. The performance of these designs is illustrated by simulation.