Model Reference Adaptive Control Approach Research Articles

An MRAC Approach for Tracking and Ripple Attenuation of the Common Rail Pressure for GDI Engines

AbstractGasoline Direct Injection (GDI) spark ignition engines equipped with the Common Rail (CR) system strongly improve engine performance in terms of fuel consumption and pollutant emission reduction. As a drawback the fuel pressure in the rail has to be kept as constant as possible to the demanded pressure working set-points in order to achieve the advantages promised by this technology. In this work a Model Reference Adaptive Control (MRAC) algorithm based on the Minimal Control Synthesis (MCS) strategy is proposed to reduce the residual pressure in the rail. Numerical results based on a CR mean value model, previously proposed in the literature and experimentally validated, show that a very satisfactory attenuation of the pressure ripple as well as pressure tracking are attained in different working conditions. A quantitative comparison with a classical gain scheduling model-based control approach confirms furthermore the effectiveness of the proposed adaptive control strategy.

Model reference adaptive switching control of a linearized hypersonic flight vehicle model with actuator saturation

In order to address the control of an air-breathing hypersonic flight vehicle (AHFV) with actuator saturation, a model reference adaptive switching control (MRASC) approach is proposed. The design of the MRASC system is centred around a linearized longitudinal-motion flexible model at a Mach 8, altitude of 10 000 ft, and dynamic pressure of 1017 lb/ft2 flight condition. A switched reference system (SRS) is established to describe the desired dynamics of the AHFV with/without actuator saturation, and correspondingly, a switched adaptive controller (SAC) is constructed utilizing the hyperstability method. By switching between the subsystems of the SRS and the corresponding subcontrollers of the SAC, the MRASC system achieves the desired performance and is globally asymptotically stable under limited disturbances, provided that a simple linear-matrix-inequality-based sufficient condition holds. Although it is too early to say that the proposed scheme gives desired anti-saturation performance with respect to large disturbances, within a large flight envelope, there are still some advantages that will improve performance.

Time delay resistant adaptive control of mini-UAVs

Many potential applications of adaptive control, such as adaptive flight control systems, require that the controller have high performance, stability guarantees, and robustness to time delays. These requirements typically lead to engineering trade-offs, such as a tradeoff between performance and robustness. In this paper, a new Time Delay Resistant (TDR) adaptive control framework is proposed using a combination of several modifications to the typical direct model reference adaptive control (MRAC) approach. The benefits of the TDR approach are explored with a simulation of the longitudinal dynamics of a fixed-wing aircraft. Flight tests of a 4 rotor mini-UAV were also performed using a subset of the TDR adaptive control features.

Wind turbines: New challenges and advanced control solutions

Wind turbines: New challenges and advanced control solutions

A modified model reference adaptive control approach for systems with noise or unmodelled dynamics

In this paper, a modified model reference adaptive control (MRAC) strategy is developed for use on plants with noise or unmodelled high-frequency dynamics. MRAC consists of two parts, an adaptive control part and a fixed gain control part. The adaptive algorithm uses a combination of low- and high-pass filters such that the frequency range for the adaptive part of the strategy is limited. The mechanism for noise-induced gain wind-up is demonstrated analytically, and it is shown how MRAC can be modified to eliminate this wind-up. Further to this, an additional filter is proposed to improve MRAC robustness to high-frequency unmodelled dynamics. Two test plants, one with added noise and the other with unmodelled high-frequency dynamics, are considered. Both plants exhibit unstable behaviour when controlled using standard MRAC, but, with the modified strategy, robustness is significantly improved.

Direct adaptive control of a utility‐scale wind turbine for speed regulation

AbstractThe accurate modeling of wind turbines is an extremely challenging problem due to the tremendous complexity of the machines and the turbulent and unpredictable conditions in which they operate. Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. In this paper, we extended the direct model reference adaptive control (DMRAC) approach to track a reference point and to reject persistent disturbances. This approach was then used to design an adaptive collective pitch controller for a high‐fidelity simulation of a variable‐speed horizontal axis wind turbine. The objective of the adaptive pitch controller was to regulate generator speed in Region 3 and to reject step disturbances. The control objective was accomplished by collectively pitching the turbine blades.The turbine simulation models the controls advanced research turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility‐scale wind turbine that has a well‐developed and extensively verified simulator. This novel application of adaptive control was compared in simulations with a classical proportional integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the PI pitch controller. Copyright © 2008 John Wiley & Sons, Ltd.

Model reference adaptive synchronization of T–S fuzzy discrete chaotic systems using output tracking control

Abstract This paper presents a model reference adaptive control approach for the synchronization of a discrete-time chaotic systems using output tracking control. The reference model system is chosen using the output of master system and Takagi–Sugeno (T–S) fuzzy model is employed to represent the discrete-time chaotic slave system. Design the control input so that the controlled slave system achieves asymptotic synchronization with the reference system given that two systems start from different initial conditions, different parameters and/or different type of model. Using a gradient algorithm, the ideal controller gains which can stabilize the error equation are estimated. Simulation examples of two cases are given to demonstrate the validity of our proposed adaptive method.

Adaptive control of nonlinear dynamical systems using a model reference approach

In this paper we consider using a model reference adaptive control approach to control nonlinear systems. We consider the controller design and stability analysis associated with these type of adaptive systems. Then we discuss the use of model reference adaptive control algorithms to control systems which exhibit nonlinear dynamical behaviour using the example of a Duffing oscillator being controlled to follow a linear reference model. For this system we show that if the nonlinearity is “small” then standard linear model reference control can be applied. A second example, which is often found in synchronization applications, is when the nonlinearities in the plant and reference model are identical. Again we show that linear model reference adaptive control is sufficient to control the system. Finally we consider controlling more general nonlinear systems using adaptive feedback linearization to control scalar nonlinear systems. As an example we use the Lorenz and Chua systems with parameter values such that they both have chaotic dynamics. The Lorenz system is used as a reference model and a single coordinate from the Chua system is controlled to follow one of the Lorenz system coordinates.

PID AUTOTUNING USING NEURAL NETWORKS AND MODEL REFERENCE ADAPTIVE CONTROL

This paper describes the application of artificial neural networks for automatic tuning of PID controllers using the Model Reference Adaptive Control approach. The effectiveness of the proposed method is shown through a simulated application.

Reduced spatial order model reference adaptive control of spatially varying distributed parameter systems of parabolic and hyperbolic types

AbstractThis paper presents control laws for distributed parameter systems of parabolic and hyperbolic types with unknown spatially varying parameters. These laws, based on the model reference adaptive control approach, guarantee asymptotic tracking of the output of the reference model by the output of the plant for arbitrary time invariant, but spatially varying reference input. The novel capabilities of the algorithms proposed are providing reduced sensitivity to measurement noise due to the reduced order of the spatial differentiation of the output data and permitting on‐line estimation of the spatially varying plant parameters, constructively enforceable through the reference input and/or boundary conditions. The parameter estimation is carried out by means of an auxiliary system with the time‐varying parameters that simultaneously converge in L2 to plant parameters when appropriate input signals in the reference model are used. The orthogonal expansions of these time‐varying parameters, which can be computed by passing the auxiliary system parameters through the integrator block, converge to the plant parameters pointwise if the latter are sufficiently smooth. The parameter convergence is obtained by combining the adaptation laws with sufficiently rich input signals, referred to as generators of persistent excitation, which guarantee the existence of a unique steady state for the parameter errors. Copyright © 2001 John Wiley & Sons, Ltd.

Direct Adaptive Control of a Linear Parabolic System

This paper presents an adaptive model reference algorithm for a linear distributed parameter system with input boundary control and output boundary reference. The control and adaptation laws are based a model reference adaptive control approach. This controller is applied to a tubular reactor model with unknown kinetic parameters. Simulation results are shown for set-point changes, variation of kinetic parameters and input perturbation.

Compensation of Parameter Variation Effects in Sensorless Indirect Vector Controlled Induction Machines Using Model-Based Approach

The majority of speed estimation schemes for sensorless vector control of induction machines use a mathematical model of the machine in the estimation process. These schemes are therefore inherently sensitive to parameter variation effects in the machine. The variety of speed estimation methods makes any attempt to develop a universal approach to compensation of parameter variation effects impossible. This paper concentrates on one of the most frequently used schemes, in which speed is estimated using model reference adaptive control approach (MRAC) on the basis of two estimated values of the rotor flux space vector. The estimator is analyzed in conjunction with indirect feed-forward rotor flux-oriented induction machine. An attempt is made to improve the accuracy of the speed estimation by appropriate modification of the speed estimator and the indirect vector controller structures using modified induction motor models that account for one or more of the phenomena that are neglected in development of the basic constant parameter scheme. In particular, compensation of main flux saturation, compensation of iron loss, and simultaneous compensation of both the iron loss and main flux saturation are elaborated. Novel structures of the speed estimator are developed for each of the three cases and are applied in conjunction with the appropriate modified form of the indirect rotor flux-oriented controller. Excellent compensation capability is demonstrated in all the cases by performing extensive simulation studies.

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.

Model Reference Adaptive Control of Nonlinear Systems with Canonical Structure

Abstract Model reference adaptive control (MRAC) has been developed in many modifications. The stability proofs have been given under the assumption that the plant model is linear. However, MRAC approaches give often convergent solutions even for nonlinear systems. The aim of this paper is to show that for nonlinear systems with the model in canonical form, the standard MRAC with state feedback structure can be used to obtain the perfect model matching. The stability proof is derived using the general Laypunov stability theory. At the end of paper, an example of adaptive control of third order nonlinear system is presented, where a considerable improvement of control system dynamical behavior has been obtained.

ADAPTIVE MODAL VIBRATION CONTROL OF A FLUID-CONVEYING CANTILEVER PIPE

A model reference adaptive control approach, designed in the modal space, is applied for flutter control of a cantilever pipe conveying fluid. The control input is provided by a pair of surface-mounted piezoelectric actuators which are driven 180° out of phase to provide an equivalent bending moment acting on the controlled system. Comparison of performance of the model reference adaptive control with that of the optimal independent modal space control reveals that the former is more robust than the latter in terms of flow speed variations, which are unknown in the control system designed; that is, the adaptive approach can tolerate a larger range of flow speed uncertainties without resulting in an unstable control system, so that successful flutter suppression of the fluid-conveying cantilever pipe with high flow speed can be achieved.

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.

A robust adaptive controller for PM motor drives in robotic applications

The paper deals with theoretical development and practical implementation of an adaptive speed and position regulator suitable for robotic applications. The proposed adaptive control scheme is characterized by a reduced amount of computation and is based on the model reference adaptive control approach to compensate the variations of the system parameters, such as inertia and torque constant. A disturbance torque observer is employed to balance the required load torque and reduce the complexity of the adaptive algorithm. Simulation tests of a robotic drive, including an interior type permanent magnet synchronous (IPMS) motor, are reported in order to compare the proposed control scheme with standard speed and position regulators. Experimental results, obtained from a prototype based on a commercial PC board, are also reported in order to practically evaluate the feasibility and the features of the proposed adaptive control scheme. >

An analysis of some fundamental problems in adaptive control of force and impedance behavior: theory and experiments

Force control in robotic mechanisms has been extensively researched. There have been several results which have concentrated either on explicit force control or impedance control. Further, many of these works require accurate identification of the stiffness of the environment. In this work the authors examine the role of adaptive controllers for force control with unknown system and environment parameters and clearly integrate several fundamental issues such as explicit force control, impedance control, and impedance control combined with a desired force control. All of these issues are treated using standard model-reference adaptive control (MRAC) approach. Within the same framework, the authors analyze other equally fundamental issues such as environment stiffness identification, stability of the complete system, and parameter convergence. The authors demonstrate the effectiveness of the proposed theory through experiments.

Evolution of Adaptive Control

The evolution of the adaptive control algorithms driven by the results obtained in the application of the 1st generation of adaptive controllers (model reference adaptive control, self-tuning minimum variance) is examined. Research in the field of adaptive control has been directed, on the one hand, toward the development of a robust general purpose adaptive controller and, on the other, towards the extension of the model reference adaptive control approach to nonlinear systems. Research has also investigated the stability/passivity approach for developing dedicated adaptive control algorithms for particular classes of nonlinear plants (e.g., rigid robots). The paper will review the results obtained in these directions both from the theoretical and the practical points of view. In the final part, current research directions will be included.

Stability of Control Systems with Local Adaptive Feedback Loops

This paper discusses stability of a class of adaptive control systems. The system considered consists of an adaptive block and non-adaptive blocks. The adaptive block is constructed by the conventional model reference adaptive control (MRAC) approach. Assuming the general properties of MRAC, sufficient conditions for the whole system to be stable are obtained.