Model Reference Adaptive Observer Research Articles

Model Reference Adaptive Observer for Permanent Magnet Synchronous Motors Based on Improved Linear Dead-Time Compensation

Model Reference Adaptive Observer for Permanent Magnet Synchronous Motors Based on Improved Linear Dead-Time Compensation

Modified model reference adaptive observer‐based control without assumptions on uncertain parameter bounds

AbstractThis paper proposes a Modified model reference adaptive controller and observer (MMRACO) for unknown linear time‐invariant (LTI) systems. The recent literature, and in particular the so‐called MRACO approach, has demonstrated how some deficiencies in standard model reference adaptive control can be overcome by using a combination of modified reference models and observers, but this is done at the expense of knowing bounds on certain unknown parameters. Here, a novel adaptive observer/controller combination is presented which removes the need to know the above bounds but preserves the other desirable features of the MRACO approach. A Lyapunov analysis of the closed‐loop system ensures asymptotic convergence of both tracking and observer errors, with uniform boundedness of parameter estimation errors. A key advantage of the scheme is that the design involves only solutions of two Lyapunov equations (or linear matrix inequalities) and does not require the selection of a “high gain” parameter. The effectiveness of the approach is illustrated in some numerical examples.

D-MRACO: Decentralized Model Reference Adaptive Controller and Observer

Model Reference Adaptive Controller and Observer (MRACO) has been proposed recently in Ohrem and Holden (2021) for a single unknown plant. Motivated by the advances in multiagent systems, we propose a unified framework named Decentralized MRACO (D-MRACO), addressing leaderless synchronization and leader-follower tracking problems of multiple unknown plants (agents). Numerical examples show the efficiency and robustness of the proposed D-MRACO.

High-Tracking-Precision Sensorless Control of PMSM System Based on Fractional Order Model Reference Adaptation

In order to solve parameter fluctuations and disturbances, a novel fractional order model reference adaptive speed observer that estimates the rotor position and the angular velocity from the stator currents is proposed for sensorless control of permanent-magnet synchronous motors (PMSM). Firstly, a novel fractional order model reference adaptive controller (FOMRAC) for adaptive identification is designed to achieve fast response and high precise identification of load torque in the full speed range when the motor is running at variable-speed or variable-load. Additionally, an appropriate adjustable matrix P is chosen to make the convergence of the adaptive law meet the requirements. Next, an improved model reference adaptive observer (MRAO) is proposed to suppress the serious chattering and compensate rotor position error, which can stabilize the system. The validity of the proposed fractional order model reference adaptive sensorless control strategy for PMSM is demonstrated with simulations.

Control Strategy of Biaxial Variable Gain Cross-Coupled Permanent Magnet Synchronous Linear Motor Based on MPC-MRAS

Aiming at the problem of poor tracking performance and chattering in track processing of biaxial permanent magnet linear synchronous motor (PMLSM), a cross-coupling control system based on model prediction was designed. First, according to the motion equation of PMLSM, an integrated controller is designed to predict the speed and current. In order to solve the problem that PMLSM is highly dependent on speed sensor, the actual motor model is designed, the adjustable model is designed by estimating the current model, and the model reference adaptive observer is designed. Second, cross-coupling control algorithm was added to the single axis control system of two PMLSM to improve the contour control accuracy and matching degree of the two motors. Finally, the experimental verification is carried out on the two-dimensional <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">XY</i> -axis experimental platform. Experimental results show that this method not only simplifies the structure of the control system, but also has better control effect than the traditional biaxial control structure.

Model Reference Adaptive Speed Observer Control of Permanent Magnet Synchronous Motor Based on Single Neuron PID

Abstract For the speed sensorless control of permanent magnet synchronous motor (PMSM), a design method based on model reference adaptive observer and single neuron PID speed loop was proposed. In this method, the model reference adaptive observer is used to identify the speed online, the Popov hyperstability is used to determine the reference adaptive law of the speed observer, the neural network module is used to control the q-axis current, and the LMS algorithm is selected to modify the weights of the neural network speed loop online. The simulation results show that the model reference adaptive speed observer control of PMSM based on single neuron PID is effective and robust.

A hybrid fault-tolerant control strategy for four-wheel independent drive vehicles

In this paper, a hybrid fault-tolerant control strategy is putted forward to improve the stability of the four-wheel independent drive (4WID) electric vehicle with motor failures. To improve the handling performance of the vehicle with in-wheel motor failures, the faults of in-wheel motors are analyzed and modeled. Then, a model reference adaptive fault observer was designed to observe the faults in real-time. Based on the observation results, there are designed a model predictive control (MPC) based high-performance active fault-tolerant control (AFTC) strategy and a sliding mode control based high-robust passive fault-tolerant control (PFTC) strategy. However, the fault observation results may not always be accurately. For this circumstance, a hybrid fault-tolerant control strategy was designed to make the control method find a balance between optimality and robustness. Finally, a series of simulations are conducted on a hardware-in-loop (HIL) real-time simulator, the simulation results show that the control strategy designed in this paper is effectiveness.

Limited-Position Set Model-Reference Adaptive Observer for Control of DFIGs without Mechanical Sensors

Operations of the doubly-fed induction generators (DFIGs) without mechanical sensors are highly desirable in order to enhance the reliability of the wind generation systems. This article proposes a limited-position set model-reference adaptive observer (LPS-MRAO) for control of DFIGs in wind turbine systems (WTSs) without mechanical sensors, i.e., without incremental encoders or speed transducers. The concept of of the developed LPS-MRAO is obtained from the finite-set model predictive control (FS-MPC). In the proposed LPS-MRAO, an algorithm is presented in order to give a constant number of angles for the rotor position of the DFIG. By using these angles, a certain number of rotor currents can be predicted. Then, a new quality function is defined to find the best angle of the rotor. In the proposed LPS-MRAO, there are not any gains to tune like the classical MRAO, where a proportional-integral is used and must be tuned. Finally, the proposed LPS-MRAO and classical one are experimentally implemented in the laboratory and compared at various operation scenarios and under mismatches in the parameters of the DFIG. The experimental results illustrated that the estimation performance and robustness of the proposed LPS-MRAO are better than those of the classical one.

Balanced parallel instantaneous position control of PMDC motors with low-cost position sensors

This paper presents an advanced parallel position control scheme for dual permanent DC (PMDC) motors based on a low-cost and low-resolution Hall sensor, which decreases the control performance and accuracy due to the insufficient resolution and slow response in the low-speed range. To balance and improve the position control performance of both PMDC motors, an instantaneous position compensation based on operating time and a current model speed observer with an adaptive sliding mode observer based on the back electromotive force (EMF) constant are presented in this paper. The insufficient resolution and low dynamic response of the Hall sensor can be improved by the advanced current model reference adaptive observer using the back EMF bias calculation and the sliding mode observer of the back EMF constant. From the proposed sensor–sensorless combined estimation method, precise continuous speed and position information can be estimated at every sampling period. To compensate for speed and position estimation errors, the back EMF constant can be adjusted with the average speed error between the speed observer and the actual speed obtained from the Hall sensor. For the balance control of parallel PMDC motors, instantaneous position and speed reference control based on the operating time is presented. In the proposed control method, the speed reference is determined by the time-based speed reference, the instantaneous position error and the position error between two motors. Smooth balancing can be achieved from the compensation term of the balanced position error. The control performance of the proposed scheme for a dual PMDC motor system is verified by comparative simulations and experiments. In both simulations and experiments, the proposed method shows a significant improvement in the position control when compared to that of the conventional control method.

Stator Flux Based Model Reference Adaptive Observers for Sensorless Vector Control and Direct Voltage Control of Doubly-Fed Induction Generator

A position sensorless operation of a doubly-fed induction generator (DFIG) is desired from considerations of cost, maintenance, cabling, and reliability. This article proposes two stator flux based model reference adaptive observers (SF-MRAOs) for the estimation of the rotor speed and position in a stand-alone DFIG. The cross product of the reference and estimated stator flux linkage vectors is fed as controller input in the existing method, thereby, making the observer model nonlinear. The first proposed method, which is based on notch filtering, offers a performance comparable to that of the existing method while reducing the number of voltage and current sensors required. The second proposed method linearizes the error input to the controller, making the controller design straight forward, and also leading to superior performance than the existing methods. The linearized SF-MRAO is shown to work successfully with good dynamic performance in vector control of a stand-alone DFIG. This article also shows that the proposed linearized SF-MRAO can be employed for obtaining the rotor current angle in direct voltage control of a stand-alone DFIG. Simulation and experimental results are presented from a laboratory prototype of a 10-hp DFIG coupled to a squirrel-cage induction motor. The sensitivity of the performance of the proposed linearized SF-MRAO to variations in machine parameters is also studied theoretically and experimentally.

Speed-Sensorless Dual Reference Frame Predictive Torque Control for Induction Machines

In finite control set predictive torque control (FCS-PTC), mismatched parameters will lead to the electromagnetic torque prediction error. To solve the aforementioned problem, this paper proposes feedback-correction-based dual reference frame predictive torque control for induction machines, abbreviated as DRF-PTC. First, a DRF flux observer is proposed, which abandons a traditional model reference adaptive observer with rotor speed as adaptive variable. The proposed flux observer decouples the flux observation and the speed estimation and improves the estimation accuracy of flux linkage and rotor speed. Second, a DRF-PTC is proposed to eliminate the effect of speed estimation error on torque prediction. For the influence of mismatched parameters, a correction term is incorporated in double reference frame torque prediction equations, in which the correction term is derived from the correction term of the proposed flux observer. Finally, the proposed DRF-PTC in this paper is verified on the experimental platform of an induction machine. Experimental results show that the proposed DRF-PTC has excellent performance in speed estimation and electromagnetic torque prediction, compared with the traditional FCS-PTC.

Speed sensorless control of a six‐phase induction motor drive using backstepping control

In this study, a direct torque and flux control is described for a six-phase asymmetrical speed and voltage sensorless induction machine (IM) drive, based on non-linear backstepping control approach. First, the decoupled torque and flux controllers are developed based on Lyapunov theory, using the machine two axis equations in the stationary reference frame. In this control scheme, the actual stator voltages are determined from dc-link voltage using the switching pattern of the space vector pulse-width modulation inverter. Then, for a given motor load torque and rotor speed, a so-called fast search method is used to maximise the motor efficiency. According to this method, the rotor reference flux is decreased in the small steps, until the average of real input power to the motor reaches to a minimum value. In addition, a model reference adaptive system-based observer is employed for online estimating of the rotor speed. Finally, the feasibility of the proposed control scheme is verified by simulation and experimental results.

Adaptive Speed Observer for a Stand-Alone Doubly Fed Induction Generator Feeding Nonlinear and Unbalanced Loads

In this paper, an improved sensorless control algorithm for a variable speed constant frequency doubly fed induction generator is presented. Unlike previously reported methods the proposed algorithm does not require the rotor position or speed information for the stator field orientation of the rotor variables. The slip frequency is estimated by a reactive power-based model reference adaptive observer and is used in the rotor current controllers for back emf compensation. A new on-line estimation method for the magnetizing inductance of the machine is also proposed to enhance the performance of the controller. Small-signal models of the slip frequency and the magnetizing inductance estimators are developed to aid their design. The proposed algorithm is capable of “speed catching on the fly” and performs satisfactorily with balanced, unbalanced, linear, and nonlinear loads (in any combination) particularly, nonlinear unbalanced loads, which has not been reported in the literature so far. Experimental and simulation results are presented to demonstrate an excellent load voltage regulation property of the control algorithm during severe transient operating conditions. Total harmonic distortion and unbalance of the load voltage and stator current even with large nonlinear/unbalanced loads are also found to be much smaller compared to systems reported earlier.

Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks.

Robust Decoupled Control of Direct Field-Oriented Induction Motor Drive

This paper focuses on the development of a decoupling mechanism and a speed control scheme based on total sliding-mode control (TSMC) theory for a direct rotor field-oriented (DRFO) induction motor (IM). First, a robust decoupling mechanism including an adaptive flux observer and a sliding-mode current estimator is investigated to decouple the complicated flux and torque dynamics of an IM. The acquired flux angle is utilized for the DRFO object such that the dynamic behavior of the IM is like that of a separately excited dc motor. However, the control performance of the IM is still influenced seriously by the system uncertainties including electrical and mechanical parameter variation, external load disturbance, nonideal field-oriented transient responses, and unmodeled dynamics in practical applications. In order to enhance the robustness of the DRFO IM drive for high-performance applications, a TSMC scheme is constructed without the reaching phase in conventional sliding-mode control (CSMC). The control strategy is derived in the sense of Lyapunov stability theorem such that the stable tracking performance can be ensured under the occurrence of system uncertainties. In addition, numerical simulations as well as experimental results are provided to validate the effectiveness of the developed methodologies in comparison with a model reference adaptive system flux observer and a CSMC system.

Adaptive Observer for Sensorless Control of Permanent Magnet Synchronous Motor Drives

This paper develops a sensorless control method for nonsalient permanent magnet synchronous motor drives. The position and speed estimations are based on the back electromotive force (emf) estimation in f g stator reference. Two equivalent solutions are developed to estimate the back emf (i.e., the adaptive filter technique), and alternatively, an extended disturbance observer, both being speed adaptive. The position estimation is computed directly from the back emf components. The speed estimation uses a model reference adaptive observer as a sinusoidal oscillator external synchronized by the back emf with (i) an amplitude adaptive correction speed depending, and (ii) a phase correction realized by an adaptive mechanism using a variable structure plus a proportional integral compensator. The speed sign is included. The speed and position observers can be independently tuned, and the estimations are robust to parameter deviations. A relatively large speed range of 1:100 is obtained. Extensive simulation results are given and discussed.

Asymptotically stable adaptive load torque observer for precision position control of BLDC motor

A new control method for the precision robust position control of a brushless DC (BLDC) motor using the asymptotically stable adaptive load torque observer is presented. A precision position control is obtained for the BLDC motor system approximately linearised using the field-orientation method. DC motors have been gradually replaced by the BLDC motor, since the industry applications require more powerful actuators in small sizes. Many of these motor systems have BLDC motors to obtain high power rates. On the other hand, the disadvantages are the high cost and more complex controller caused by the complex driving principle of BLDC motors, and the load torque disturbance is directly affected to a motor shaft. The application of the load torque observer using fixed gain has been published (Ko et al, 1993). However, the flux linkage is not exactly known for a load torque observer. There is a problem of uncertainty of obtaining very high precision position control. Therefore, a model reference adaptive observer was considered to overcome the problem of the unknown parameter and torque disturbance (Ko et al, 1994), but this is a case of BIBO stability. A new model reference adaptive observer is considered and stability analysis is carried out using the Lyapunov stability theorem. As a result, asymptotically stable observer gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feed-forwarding the equivalent current having the fast response.