Model Reference Adaptive System Observer Research Articles

Control Strategy of Flywheel Energy Storage System for Improved Model Reference Adaptive System Based on Tent-Sparrow Search Algorithm

This study addresses speed sensor aging and electrical parameter variations caused by prolonged operation and environmental factors in flywheel energy storage systems (FESSs). A model reference adaptive system (MRAS) flywheel speed observer with parameter identification capabilities is proposed to replace traditional speed sensors. The proposed method uses reference and adjustable models to identify the stator resistance and permanent magnet flux (PM Flux) to mitigate the adverse effects of electrical parameter changes on control performance. The Tent chaotic mapping-improved Sparrow Search Algorithm (SSA) optimizes the Proportional-Integral (PI) controller parameters for the dual closed-loop and MRAS speed adaptation laws of the flywheel motor. Moreover, a self-switching parameter identification (SSPI) scheme, which constructs a cost function based on the current, parameter identification, and speed errors, is proposed to prevent inaccuracies in parameter identification. The MRAS observer selects the appropriate PI adaptive mechanism based on the error values, thereby enhancing identification accuracy. Simulink simulations show significant improvements in the rapidity and accuracy of the Tent-SSA optimized MRAS flywheel speed observer, enhancing the stability and robustness of the flywheel rotor. Experimental validation on a constructed FESS platform confirms the feasibility of this method.

Sensorless fuzzy-sliding mode control of five phases permanent magnet synchronous motor using MRAS: in three different operating modes

This paper presents a comprehensive study on sensorless control techniques for five-phase permanent magnet synchronous motors (5P-PMSMs). To optimize the speed control performance of (5P-PMSM), which has more advantages than its counterpart three-phase PMSM system, we utilized a combination of fuzzy logic and sliding mode control techniques to optimize the proposed sliding mode control. Additionally, the Model Reference Adaptive System (MRAS) is employed to estimate the speed and rotor position of the 5P-PMSM to enhance the robustness and adaptability of the control system. The modelling of the machine, detailed with a robust nonlinear strategy based on the sliding control, is introduced to track the system until the desired sliding surface is achieved first. To guarantee that the tracking errors converge, the sliding mode control has a chatter due to the discontinuous term. To mitigate the drawback, the proposed control is designed by combining SMC with fuzzy logic, enhancing the performance in a steady state. Examining the control performance of the integrated control fuzzy-SMC with MRAS in different operating modes, including three tests in reversal speed operation, open phase fault mode, and the low-speed operating mode under load torque. The main aim is to assess and analyze the robustness and performance of the proposed control strategy. The stability of the overall control system is examined using the Lyapunov theorem and Popov’s theory analysis of MRAS observer stability. The simulation results of the suggested control displayed by MATLAB-Simulink illustrate the effectiveness and adaptability of the sensorless control scheme across different operating conditions, offering promising prospects for practical implementation in industrial applications.

An improved sliding mode model reference adaptive system observer for PMSM applications

This paper introduces a sensorless control strategy of permanent magnet synchronous motors, termed the fast super twisting algorithm-based sliding mode improved model reference adaptive system observer (FSTA-SM-IMRASO). The proposed observer builds upon the conventional model reference adaptive system observer (MRASO) by incorporating a feedback correction term. Additionally, an adaptive feedback gain is devised to accommodate varying system operating conditions, thereby significantly enhancing the convergence speed of the error between the reference model and the adjustable model. Furthermore, a fast super twisting algorithm featuring an enhanced exponential term is devised and integrated with the model reference adaptive system theory, replacing the conventional PI controller used in MRASO. This integration leads to notable improvements in the system dynamic and static capabilities. Finally, the effectiveness of the proposed strategy is verified by simulation.

Sensorless control of permanent magnet synchronous motor for exhaust energy recovery of internal combustion engine: a comparison between Kalman filter and MRAS observer

This paper deals with the sensorless control of a Permanent Magnet Synchronous Motor (PMSM) to be employed on a turbo-generator to recover the exhaust gas energy of an Internal Combustion Engine (ICE). The main problem with this application is the high rotational speed required by the exhaust gas turbo-generator. Indeed, this implies the difficulty of installing an encoder for speed measurement and control. For this reason, sensorless control is highly recommendable, but, on the other hand, the main sensorless techniques could fail in this peculiar situation because of the high computational effort required compared with the other sensorless applications. Moreover, a good knowledge of the model parameters is necessary. Therefore, the main goal of this paper is to compare two main sensorless techniques for rotational speed measurement, both in the deterministic framework (Model Reference Adaptive System (MRAS) observer) and stochastic framework (Extended Kalman Filter (EKF)), to verify their effectiveness, their computational load, their sensitivity against parameter variation and noisy measurements, and, finally, to present the best solution for the exhaust gas energy recovery from the internal combustion engine.

Performance analysis of a robust MF-PTC strategy for induction motor drive

The load model-based conventional predictive torque control (PTC) strategy performs as a high-performance controller at transient and steady-state conditions. However, its performance is poor on the issue of parameters variation. A robust model-free PTC (MF-PTC) strategy has been proposed in this paper to overcome the aforementioned drawback. An auto-regressive exogenous (ARX) model instead of a load model has been used to establish a model-free controller. This model is usually formed based on their input-output transfer function. A recursive least square algorithm has been employed to estimate the unknown parameters of the ARX model. Then, an observable canonical state-space model uses those estimated parameters to achieve an accurate prediction of the control variables. The performance of the proposed scheme can be affected by the variation of resistance. A resistance estimator based on the model reference adaptive system observer has been applied to improve the robustness of the system against variation of the stator and rotor resistance, and inductance measurement uncertainty. Simulation results show that the proposed MF-PTC scheme is robust against parameters uncertainty and works well at transient and steady-state conditions.

Fractional order second-order sliding mode MRASO for SPMSM

To improve the accuracy of the sensorless control system for permanent magnet synchronous motors, this paper proposes the based on fractional order integral sliding mode theory in the model reference adaptive system observer. The purpose of this approach is to enhance the robustness of the system. Furthermore, this paper introduces the second-order sliding mode reaching law to suppress chattering phenomena and improve the control accuracy of the observer. Simulation results show that this strategy achieves excellent dynamic and static performance.

Modified Super-Twisting Algorithm-Based Model Reference Adaptive Observer for Sensorless Control of the Interior Permanent-Magnet Synchronous Motor in Electric Vehicles

In this paper, the model reference adaptive system (MRAS) method has been employed to observe speed in sensorless field-oriented control (FOC) with flux weakening (FW) and maximum torque per ampere (MTPA) operations for the interior permanent-magnet synchronous motor (IPMSM). This paper focuses on the modified MRAS observer, which is based on the sigmoid function as a switching function and also the adaptive sliding mode coefficient. The sliding mode strategies are employed for the adaptation mechanism instead of the PI controller. The conventional PI-MRAS causes oscillations in rotor speed. To solve this problem, the modified adaptive super-twisting algorithm (STA)-based MRAS method is proposed by utilizing the sigmoid function. The proposed modified MRAS is compared to conventional methods. Additionally, it is examined for performance against the fast terminal sliding mode (FTSM), which is applied to the MRAS as an adaptation mechanism in terms of sliding mode strategies. The modified STA-MRAS is explored under the ECE and EUDC (Extra Urban Driving Cycle) drive cycles for electric vehicle applications. Finally, the obtained results show the validity and capability of the proposed adaptive STA-MRAS in terms of speed tracking.

Improved Deadbeat Predictive Thrust Control for Linear Induction Machine With Online Parameter Identification Based on MRAS and Linear Extended State Observer

This paper proposes an improved deadbeat predictive thrust control (IDPTC) for linear induction machine (LIM) drives based on online parameter identification. First, to achieve fast thrust dynamic response with low thrust ripples, a DPTC method is induced based on the reference primary flux vector calculator and discrete-time LIM model. Second, a novel online magnetizing inductance identification is designed based on back electromotive force model reference adaptive system (MRAS) and linear extended state observer. Compared to the conventional MRAS identification strategy, there is no pure integration and differential operation in both reference and adaptive models for the proposed method, so that integral initial values, dc bias and high-frequency-noise amplification problems can be solved. Then, to improve the robustness of DPTC against magnetizing inductance mismatch, the proposed online parameter identification is further combined with the DPTC method, in which the flux can also be estimated as an intermediate variable without conventional parameter-based flux observer. Finally, comprehensive simulation and experiments have been conducted on one 3 kW arc induction machine, showing that the proposed method can effectively eliminate the influence of magnetizing inductance mismatch on the control performance and significantly improve the parameter robustness compared to the existing DPTC methods.

A Dual Observer for Parameter-Free Encoderless Control of Doubly-Fed Reluctance Generators

A novel, cascaded model reference adaptive system (MRAS) observer design for speed and reactive power ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf{Q}$</tex-math></inline-formula> ) control of the emerging brushless doubly-fed reluctance generator (BDFRG) without a shaft position sensor, and no machine parameter knowledge, is proposed. The main advantages of the underlying estimation technique over the existing ones reported in the open literature are the intrinsic versatility, robustness, and accuracy, offering entirely decoupled torque (power) and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf{Q}$</tex-math></inline-formula> responses. The reference model of the rotor angular velocity and position MRAS observer is purely based on the current measurements of the converter-fed (secondary) winding, and its adaptive counterpart on the measured grid voltages and currents at line frequency. The latter requires the inductance ratio for calculations, the online estimates of which being generated by the supplementary MRAS observer working in parallel. Doing so, a complete machine parameter independence and stability of the scheme have been achieved, and its viability fully experimentally validated under variable loading conditions of the small-scale BDFRG wind turbine emulated in a laboratory environment.

Design and Xilinx Virtex-field-programmable gate array for hardware in the loop of sensorless second-order sliding mode control and model reference adaptive system–sliding mode observer for direct torque control of induction motor drive

This article aims first to propose an improved space vector modulation–direct torque control in order to enhance the induction motor performance using: (1) a super-twisting controller and (2) a novel model reference adaptive system based on a sliding mode observer. Second, due to the complexity of the suggested control algorithm, this article deals also with a hardware implementation on a field-programmable gate array board. Indeed, the field-programmable gate array is mainly chosen to reduce the execution time, thanks to its parallel processing which significantly improves the quality of the control system by reducing the sampling period, and consequently the delays in the control loop. Besides, the super-twisting controller is proposed to enhance the speed regulation loop which is a second-order sliding mode control technique that uses a continuous control law to prevent the chattering phenomenon induced by the first-order sliding mode control technique. Moreover, the high performance control requires information about the rotor speed which can be obtained by a sensor. Generally, the use of the speed sensor increases the system cost and size, and reduces its system reliability. Therefore, a combination between a model reference adaptive system observer and a sliding mode observer is suggested for speed estimation and overcoming the sensitivity of the classical model reference adaptive system observer against uncertainties and stator resistance variations. The performance of the proposed space vector modulation--direct torque control--super-twisting controller with the model reference adaptive system--sliding mode observer algorithm of an induction motor is verified through simulation, hardware co-simulation and experimental validation utilizing a field-programmable gate array Virtex-5-ML507 board. The performance of the suggested sensorless control method is compared also with other recent published schemes.

Second-Order ESO-Based Current Sensor Fault-Tolerant Strategy for Sensorless Control of PMSM With B-Phase Current

Usually, two-phase current sensors are required to realize sensorless control of permanent magnet synchronous motor (PMSM). However, once the phase current sensor fails, the whole system will not work. In this article, a novel second-order extended state observer (SO-ESO) based current sensor fault-tolerant strategy for realizing PMSM sensorless control and multiparameter identification is proposed, which can significantly improve the system reliability. When a fault occurs in the A-C two-phase current sensor, the proposed scheme uses only a B-phase current sensor to estimate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> axis stator current and time varying resistance, achieving a high-performance sensorless control function. In order to reduce the chattering of the system, a sigmoid function is introduced in the SO-ESO. In addition, an SO-ESO based parallel speed and multiparameter identification scheme are proposed by using two model reference adaptive system observer (MRASO). The first MRASO is designed based on super twisting algorithm with a corrective feedback loop and is used for estimating rotor speed and position. The second MRASO only needs to identify inductance and permanent flux because the stator resistance is estimated by SO-ESO. The second MRASO and SO-ESO updates the three identified electrical parameters (i.e., stator resistance, inductance, and permanent flux) and estimated currents to the first MRASO to achieve high robustness sensorless control. The relevant results show that the scheme gives good results, and the system has good dynamic performance and better fault tolerance.

Switched PI Control Based MRAS for Sensorless Control of PMSM Drives Using Fuzzy-Logic-Controller

With the use of sensorless control strategy, mechanical position sensors can be removed from the gearbox, so as to decrease the maintenance costs and enhance the system robustness. In this paper, a switching PI control based model reference adaptive system (MRAS) observer using Fuzzy-Logic-Controller (FLC) is introduced for sensorless control of permanent magnet synchronous motor (PMSM) drives. The main work and innovation of this paper include: 1) A disturbance observer based voltage compensation method is proposed to solve the problems of voltage distortion in voltage source inverter (VSI) fed PMSM systems. 2) A double closed-loop FLC is designed for speed and current control. The response performance of speed regulation and the accuracy of the command voltage are improved, and the difficulty of manual adjustment of control parameters is avoided. 3) A sensorless control strategy of a switching PI control based MRAS observer is proposed for stator resistance tracking. By setting different thresholds, the proposed MRAS observer can choose the appropriate PI adaptive mechanism based on the amplitude of the current error variable, which can improve the accuracy of resistance estimation and improve the dynamic performance of sensorless control. 4) The experimental results are given to verify the availability of the proposed scheme.

Sensorless Speed Contorl of Doubly-Fed Induction Machine Using Reactive Power Based MRAS

A sensorless speed control method for doubly-fed induction machine (DFIM) operating with constant frequency but in variable speed mode is presented in this project work. The control method is based on rotor speed estimation technique by a reactive power model reference adaptive system (MRAS) observer. The presented technique does not depend on any kind of flux evaluation and also independent to the resistance variation of either stator or rotor. The MRAS observer has a capacity for speed catching operation. PI controller is designed and also optimized using algorithm for better dynamic behaviour of the machine. MATLAB Simulink model and the simulation results are shown to check the effectiveness of the observer and also of the controller.

Parameter independent control of doubly-fed reluctance wind generators without a rotor position sensor

A novel model reference adaptive system (MRAS) based estimation technique for sensorless operation of a brushless doubly fed reluctance generator (BDFRG) with maximum power point tracking (MPPT) is proposed. The main advantage of this development is the truly machine parameter independent rotor angular velocity MRAS observer complemented by an original position error compensation scheme for higher accuracy, making it clearly superior to the existing designs. The simulation and experimental results have demonstrated the excellent performance prospects for typical wind turbines emulated in a laboratory environment.

A Newly Designed VSC-Based Current Regulator for Sensorless Control of PMSM Considering VSI Nonlinearity

A novel d-axis variable-structure control (VSC) current regulator is proposed for realizing fast and accurate sensorless control in the surface-mounted permanent magnet synchronous motor (SPMSM) in this article. In this proposed regulator, the sigmoid function is employed as a switching control law to reduce the chattering effect and increase the degrees of freedom in tuning the regulator. The sensorless control performance under the d-axis VSC current regulator is testified by using the model reference adaptive system (MRAS) and sliding-mode control (SMC) method. In the MRAS observer, the adaptive law of speed and resistance is designed so that resistance, speed, and position can be estimated simultaneously, which can eliminate the influence of the resistance variations theoretically. In the sliding-mode observer, the back electromotive force observer is employed to estimate the speed and position of PMSM so that the estimation can cover a relative low-speed range because pure integration is not employed. Furthermore, the dead-time compensation voltages (DTCV) strategy is employed to online estimate disturbance voltage in a feed-forward manner, which can improve the sensorless control performance of PMSM. Experimental results obtained from an SPMSM drive system validate the superiority of the proposed d-axis VSC current regulator.

Sensorless Control of Ship Shaft Stand-Alone BDFIGs Based on Reactive-Power MRAS Observer

This article proposes a rotor position observer based on a reactive power model reference adaptive system (MRAS) for sensorless direct voltage control (DVC) strategy of the stand-alone brushless doubly fed induction generators (BDFIGs). The proposed MRAS observer is based on the control winding (CW) reactive power and the power winding (PW) field orientation. The suggested new sensorless control method does not require flux computation, which can ensure the simplicity and efficacy of the proposed method. The stability analysis of the new observer is investigated and confirmed with the concept of hyperstability and using Popov's criterion methodology. The robustness of the new control method is analyzed under parameter uncertainties. Furthermore, comprehensive simulation and experimental results are obtained with a prototype wound-rotor BDFIG. The corresponding results confirm the capability and effectiveness of the proposed sensorless DVC strategy with a good transient behavior under different operating conditions for the stand-alone BDFIG system. Moreover, these results assure that the presented rotor position observer is robust via any machine parameter change.

Speed Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent-Magnet Machine Based on Model Reference Adaptive System

A novel 6/13-pole hybrid excitation axial field flux-switching permanent magnet machine (HEAFFSPMM) exhibits strong fault tolerance capability, high efficiency, and large torque density. However, merely few research on speed sensorless control in HEAFFSPMM exists. The speed sensorless control methods based on model reference adaptive system (MRAS) are studied and compared for the machine to improve the stability and reliability of the system and consequently improve the application of machine in control system. Based on the field-oriented control strategy, the MRAS observer of speed is designed and built by applying stator currents, stator flux linkages, and simplified stator currents. The three speed sensorless control algorithms of MRAS are compared and analyzed by using MATLAB/Simulink simulation and dSPACE1104 experimental platform. Results show that the speed sensorless control algorithm based on simplified stator currents has good control performance and high control accuracy.

Sensorless Control of Brushless Doubly Fed Induction Machine Using a Control Winding Current MRAS Observer

In order to realize sensorless control for brushless doubly fed induction machine (BDFIM), this paper presents a model reference adaptive system (MRAS) observer, designed based on the error of the control winding current. Furthermore, a phase-locked loop is employed to estimate the current winding position and rotor speed. Consequently, a detailed theoretical derivation proves that the MRAS observer is stable and the dynamic performance is good. Thus, it does not cause any estimated speed error in steady state. Moreover, the estimated position error is bounded and trivial, thus its effects on the sensorless control of the BDFIM are neglected. The correctness, feasibility, and robustness of the proposed sensorless control method are verified by means of experimental validation on a 30 kW test rig.

Sensorless control and diagnosis of synchronous generator used in wind energy conversion system under inter turn short-circuit fault

This paper deals with control and diagnosis of the synchronous generator (SG) used in a wind energy conversion system under inter turn short-circuit fault. In the first part of this paper, a speed sensorless control of the synchronous generator is presented. In this case speed estimation is carried out using model reference adaptive system (MRAS). In the second part, the MRAS observer is associated with the Luenberger observer in order to estimate the stator resistances according d and q axis. The stability of the system is proved by using Lyapunov theory. Finally, the proposed new hybrid observer MRAS-Luenberger is used to detect the turn-to-turn short circuit faults. The Park's vector approach (PVA) is adopted to take decision if there are faults. The proposed technique is tested on dSPACE DS1103 and the results confirm the efficacy to detect the fault by observing the shape. This method gives us the right information for the fault isolation.

MRAS speed observer for sensorless adaptive intelligent backstepping controller of induction machines

In this paper, a sensorless adaptive neuro-fuzzy backstepping control scheme is developed for induction machines with unknown model, uncertain load-torque and nonlinear friction where the speed is obtained using the model reference adaptive system (MRAS). Neurofuzzy systems are used to online approximate the uncertain nonlinearities and an adaptive backstepping technique is employed to systematically construct the control law. The MRAS observer is based on two different models, one that is speed independent (reference model) and another that is speed dependent (adjustable model). The speed is estimated via the outputs of the two models. The proposed sensorless controller guarantees the tracking errors converge to a small neighbourhood of the origin and the boundedness of all closed-loop signals what demonstrate the effectiveness of the proposed approach.