Magnetic Modelling of Synchronous Reluctance and Internal Permanent Magnet Motors Using Radial Basis Function Networks

The general trend toward more intelligent energy-aware ac drives is driving the development of new motor topologies and advanced model-based control techniques. Among the candidates, pure reluctance and anisotropic permanent magnet motors are gaining popularity, despite their complex structure. The availability of accurate mathematical models that describe these motors is essential to the design of any model-based advanced control. This paper focuses on the relations between currents and flux linkages, which are obtained through innovative radial basis function neural networks. These special drive-oriented neural networks take as inputs the motor voltages and currents, returning as output the motor flux linkages, inclusive of any nonlinearity and cross-coupling effect. The theoretical foundations of the radial basis function networks, the design hints, and a commented series of experimental results on a real laboratory prototype are included in this paper. The simple structure of the neural network fits for implementation on standard drives. The online training and tracking will be the next steps in field programmable gate array based control systems

Performance Comparison of Field-oriented Control, Direct Torque Control, and Model-predictive Control for SynRMs

Simulation studies of three synchronous reluctance motor (SynRM) control strategies are presented: field-oriented control (FOC), direct torque control (DTC), and finite-set model-predictive control (FS-MPC). FOC uses linear controllers and pulse-width modulation to control the fundamental components of the load voltages vectors. In contrast, DTC and FS-MPC are nonlinear strategies wherein the voltage vectors are directly generated in the absence of a modulator. Theoretical operating principles and control structures of these control strategies are presented. Moreover, a comparative analysis of the static and dynamic performance of the control strategies is conducted using Matlab/Simulink to identify their advantages and limitations. It is confirmed that each of the control strategies has merits and that all three of them satisfy the requirements of modern high-performance drives.info:eu-repo/semantics/publishedVersio

Robust Control of Synchronous Reluctance Motor Based on Automatic Disturbance Rejection

This article proposes the theoretical development and experimental application of the active disturbance rejection control (ADRC) to synchronous reluctance motor (SynRM) drives. The ADRC is a robust adaptive extension of the input-output feedback linearization control (FLC). It performs the exact linearization of the SynRM model by a suitable nonlinear transformation of the state based on the online estimation of the corrective term by the so-called extended state observers (ESO). Consequently, any unmodeled dynamics or uncertainty of the parameters are properly addressed. The control strategy has been verified successfully both in numerical simulations and experimentally on a suitably developed test set-up that provides the ADRC robustness versus parameters variations which cannot be obtained with other model-based nonlinear control techniques (e.g., FLC). Simulation results show the capability of the ADRC to maintain its dynamic performance, even in the presence of quick variations of the SynRM dynamic inductances. Experimental results confirm the robustness of the ADRC versus any model parameter uncertainty. The proposed ADRC has been experimentally compared with a previously developed FLC, in both a tuned and detuned working configuration, with the classic rotor oriented control, and with a finite state model predictive control (MPC), where speed control is integrated into the MPC. Experimental results show far better robustness versus any parameter variation

Adaptive Feedback Linearization Control of SynRM Drives With On-Line Inductance Estimation

This article proposes an adaptive input-output Feedback Linearization Control ( FLC ) techniques for Synchronous Reluctance Motor ( SynRM ) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. As a major result, it permits a null stator current steady state tracking error even with a proportional derivative controller. The estimation law is obtained thanks to a Lyapunov-based analysis and thus the stability of the entire control system, including the estimation algorithm, is intrinsically guaranteed. The proposed adaptive FLC technique, has been tested experimentally on a suitably developed test set-up, and compared experimentally with its non-adaptive versions in both tuned and detuned working conditions. Moreover, a sensitivity analysis of the performance of the adaptive FLC to the variations of the stator resistance at low speed has been made. Finally, an analysis of the effects of the iron losses on the control performance and stability at high speed in the field weakening region at medium/high loads has been made

An Advanced Model Predictive Current Control of Synchronous Reluctance Motors

Synchronous reluctance motors (SynRMs) have, in recent years, attracted much attention due to their high-efficiency output and nature of their construction denoted by the lack of expensive magnetic materials, thus cheapening the overall cost whilst increasing in robustness. These benefits have made the SynRM a strong contender against other established electric motors in the market. Similarly, model predictive current control (MPCC) has recently become a powerful advanced control technology in industrial drives, being, therefore, a suitable choice for SynRM drives granting overall high control performance and efficiency. However, current prediction in MPCC requires a high number of voltage vectors (VVs) synthesizable by the converter, being therefore computationally demanding. Accordingly, the main goal of this work is the development and analysis of a more efficient and advanced MPCC for SynRMs whilst reducing the computational burden and delivering good control performance in contrast with the standard MPCC. Therefore, to achieve the intended levels of efficiency and control performance in SynRM drives, a combination of two control strategies is developed, which combines hysteresis current control (HCC) and MPCC, dubbed in this work HCC-MPCC. Furthermore, the SynRM dynamic model equations comprising the magnetic saturating effects and iron losses are presented through a detailed theoretical and computational analysis of the drive’s control. Conclusively, the developed HCC-MPCC for SynRM drives is analyzed through thorough and rigorous experimental tests alongside the standard MPCC, whose obtained results are detailed comprehensively.Os motores síncronos de relutância (SynRMs) têm, nos últimos anos, atraído muita atenção devido às suas características construtivas, designadamente pela falta de materiais magnéticos caros, depreciando assim o custo em geral; e simultaneamente pelo aumento em robustez. Esses benefícios tornaram o SynRM num forte concorrente face a outros motores elétricos existentes no mercado. Da mesma forma, o modelo preditivo de controlo de corrente (MPCC) tornou-se recentemente numa poderosa estratégia de controlo avançado em acionamentos industriais, sendo, portanto, uma escolha adequada para acionamentos envolvendo SynRMs, garantindo elevado desempenho e eficiência de controlo. No entanto, a previsão da corrente no MPCC requer um grande número de vetores de tensão (VVs) sintetizáveis pelo conversor, sendo, portanto, exigente computacionalmente. Consequentemente, o objetivo principal deste trabalho é o desenvolvimento e análise de um MPCC mais eficiente e avançado para SynRMs, reduzindo a carga computacional e, simultaneamente, demonstrando um bom desempenho de controlo em contraste com o MPCC clássico. Portanto, para atingir os níveis pretendidos de eficiência e desempenho de controlo em acionamentos com SynRMs, uma combinação de duas estratégias de controlo é desenvolvida, combinando o controlo de corrente de histerese (HCC) e MPCC, denominado neste trabalho HCC-MPCC. Além disso, as equações do modelo dinâmico do SynRM, compreendendo os efeitos de saturação magnética e as perdas de ferro, são apresentadas através de uma análise teórica e computacional detalhada do controlo do acionamento. Conclusivamente, o HCC-MPCC desenvolvido para acionamentos com SynRMs é analisado por meio de testes experimentais conjuntamente com o MPCC padrão, sendo os resultados obtidos detalhados de forma abrangente

On tracking control problem for polysolenoid motor model predictive approach

The Polysolenoid Linear Motor (PLM) have been playing a crucial role in many industrial aspects due to its functions, in which a straight motion is provided directly without mediate mechanical actuators. Recently, with several commons on mathematic model, some control methods for PLM based on Rotational Motor have been applied, but position, velocity and current constraints which are important in real systems have been ignored. In this paper, position tracking control problem for PLM was considered under state-independent disturbances via min-max model predictive control. The proposed controller forces tracking position errors converge to small region of origin and satisfies state including position, velocity and currents constraints. Further, a numerical simulation was implemented to validate the performance of the proposed controller

A Novel 100 kW Power Hardware-in-the-Loop Emulation Test Bench for Permanent Magnet Synchronous Machines with Nonlinear Magnetics

This paper presents a high dynamic power hardware-inthe-loop (PHIL) emulation test bench to mimic arbitrary permanent magnet synchronous machines with nonlinear magnetics. The proposed PHIL test bench is composed of a high performance real-time simulation system to calculate the machine behaviour and a seven level modular multiphase multilevel converter to emulate the power flow of the virtual machine. The PHIL test bench is parametrized for an automotive synchronous machine and controlled by a motor converter using a predictive trajectory dead-beat current controller. Measurements of high dynamic current steps and phase current ripples at the real machine are reproduced precisely at the PHIL test bench. Thus, the validity of the used machine model as well as the excellent performance of the PHIL test bench is proven

Kinetic-Rotor Self-Commissioning of Synchronous Machines for Magnetic Model Identification with Online Adaptation

This paper proposes a new magnetic model self-identification technique for synchronous machines to build the flux-map look-up tables (LUTs). Provided the shaft is free to turn, an alternating self-acceleration and deceleration sequence is envisaged for identification without a dedicated experimental rig or additional hardware. Respect to previous works, the stator flux and the stator resistance are adapted online during the run, thus eliminating the need for post-processing and the sensitivity to winding temperature variations during the test. Experimental validations on a 1.1 kW synchronous reluctance (SyR) and a 11 kW permanent-magnet assisted synchronous reluctance (PM-SyR) motors are provided