Disturbance/uncertainty estimation and attenuation techniques in PMSM drives–a survey

This paper gives a comprehensive overview on disturbance/uncertainty estimation and attenuation (DUEA) techniques in permanent magnet synchronous motor (PMSM) drives. Various disturbances and uncertainties in PMSM and also other alternating current (AC) motor drives are first reviewed which shows they have different behaviors and appear in different control loops of the system. The existing DUEA and other relevant control methods in handling disturbances and uncertainties widely used in PMSM drives, and their latest developments are then discussed and summarized. It also provides in-depth analysis of the relationship between these advanced control methods in the context of PMSM systems. When dealing with uncertainties,it is shown that DUEA has a different but complementary mechanism to widely used robust control and adaptive control. The similarities and differences in disturbance attenuation of DUEA and other promising methods such as internal model control and output regulation theory have been analyzed in detail. The wide applications of these methods in different AC motor drives (in particular in PMSM drives) are categorized and summarized. Finally the paper ends with the discussion on future directions in this area

Simulink modeling and design of an efficient hardware-constrained FPGA-based PMSM speed controller

The aim of this paper is to present a holistic approach to modeling and FPGA implementation of a permanent magnet synchronous motor (PMSM) speed controller. The whole system is modeled in the Matlab Simulink environment. The controller is then translated to discrete time and remodeled using System Generator blocks, directly synthesizable into FPGA hardware. The algorithm is further refined and factorized to take into account hardware constraints, so as to fit into a low cost FPGA, without significantly increasing the execution time. The resulting controller is then integrated together with sensor interfaces and analysis tools and implemented into an FPGA device. Experimental results validate the controller and verify the design

High performance disturbance observer based control system design for permanent magnet synchronous AC machine applications

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonAn electrical machine is one of the main workforces in different industries and serves them in various applications. Machine drive control design involves many technical issues for efficient and robust exploitation. Over several decades, Permanent Magnet Synchronous Motor (PMSM) is getting preferred for industrial applications over its counterpart Squirrel Cage Induction Motor (SCIM) drive, because of their higher efficiency, power density, and higher torque to inertia ratio. In the prospective that PMSM drives are considered the drives of the future, there are still technical challenges and issues related to PMSM control. Many studies have been devoted to PMSM control in the past, but there are still some open research areas that bring worldwide researchers’ interests back to PMSM drive control. One of the approaches that may facilitate better performance, higher efficiency, and robust and reliable work of the control system is the disturbance observer-based control (DOBC) with linear and nonlinear output feedback control for PM synchronous machine applications. DOBC is adopted due to its ability to reject external and internal disturbances with improving tracking performance in the variable speed wind energy conversion system (WECS) to maximize power extraction. The high order disturbance observer (HODO) is utilized to estimate the aerodynamic torque-based wind speed without the use of a traditional anemometer, which reduces the overall cost and improves the reliability of the whole system. Also, this method has been designed to improve the angular shaft speed tracking of the PMSM system under load torque disturbance and speed variations. The model-based linear and nonlinear feedback control are used in the proposed control systems. The sliding mode control (SMC) with switching output feedback control law and integral SMC with linear feedback and state-dependent Riccati equation (SDRE) based approaches have been designed for the systems. The SDRE control accounts for the nonlinear multivariable structure of the WECS and is approximated with Taylor series expansion terms. The chattering inherited from SMC is eliminated by the continuous approximation technique. The sliding mode is guaranteed by eliminating the reaching mode in the proposed integral SMC. The model-free cascaded linear feedback control system based on the proportional-integral (PI) controllers use a back-calculation algorithm anti-windup scheme. The proposed speed controllers are synthesized with HODO to compensate for the external disturbance, model uncertainty, noise, and modelling errors. Moreover, servomechanism-based SDRE control, a near-optimal control system is designed to suppress the model uncertainty and noise without the use of disturbance observers. The proposed control systems for PMSM speed regulation have demonstrated a significant improvement in the angular shaft speed-tracking performance at the transients. Their performances have been tested under speed, load torque variations, and model uncertainty. For example, HODO-based SMC with switching output feedback control law (SOFCL) has demonstrated improvement by more than 78% than the PI-PI control system of the PMSM. The performance of the HODOs-based Integral SMC with SDRE nonlinear feedback is improved by 80.5% under external disturbance, model uncertainty, and noise than Integral SMC with linear feedback in the WECS. The HODO-based SDRE control with servomechanism has shown an 80.2% improvement of mean absolute percentage error under disturbances than Integral SMC with linear feedback in the WECS. The PMSM speed tracking performance of the proposed HODO-based discrete-time PI-PI control system with back-calculation algorithm anti-windup scheme is improved by 87.29% and 90.2% in the speed commands and load torque disturbance variations scenarios respectively. The simulations for testing the proposed control system of the PMSM system and WECS have been implemented in Matlab/Simulink environment. The PMSM speed control experimental results have been obtained with Lucas-Nuelle DSP-based rapid control prototyping kit.Center for International Program “Bolashak” of the Ministry of Education and Science Republic of Kazakhsta

Multirate input based quasi-sliding mode control for permanent magnet synchronous motor

Permanent magnet synchronous motor field oriented control system often uses dual-loop (speed and current) cascade structure, and the dynamics speeds of the two loops mismatch. The motor’s mechanical and electrical subsystems have the typical multirate characteristics. Based on the multirate control theory, this paper proposes multirate input quasi-sliding mode algorithm for the speed control loop. Under the situation of the output data loss, the proposed algorithm builds the extended input vector with the output prediction information. Due to the extended input vector, the proposed algorithm reduces the system steady state chatterring, and then improves the performance of the whole system. Simulation and experimental results demonstrate the effectiveness of the proposed algorithm

A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds

High precision demands in a large number of emerging robotic applications strengthened the role of the modern control laws in the position control of the Permanent Magnet Synchronous Motor (PMSM) servo system. This paper proposes a learning-based adaptive control approach to improve the PMSM position tracking in the presence of the friction uncertainty. In contrast to most of the reported works considering the servos operating at high speeds, this paper focuses on low speeds in which the friction stemmed deteriorations become more obvious. In this paper firstly, a servo model involving the Stribeck friction dynamics is formulated, and the unknown friction parameters are identified by a genetic algorithm from the offline data. Then, a feedforward controller is designed to inject the friction information into the loop and eliminate it before causing performance degradations. Since the friction is a kind of disturbance and leads to uncertainties having time-varying characters, an Adaptive Proportional Derivative (APD) type Iterative Learning Controller (ILC) named as the APD-ILC is designed to mitigate the friction effects. Finally, the proposed control approach is simulated in MATLAB/Simulink environment and it is compared with the conventional Proportional Integral Derivative (PID) controller, Proportional ILC (P-ILC), and Proportional Derivative ILC (PD-ILC) algorithms. The results confirm that the proposed APD-ILC significantly lessens the effects of the friction and thus noticeably improves the control performance in the low speeds of the PMSM

A Low-Complexity Optimal Switching Time-Modulated Model-Predictive Control for PMSM With Three-Level NPC Converter

Conventional finite control set model-predictive control (FCS-MPC) presents a high computational burden, especially in three-level neutral-point-clamped (NPC) converters. This article proposes a low-complexity optimal switching time-modulated model-predictive control (OST-M2PC) method for a three-level NPC converter. In the proposed OST-M2PC method, the optimal switching time is calculated using a cost function. Compared with the conventional FCS-MPC, the proposed OST-M2PC method has a fixed switching frequency as well as better power quality. The proposed OST-M2PC can operate at a 20-kHz sampling frequency, reducing the computational burden of the processor. Simulation and experimental results validate the operation of the proposed method

Soft Sensor-based Servo Press Monitoring

The force that a servo press exerts forming a workpiece is one the most important magnitudes in any metal forming operation. The process force, along with the characteristics of the die, is what shapes the workpiece. When the process force is greater than the maximum force for which the servo press was designed, the servo press integrity can be damaged. Therefore, the knowledge of the process force is of great interest for both, press manufacturers and users. As such, the metal forming sector is seeking systems that can monitor the process force and the operation of the servo press to analyse process’s performance and predict future deviations in the forming operation. Servo press users want to guarantee the quality of the formed parts and reduce facility downtimes due to malfunctions of the press. This dissertation addressed the monitoring of the process force and the dynamic performance of a servo press based on a model based statistical signal processing algorithm known as the dual particle filter (dPF). Initially both, the developed model of a servo press and the proposed dPF, have been experimentally evaluated and validated in a reduced scale test bench. The test bench has been designed and manufactured based on a design methodology that allows to replicate the kinematic and dynamic behaviour of different servo press facilities in the same test bench. The experimental validation has been also carried out in an industrial servo press under three different metal forming processes. The estimation results have proved the ability of the dPF to track the process force throughout the evaluated processes, obtaining a deviation lower than 5% with respect to the measured force signals at the maximum force position. The dPF algorithm has been accelerated by means of a field programmable gate array (FPGA) to achieve a real time estimation.Serbo prentsa batek pieza gordin bat eraldatzeko egindako prozesuko indarra edozein konformatu eragiketako magnitude garrantzitsuenetarikoa da. Prozesuko indarra da, trokelaren ezaugarriekin batera, pieza gordina eraldatzen duena. Prozesuko indarra prentsak diseinuaren arabera jasan dezakeena baino handiagoa bada, prentsak kalteak izan ditzake bere osotasunean. Beraz, prozesuko indarraren ezagutza interes handikoa da, prentsa egileentzat zein erabiltzaileentzat. Hori dela eta, metal eraldatzearen sektoreak prozesuko indarra eta prentsa beraren funtzionamendua monitoriza ditzaketen sistemen bila diardute, prentsaren jarduera aztertu eta eraldatzeko operazioetan etorkizunean izan daitezkeen desbideraketak aurreikusteko. Prentsa erabiltzaileek fabrikatutako piezen kalitatea bermatzea eta funtzionamendu akatsengatiko prentsaren geldialdiak murriztea bilatzen dute. Tesi honek servo prentsa baten prozesuko indarra eta portarea dinamikoaren monitorizazioa jorratzen ditu, dual particle filter (dPF) izeneko modeloetan oinarritutako seinalaren prozesamendu estadistikoko algoritmo baten bitartez. Lehenik eta behin, garatutako servo prentsaren modeloa eta proposatutako dPFa eskalatutako entsegutarako banku batean ebaluatu eta balioztatu dira. Eskalatutako entsegutarako bankua serbo prentsa desberdinen portaera zinematiko eta dinamikoa erreplikatzea ahalbidetzen duen metodologia baten bitartez diseinatu eta gauzatu da. Esperimentu bidezko balioztatzea serbo prentsa industrial batean ere gauzatu da hiru konformatuko prozesu desberdinetan. Estimazio emaitzek dPFak prozesuko indarrari jarraitzeko duen ahalmena forgatu dute, neurtutako indarrarekiko %5ekoa baino txikiagoko desbideraketa lortuz indar maximoa egiten den puntuan. dPF algoritmoa field programmable gate array (FPGA) baten bitartez azeleratu da, denbora errealeko estimazioa lortzeko.La fuerza que una servo prensa ejerce conformando una pieza es la magnitud más importante en cualquier operación de conformado. La fuerza aplicada, junto a las características del troquel, es la magnitud que da forma a la pieza. Cuando la fuerza de proceso es más grande que la fuerza máxima para la que fue diseñada la servo prensa, la integridad de ésta puede verse afectada. Por lo tanto, el conocimiento de la fuerza de proceso es de gr´an interés tanto para los fabricantes de prensas como para los usuarios de las mismas. Así pues, el sector del conformado está buscando sistemas capaces de monitorizar la fuerza de proceso y el funcionamiento de la servo prensa para analizar el proceso y predecir futuras desviaciones de las operaciones de conformado. Los usuarios de las servo prensas quieren garantizar la calidad de las piezas fabricadas y reducir las paradas de las servo prensas debidas al mal funcionamiento de las mismas. Esta tesis aborda la monitorización de la fuerza de proceso y el comportamiento dinámico de una servo prensa mediante un algoritmo de tratamiento estadístico de la señal conocido como el dual Particle Filter (dPF). Inicialmente, tanto el modelo desarrollado como el dPF propuesto han sido evaluados y validados experimentalmente en un banco de ensayos de escala reducida. El banco de ensayos ha sido diseñado y fabricado mediante una metodología de diseño que permite replicar el comportamiento cinem´atico y din´amico de distintas servo prensas en el mismo banco. La validación experimental también se ha llevado a cabo en una servo prensa industrial mediante tres procesos de conformado distintos. Los resultados de estimación han provado la habilidad del dPF para seguir la fuerza de proceso en los procesos evaluados, obteniendo una desviación menor que un 5% con respecto a las señales medidas en el punto donde se da la fuerza máxima. El algoritmo dPF ha sido acelerado mediante un filed programmable gate array (FPGA) para lograr estimaciones en tiempo real

Design and Implementation of Recursive Model Predictive Control for Permanent Magnet Synchronous Motor Drives

In order to control the permanent-magnet synchronous motor system (PMSM) with different disturbances and nonlinearity, an improved current control algorithm for the PMSM systems using recursive model predictive control (RMPC) is developed in this paper. As the conventional MPC has to be computed online, its iterative computational procedure needs long computing time. To enhance computational speed, a recursive method based on recursive Levenberg-Marquardt algorithm (RLMA) and iterative learning control (ILC) is introduced to solve the learning issue in MPC. RMPC is able to significantly decrease the computation cost of traditional MPC in the PMSM system. The effectiveness of the proposed algorithm has been verified by simulation and experimental results

Research on an Improved Method for Permanent Magnet Synchronous Motor

In permanent magnet synchronous motor (PMSM) traditional vector control system, PI regulator is used in the speed loop, but it has some defects. An improved method of PMSM vector control is proposed in the paper. The active-disturbance rejection control (ADRC) speed regulator is designed with the input signals of given speed and real speed and the output of given stator current q coordinate component. Then, in order to optimize ADRC controller, the least squares support vector machines (LSSVM) optimal regression model is derived and successfully embedded in the ADRC controller. ADRC observation precision and dynamic response of the system are improved. The load disturbance effect on the system is reduced to a large extent. The system anti-interference ability is further improved. Finally, the current sensor CSNE151-100 is selected to sample PMSM stator currents. The voltage sensor JLBV1 is used to sample the stator voltage. The rotor speed of PMSM is measured by mechanical speed sensor, the type of which is BENTLY 330500. Experimental platform is constructed to verify the effectiveness of the proposed method