Relevant bibliographies by topics / Intelligent controller PMSM drive

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Intelligent controller PMSM drive'

Author: Grafiati
Published: 5 June 2025
Last updated: 24 June 2025

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Journal articles on the topic "Intelligent controller PMSM drive"

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Megrini, Meriem, Ahmed Gaga, and Youness Mehdaoui. "Enhancement of Field Oriented Control for Permanent Magnetic Synchronous Motor using Ant Colony Optimization." WSEAS TRANSACTIONS ON POWER SYSTEMS 19 (March 1, 2024): 18–25. http://dx.doi.org/10.37394/232016.2024.19.3.

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Because of its frequent use in diverse systems, the PMSM drive must be controlled. Field-oriented control (FOC) based PMSM drive is modeled in the present work to optimize the torque and speed performance of the PMSM. The FOC is based on a dissociated speed and flux control approach, which controls the speed and flux of the PMSM independently. The standard Proportional Integrator Derivative (PID) controller regulates the speed in FOC, which is noted for its increased resilience in linear systems, however in nonlinear ones, the PID controller responds poorly to changes in the system’s variables. In this case, the best solutions are frequently based on optimization techniques that produce the controller’s gains in every period. Optimizing the PID’s behavior in response to the system’s nonlinear behavior. The novel proposed strategy for enhancing the gains of the PID controller by employing a cost function such as Integral Time Absolute Error (ITAE) is based on PID speed regulation and is optimized using the Ant Colony Optimization algorithm (ACO) for FOC. To confirm the strategy’s aims, the suggested method is implemented on Matlab/Simulink. The simulation results demonstrated the efficiency of the intelligent ACO-FOC control, which delivers good performance in terms of stability, rapidity, and torque fluctuations.
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Waley, Salam, Chengxiong Mao, and Nasseer K. Bachache. "Biogeography Based Optimization Tuned Fuzzy Logic Controller to Adjust Speed of Electric Vehicle." TELKOMNIKA Indonesian Journal of Electrical Engineering 16, no. 3 (2015): 509. http://dx.doi.org/10.11591/tijee.v16i3.1642.

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There are many power electronic converters and motor drives connected together to form the electrical system of an Electric Vehicle. In this paper, we have presented a modeling tool that has the advantages of utilizing capabilities of the PMSM software in detailed simulations of converters, motor drives, and electric machines. In addition, equivalent electrical models of Electric Vehicle drive system. This paper also gives a brief idea of PMSM validity as an Electric Vehicle simulation tool. PMSM drive system is described and analyzed due to its importance in many applications especially in Electric Vehicle applications. Applications due to their high efficiency, low inertia and high torque to volume ratio. In this paper we embody the simulation of Fuzzy Logic Controller. The controller govern the speed control of Electrical Vehicle EV using permanent magnet synchronous motor PMSM. This work characterizes to obtain the optimal parameters of FLC. Biogeography Based Optimization (BBO) is a new intelligent technique for optimization; it can be used to tune the parameters in different fields. The main contribution of this work efforts the ability of BBO to design the parameters of FLC by determining the shapes of triangle memberships of the inputs and output. The results of optimal controller (BBO-FLC) compared with the other controllers designed by Genetic Algorithm GA which it is a powerful method has been found to solve the optimization problem. The implementation of BBO algorithm has been done by M-file/Matlab, this program linked with SIMULINK to calculate the finesses function which has the complete mathematical system model has implemented using. The results show the excellent performance of BBO-FLC compared with GA-FLC and PI controller, also the proposed method was very fast and need a few number of iterations. These results also confirmed that the transient torque and current never exceed the maximum permissible value.
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Hoai, Hung-Khong, Seng-Chi Chen, and Hoang Than. "Realization of the Sensorless Permanent Magnet Synchronous Motor Drive Control System with an Intelligent Controller." Electronics 9, no. 2 (2020): 365. http://dx.doi.org/10.3390/electronics9020365.

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This paper presents the sensorless control algorithm for a permanent magnet synchronous motor (PMSM) drive system with the estimator and the intelligent controller. The estimator is constructed on the novel sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate the position and speed of the rotor. The intelligent controller is a radial basis function neural network (RBFNN)-based self-tuning PID (Proportional-Integral-Derivative) controller, applied to the velocity control loop of the PMSM drive control system to adapt strongly to dynamic characteristics during the operation with an external load. The I-f startup strategy is adopted to accelerate the motor from standstill, then switches to the sensorless mode smoothly. The control algorithm program is based on MATLAB and can be executed in simulations and experiments. The control system performance is verified on an experimental platform with various speeds and the dynamic load, in which the specified I-f startup mode and sensorless mode, inspected by tracking response and speed regulation. The simulation and experimental results demonstrate that the proposed method has worked successfully. The motor control system has smooth switching, good tracking response, and robustness against disturbance.
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Kant, Surya, Mini Sreejeth, Madhusudan Singh, et al. "Development of intelligent hybrid controller for torque ripple minimization in electric drive system with adaptive flux estimator: An experimental case study." PLOS ONE 20, no. 3 (2025): e0312946. https://doi.org/10.1371/journal.pone.0312946.

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In order to ensure optimal performance of permanent magnet synchronous motors (PMSMs) across many technical applications, it is imperative to minimize torque fluctuations and reduce total harmonic distortion (THD) in stator currents. Hence, this study proposes the utilization of an adaptive flux estimator (AFE) in conjunction with an Intelligent Hybrid Controller (IHC) to mitigate the ripples and total harmonic distortion (THD). The IHC system is constructed by integrating PI and fuzzy logic controllers (FLC) in a cascade configuration, alongside a new switching unit that facilitates automatic switching between the two controllers during various operations of the PMSM. AFE estimates accurate flux which is required to achieve ripple free high dynamic performance of the PMSM drive by using a limiter to fix the flux at reference flux value of the drive. The proposed controller with AFE has achieved its originality through the refinement of membership functions located at the center of the universe of discourse (UOD) and the enhancement of the switching function. These improvements have resulted in increased sensitivity in the proximity to the reference speed. The Fuzzy Logic Controller (FLC) demonstrates superior performance when operating in a transient state, whereas the Proportional-Integral (PI) controller of the proposed system exhibits satisfactory performance under steady-state situations. The efficacy of AFE with IHC is substantiated by the simulation and experimental analysis reported in this study. A significant reduction in both total harmonics distortion (THD) and torque ripples are found.
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Zhang, Li-guo, and Man-feng Dou. "Multiprotocol Communication Interface PMSM Control on Account of Industrial Configuration Software." Journal of Electrical and Computer Engineering 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/651216.

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The purpose is to achieve drive controller of PMSM connect with industrial control configuration software seamless and to meet the industrial configuration software in the demand for motor to realize intelligent control. A software interface was designed and implemented about motor drive controller and the PC the industrial control configuration base on Modbus_RTU serial communication protocol of industrial control. One kind of design and implementation methods have been proposed in the communication interfaces for industrial applications scalable multiselectivity. Using the latest high-performance multiprotocol transceiver device pin programmable SP339 as the lower machine communications chip designed optional multi-interface hardware circuit with DSP TMS320F2812 as the processor. The interface program was studied with regard to C language software of lower machine and control configuration software of PC. Database creation, data acquisition, and animation links of PC configuration software are realized. Online debugging results meet the design requirements on account of PC control configuration software and the lower machine controller hardware and software.
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Marulasiddappa, Hallikeri Basappa, and Viswanathan Pushparajesh. "Various control methods of permanent magnet synchronous motor drives in electric vehicle: a technical review." TELKOMNIKA (Telecommunication, Computing, Electronics and Control) 20, no. 6 (2022): 1225–29. https://doi.org/10.12928/telkomnika.v20i6.24236.

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Day by day use of internal combustion engines (ICE) compared to electric vehicles (EV) is deteriorating because mainly of pollution and their less fuel availability. In the present scenario, an electric vehicle plays a major role in place of an ICE vehicle. So that performance of EV can be improved by proper selection of electric motor. Initially, EV prefers induction motors for traction purposes, but complexity in controlling induction motor, permanent magnet synchronous motor (PMSM) presently used in EV by most of the electric vehicle manufacturers due to its advantages. This paper reviews on various control methods for PMSM used in EV. Various control methods are being used for EV applications. Initially, conventional direct torque control (DTC) technique being used in controlling electric motors but it has a drawback of high torque and flux ripples. Hence, intelligent controllers are predominantly using in controlling PMSM drives.
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Putra, Dwi Sudarno, Seng-Chi Chen, Hoai-Hung Khong, and Chin-Feng Chang. "Realization of Intelligent Observer for Sensorless PMSM Drive Control." Mathematics 11, no. 5 (2023): 1254. http://dx.doi.org/10.3390/math11051254.

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An observer is a crucial part of the sensorless control of a permanent magnet synchronous motor (PMSM). An observer, based on mathematical equations, depends on information regarding several parameters of the controlled motor. If the motor is replaced, then we need to know the motor parameter values and reset the observer’s parameters. This article discusses an intelligent observer that can be used for several motors with different parameters. The proposed intelligent observer was developed using machine learning methods. This observer’s core algorithm is a modified Jordan neural network. It processes Iα, Iβ, vα, and vβ to produce Sin θ and Cos θ values. It is combined with a phase-locked loop function to generate position and speed feedback information. The offline learning process is carried out using data acquired from the simulations of PMSM motors. This study used five PMSMs with different parameters, three as the learning reference sources and two as testing sources. The proposed intelligent observer was successfully used to control motors with different parameters in both simulation and experimental hardware. The average error in position estimated for the simulation was 0.0078 p.u and the error was 0.0100 p.u for the experimental realization.
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Pietrusewicz, Krzysztof. "Multi-degree of freedom robust control of the CNC X-Y table PMSM-based feed-drive module." Archives of Electrical Engineering 61, no. 1 (2012): 15–31. http://dx.doi.org/10.2478/v10171-012-0002-6.

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Multi-degree of freedom robust control of the CNC X-Y table PMSM-based feed-drive module The paper presents results of studies on linear synchronous motors controlled in CNC feed axes through an intelligent digital servodrive. The research includes a conceptual design of an open servodrive control system and identification of dynamic models of a test stand with an open CNC system. Advantages of robust control over the classic one are discussed. A hybrid predictive approach to robust control of milling machine X-Y table velocity is proposed and results of simulation tests are presented. was prepared during the work for the Ministry of Science and Higher Education grant number N N502 336936, (acronym for this project is M.A.R.I.N.E. multivariable hybrid ModulAR motIon coNtrollEr), while its main purpose is the development of new robust position/velocity model-based control system, as well as to introduce the measurement of the actual state into the switching algorithm between the locally synthesized controllers. Such switching increases the overall robustness of the machine tool feed-drive module. The paper is the extended version of material proposed in [10].
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Zhenyu, Jia,, and Kim, Byeongwoo. "Direct Torque Control with Adaptive PI Speed Controller based on Neural Network for PMSM Drives." MATEC Web of Conferences 160 (2018): 02011. http://dx.doi.org/10.1051/matecconf/201816002011.

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This paper presents an adaptive speed controller based on artificial intelligent technique to improvethe performance of classical Direct Torque Control (DTC) for Permanent Magnet Synchronous Motor (PMSM) drives. The proposed method applies back propagation (BP) based neural network (NN) to tune the parameters of classical proportional-integral (PI) speed controller. Comparisons between conventional PI speed controller and proposed method are carried out by Simulation.Simulation results demonstrate that conventional DTC system based on the proposed NN speed controller can achieve higher performance with fast speed response, small overshoot and robustness.
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Tomer, Anurag Singh, and Saty Prakash Dubey. "Response Based Comparative Analysis of Two Inverter Fed Six Phase PMSM Drive by Using PI and Fuzzy Logic Controller." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (2016): 2643. http://dx.doi.org/10.11591/ijece.v6i6.12764.

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<p>This Paper gives a complete modeling and simulation of a two inverter fed six phase permanent magnet synchronous motor drive system, Then response based comparative analysis is done on starting torque ,settling time, Steady state current at various speed levels and torque levels by changing proportional- integral (PI) controller to Fuzzy logic controller. The PI controller has some disadvantages like, more settling time, sluggish response due to sudden change in load torque etc. So an intelligent controller, based on fuzzy logic is introduced which replaces the PI-controller and its drawbacks. The performance of both the controller has been investigated and studied by comparing the different plots obtained by setting various speed level both incremented and decremented speed , at different load conditions like No-load, fix load and dynamic load through Matlab/Simulink environment. Finally it is concluded from the result that fuzzy logic based controller is robust, reliable gives quick response with high starting torque and more effective than the conventional PI controller. It is also observed that both the proposed model can also run above rated speed significantally.</p>
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Dissertations / Theses on the topic "Intelligent controller PMSM drive"

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Putanu, Edith-Alisa, and 普愛麗. "Intelligent Controller for a Networked PMSM." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/72790724830178263133.

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碩士<br>南台科技大學<br>電機工程系<br>98<br>This thesis is mainly concerned with the development of a control method for a permanent-magnet synchronous motor (PMSM) which runs in the conditions of a Networked Control System (NCS). The problems that appear when the process and the controller are separated by a network are pointed out in this thesis. As the NCS gained a major advancement recently, many efforts were made to improve and optimize the control over networks. Generally, the methodologies proposed to overcome delays and data dropouts have the disadvantage of not considering the random nature of the delays or the fact that the controller has to be replaced in order to be able to operate over a data network. To overcome these problems, an artificial neural network (ANN) and genetic algorithms (GAs) based controller is designed in this thesis. The proposed methodology aims at using existing non-networked based controllers and modifying the command with respect to current network traffic conditions. A middleware is implemented and modifies the output of the controller based on gain scheduling. The gain scheduling is designed by using an artificial neural network which is first trained offline to learn the relation between the delay and the optimal gain. The search of the gain is transformed into an optimization problem and the solution is given by a genetic algorithm. Trying to minimize a cost function, the genetic algorithm gives an optimal solution avoiding the local minima of the function. During the offline training the delays are considered constant. Afterwards, considering a UDP/IP channel for the communication between the controller and the PMSM, the delays are random and varying. The neural network is used online and a proper gain is selected so that the system remains stable and has a good enough performance despite the delays that might appear. Data dropouts are also considered, the PMSM being controlled with the last valid command. The experiments are conducted using a TMS320F2812 DSP based drive. Advantages of the proposed method are pointed out and experimental results are presented to show and support the high performance of this proposed method.
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周信宏. "Application on PMSM Drive Controller Using DSP Technology." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/88457599800193987583.

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碩士<br>南台科技大學<br>電機工程系<br>92<br>A study on PMSM motion controller technologies based on the TI TMS320LF2407 DSP is presented in this thesis. The study includes four-axis motion control technology and sensorless PMSM speed control technology. The former, there are two TMS320LF2407 DSPs is used to construct a four-axis motion controller system. In implementation, a fully digital two-axis servo motion controller for controlling two sets of PMSM is developed in each TMS320LF2407 DSP chip, that is, the detection of quadrature encoder pulse (QEP)、coordinate transformation, indirect field-orientation control, current loop controller, position loop controller, SVPWM output of two ac motor, and the trajectory planning of motion control, are all performed by software in a TMS320LF2407 DSP chip. Then, we use a CAN (control area network) bus to connect two DSPs to construct a four-axis servo motion controller. The latter, we use an indirect estimated method to design a sensorless PMSM speed control. First, the approach is based on the estimation of the motor back-EMF through a sliding mode observer and a cascaded low-pass filter to estimate the magnetic angle and the rotor speed. Then, those estimated values are feedback for vector control in the current loop and for speed control in the speed loop. Due to the method of sensorless PMSM speed control don’t use the QEP sensor, it can make cost down and increase the system reliability. At last, an experimental system based on TI TMS320LF2407 DSK board has been set up and some experimental results demonstrate the effectiveness of the proposed four-axis motion control system and sensorless PMSM speed control system.
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Marapally, Prasanth. "Space Vector Controlled PMSM Drive Based on Fuzzy Logic Controller." Thesis, 2017. http://ethesis.nitrkl.ac.in/8943/1/2017_MT_MPrasanth.pdf.

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To improve the dynamic performances of Permanent Magnet Synchronous Motor (PMSM) drive, a novel implementation of speed controller based on adaptive fuzzy logic is presented in this project. Using the output of the fuzzy speed controller (FC), the quadrature axis current reference value can be obtained. The basic principle of vector control is to decouple the stator current to get direct axis and quadrature axis components. The vector control strategy is formulated in the synchronously rotating reference frame. The steady-state response of the predictive control can be effectively improved by using a simple time delay control approach. To increase the performances of PMSM drive, an adaptive speed controller based on fuzzy logic is proposed. The availability of the PMSM parameters is confirmed by computer simulations. The results of simulation have shown that the PMSM drive with the proposed control scheme has the merits of simple structure, robustness, quick tracking performance. In this project, the conventional PI speed controller has been replaced by the fuzzy controller. It combines the capability of fuzzy reasoning in handling uncertain information and the ability to compensate of the disturbance voltage observer on-line. The proposed control scheme has been testified by simulation, the results indicate the PMSM drive with the adaptive fuzzy controller will have the ability of quick recovery of the speed from any disturbances and parameters variation. Accordingly, the proposed PMSM drive will have better dynamic performances and robustness.
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Shi, Ming-Xin, and 史明鑫. "Research on Performance Improvement of Fault-Tolerant PMSM Drive Systems using Periodic Current Controller." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/872c7h.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>107<br>This thesis investigates periodic current controller design for a fault-tolerant permanent magnet synchronous motor drive system to improve its performance. When a power switch in the inverter is open- or short-circuited, or an encoder malfunction, the fault-tolerant function, including fault detection, fault diagnosis, fault isolation and fault control, is proposed to improve the reliability of the permanent magnet synchronous motor drive system. As a result, the system instantaneously executes fault-tolerant function to maintain its normal operation. To improve the current harmonics, two periodic current controllers including a classic periodic current controller and a select harmonics periodic current controller, are proposed. The proposed two controllers can reduce the total current harmonics of the drive system when compared to a PI controller. A digital signal processor, TMS320F2808, made by Texas Instruments, is used as a control center to execute the inverter fault, encoder fault, and periodic current control algorithms. Experimental results match the theoretical analysis to validate the correctness and feasibility of the proposed method.
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Liu, Ying-Tsen, and 劉映岑. "Intelligent Speed Controller with Optimal Bandwidth for IPMSM Drive System." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/9fr8pk.

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碩士<br>國立中央大學<br>電機工程學系<br>105<br>A novel maximum torque per ampere (MTPA) method based on power perturbation for a field-oriented control (FOC) interior permanent magnet synchronous motor (IPMSM) drive system is proposed in this study. The proposed MTPA method, which is parameter independent and can improve the motor operation at both start-up and low speed, is designed based on the power perturbation by using the signal injection in the current angle. Moreover, the influence of current and voltage harmonics to the MTPA control can be eliminated effectively. Furthermore, to enhance the robustness of the control system, an online tuning scheme for an integral-proportional (IP) controller using a new wavelet fuzzy neural network (WFNN) with disturbance torque feedforward control is developed where the disturbance torque is obtained from an improved disturbance torque observer also proposed in this study. In order to achieve an optimal bandwidth, a novel online auto-tuning technique also using the new wavelet fuzzy neural network (WFNN) for a field-oriented control (FOC) interior permanent magnet synchronous motor (IPMSM) servo drive is proposed in this study. Finally, some experimental results using an IPMSM drive system based on a low price digital signal processor (DSP) are presented. From the experimental results, the proposed control approach can guarantee the control performance of speed loop even under a cyclic fluctuating load.
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Tsai, Cheng-Hung, and 蔡政宏. "DESIGN AND IMPLEMENTATION OF AN INTELLIGENT CONTROLLER FOR INDUCTION MOTOR DRIVE." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/74236406462116285497.

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博士<br>大同大學<br>電機工程研究所<br>88<br>The design and implementation of the controller for induction motor are the main purpose of this dissertation. The scalar control, closed-loop direct torque control and the sensorless vector control are three researching cores. For the three parts, the grey system theory, fuzzy control theory and artificial neural network are employed to improve the performance of the induction motor. The tasks are listed as follows. (1) The applications of the scalar control method The task of this research is to analyze the GM(1,1) model. Based on this research, we can build up a proper GM(1,1) model for different type of data sequence. In the fuzzy control theory, we established the knowledge base of control rules from error and change error. Then, the inference engine used the base to calculate the output signal according to the actual error and the actual change error to obtain a better performance. (2) The applications of the closed-loop direct torque control strategy The basic idea of the direct torque control is through the calculation of the current and speed feedback. The rotor flux angle, flux magnitude and the torque will be obtained. These values will be compared with the command values by using hysteresis comparators to obtain an output voltage vector. But the selection rules are not unique. It will be the main factor that affects the performance. Therefore, the fuzzy control method is employed for this application. The torque and flux magnitude are chosen as the fuzzy variables. The output voltage vector is then decided by the position of the flux angle. In the same way, the grey system theory is also adopted to predict the state that used by the fuzzy controller. (3) The applications of the sensorless vector control In the sensorless vector control, the speed is estimated by the rotor estimator under the rotor flux field oriented control. The speed is calculated by the rotor flux. In the low speed range, the motor parameters will be changed by the thermal effect. The changes will result in the estimation of the rotor flux. Therefore, the artificial neural network is adopted. Then the trained artificial neural network is employed to replace the original rotor flux estimator. The better accuracy of the rotor flux value will be obtained. Then the speed will be more accurate. In another aspect, we propose a decoupling method for the sensorless vector control. The induction motor will behave like a dc motor for the purposes of fast responses. At last, the simulation results verify the proposed scheme. In the experimental results, the better results will be also obtained by the proposed method.
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Ridwan, Muhammad, and Muhammad Ridwan. "Design and Implementation of a Periodic Speed Controller and Current Estimator for a Fault-Tolerant PMSM Drive System." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/fd9hsc.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>107<br>This thesis proposes a periodic speed controller and a sliding-mode current estimator for fault-tolerant permanent magnet synchronous motor drive systems. The fault-tolerant conditions including one power switch open-circuit, one power switch short-circuit, or one Hall-effect current sensor fault. By using the speed-loop periodic controller, the drive system has better performance, including faster transient responses and better load disturbance responses than a speed-loop PI controller drive system. The detailed design of the periodic controller and the fault-tolerant drive system, including fault detection, diagnosis, and control are included. In addition, a sliding mode current estimator is investigated to estimate the stator current. The estimated current is used to replace the measured current when a Hall-effect current sensor is faulty. A 32-bit digital signal processor, type TMS-320F-2808, is used to execute the fault-tolerant algorithm and periodic control algorithm. Experimental results show the measured results can validate the correctness of the theoretical analysis.
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Xu, Fa, and 許烱發. "Integrated design of intelligent track seeking and following controller for hard disk drive servo." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/84045201461795619996.

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Book chapters on the topic "Intelligent controller PMSM drive"

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Jamwal, Paramjeet Singh, and Sanjeev Singh. "Speed Controller Optimization for PMSM Drive Using PSO Algorithm." In Advances in Intelligent Systems and Computing. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0448-3_83.

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Shiva, Badini Sai, and Vimlesh Verma. "MRAS Based Speed Sensorless Vector Controlled PMSM Drive." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30465-2_61.

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Yao, Yao, Dawei Gu, Yebing Cui, Shuwei Song, and Fanquan Zeng. "Design of the Bus Support Capacitor in Servo Drive Controller Based on PMSM." In Emerging Trends in Intelligent and Interactive Systems and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63784-2_60.

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Jaffar Sadiq Ali, A., and G. P. Ramesh. "Neural Network-Controlled Wind Generator-Fed Γ-Z Source-Based PMSM Drive." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3174-8_34.

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Ranjan, Shilpa, Monika Verma, Madhusudan Singh, and Mini Sreejeth. "Intelligent control for PMSM drive train." In Intelligent Control for Modern Transportation Systems. CRC Press, 2023. http://dx.doi.org/10.1201/9781003436089-3.

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Tian, Lisi, Yang Liu, and Jin Zhao. "Intelligent Model-Based Speed Controller Design for PMSM." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45049-9_70.

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Yu, Jinpeng, Peng Shi, and Jiapeng Liu. "Neural Networks-Based Adaptive DSC for PMSM." In Intelligent Backstepping Control for the Alternating-Current Drive Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67723-7_9.

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Yu, Jinpeng, Peng Shi, and Jiapeng Liu. "Adaptive Fuzzy Backstepping Position Tracking Control for PMSM." In Intelligent Backstepping Control for the Alternating-Current Drive Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67723-7_8.

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Yu, Jinpeng, Peng Shi, and Jiapeng Liu. "Fuzzy-Approximation-Based Adaptive Control of the Chaotic PMSM." In Intelligent Backstepping Control for the Alternating-Current Drive Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67723-7_12.

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Tom, Ashly Mary, and J. L. Febin Daya. "Vector Control of PMSM Drive in Electric Vehicles Using SVM Regression Approach." In Communication and Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2100-3_28.

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Conference papers on the topic "Intelligent controller PMSM drive"

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Shetty, Anup, Suryanarayana K, Anantha Saligram, and L. V. Prabhu. "Analysis of Sensorless PMSM Drive with Adaptive Controller Tuning." In 2024 IEEE North Karnataka Subsection Flagship International Conference (NKCon). IEEE, 2024. https://doi.org/10.1109/nkcon62728.2024.10774793.

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Buakaew, Sornchai, and Witthawas Pongyart. "Fault-Tolerant Controller Design for PMSM Drives with Single-Phase Fault Inverters." In 2025 Fourth International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP). IEEE, 2025. https://doi.org/10.1109/ica-symp63674.2025.10876518.

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Shi, Xuanzhou, Zhiqiang Ma, and Hanlin Dong. "Logarithmic Sliding-Mode Observer and Controller for Position Sensorless PMSM Drive." In 2024 IEEE 3rd Industrial Electronics Society Annual On-Line Conference (ONCON). IEEE, 2024. https://doi.org/10.1109/oncon62778.2024.10931251.

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Mastanaiah, Aenugu, and Tejavathu Ramesh. "Enhanced Direct Torque Control of Sensorless PMSM Drive with TD3 Agent-Based Speed Controller." In 2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET). IEEE, 2024. http://dx.doi.org/10.1109/sefet61574.2024.10718017.

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Enokura, Hiroshi, Yukinori Inoue, Shigeo Morimoto, et al. "Torque Control Characteristics of Simple Controller-Based Direct Torque Control for PMSM Drive System." In 2024 27th International Conference on Electrical Machines and Systems (ICEMS). IEEE, 2024. https://doi.org/10.23919/icems60997.2024.10921392.

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Nguyen, Anh Tuan, Thiem V. Pham, and Tran Le Nhat Hoang. "Speed Controller Design for Interior PMSM Drive Based on Model Reference Adaptive Control Strategy in EV Applications." In 2024 9th International Conference on Applying New Technology in Green Buildings (ATiGB). IEEE, 2024. http://dx.doi.org/10.1109/atigb63471.2024.10717761.

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Rayd, Hamza, Aziz El Janati El Idrissi, Noureddine Zahid, and Mohamed Jedra. "Robust emerged artificial intelligence speed controller for PMSM drive." In 2014 Second World Conference on Complex Systems (WCCS). IEEE, 2014. http://dx.doi.org/10.1109/icocs.2014.7060952.

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Ming Lu, Yingguang Wang, Yuewei Hu, Luhang Liu, and Nuo Su. "Composite controller design for PMSM direct drive SGCMG gimbal servo system." In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2017. http://dx.doi.org/10.1109/aim.2017.8014003.

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Marufuzzaman, Mohd, M. B. I. Reaz, and M. A. Mohd Ali. "FPGA implementation of an intelligent current dq PI controller for FOC PMSM drive." In 2010 International Conference on Computer Applications and Industrial Electronics (ICCAIE). IEEE, 2010. http://dx.doi.org/10.1109/iccaie.2010.5735005.

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Marufuzzaman, Mohd, M. B. I. Reaz, M. S. Rahman, and M. A. Mohd Ali. "Hardware prototyping of an intelligent current dq PI controller for FOC PMSM drive." In Computer Engineering (ICECE). IEEE, 2010. http://dx.doi.org/10.1109/icelce.2010.5700559.

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