Journal articles: '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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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.

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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.pp2643-2657.

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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.

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Oubelaid, Adel, Nabil Taib, Srete Nikolovski, et al. "Intelligent Speed Control and Performance Investigation of a Vector Controlled Electric Vehicle Considering Driving Cycles." Electronics 11, no. 13 (2022): 1925. http://dx.doi.org/10.3390/electronics11131925.

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In this paper, battery electric vehicle (BEV) controllers are smartly tuned with particle swarm optimization (PSO) and genetic algorithm (GA) to ensure good speed regulation. Intelligent tuning is ensured with a proposed and well-defined cost function that aims to satisfy the design requirements in terms of minimum overshoot, fast response, and tolerable steady state input. Two proposed cost functions are formulated for both simple speed input and for driving cycles. The BEV is controlled with the field oriented control technique (FOC), and it is driven by a permanent magnet synchronous motor (PMSM). An efficient control scheme based on FOC is built using a simplified closed loop control system including BEV components such as regulators, inverter, traction machine, and sensors. Simulation results show that the optimum controller gains obtained by intelligent tuning have resulted in satisfactory BEV performance that sustains the harsh environmental conditions. Robustness tests against BEV parameter changes and environmental parameter variations confirmed the effectiveness of intelligent tuning methods.

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Jaber, Fatimah. "PID CONTROLLER FOR SPEED CONTROL OF PMSM BASED ON MAYFLY OPTIMIZATION ALGORITHM." Kufa Journal of Engineering 16, no. 1 (2025): 104–20. https://doi.org/10.30572/2018/kje/160107.

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Permanent magnet synchronous motor (PMSM) is extensively employed in AC servo drives owing to their superior torque-to-inertia ratio, power density, efficiency, and power factor compared to other motors. So, it is a crucial point to regulate the PMSM speed. Conventional proportional, integral, and differential (PID) is a simple controller and easy to implement but it is coefficients are essentially determined by experience when used in PMSM to control the speed. This invariably produces unacceptable outcomes, in addition when it comes to low-power application drives, PID controller gains typically produce adequate results but, when it comes to high-power application drives, an untuned PID does not deliver satisfactory performance. The optimization algorithm offers an effective method to produce optimal PID gains. Therefore, to optimize the PID coefficients to regulate the PMSM speed, this study suggests a mayfly optimization algorithm (MA). Recently, the MA was introduced as a new intelligent optimization method with exceptional optimization capabilities. Nuptial dancing and random flight improve the ability of the algorithm to balance its features of exploitation and exploration while assisting in its escape from local optima. This suggested approach has been verified with MATLAB, and the outcomes are compared with the standard particle swarm optimization technique (PSO) and conventional PID. The outcomes show that compared to the standard PSO or conventional PID, the PID parameters adjusted by the MA method can produce faster speed responses and less overshoot. Furthermore, the system's optimal ITAE index value, as determined by the MA technique, is smaller (0.794) as compared to other techniques 1.503 and 1.906 respectively.

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Tran, Duc Chuyen, Van Hoa Roan, Dinh Co Hoang, et al. "Improving control quality of PMSM drive systems based on adaptive fuzzy sliding control method." International Journal of Power Electronics and Drive Systems (IJPEDS) 13, no. 2 (2022): 835–45. https://doi.org/10.11591/ijpeds.v13.i2.pp835-845.

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In this paper, a solution to improve the precision in speed control for permanent magnet synchronous motors (PMSM) based on fuzzy adaptive sliding mode controller (FASMC) is proposed. In order to tackle the nonlinear tracking problem, continuously switching topologies are embedded. The designed algorithm and the closed electric drive system stability is examined by employing corresponding Lyapunov candidate functions. The results are numerically simulated and experimentally verified in the environment of MATLAB-Simulink, control Desk with dSPACE 1104 card, proving the applicability of the control algorithm which not only works well in simulations but also in practice for possible industrial traction drive applications.

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Arafa, Osama M., Said A. Wahsh, Mohamed Badr, and Amir Yassin. "Grey wolf optimizer algorithm based real time implementation of PIDDTC and FDTC of PMSM." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 3 (2020): 1640. http://dx.doi.org/10.11591/ijpeds.v11.i3.pp1640-1652.

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Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.

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Osama, M. Arafa, A. Wahsh Said, Badr Mohamed, and Yassin Amir. "Grey wolf optimizer algorithm based real time implementation of PIDDTC and FDTC of PMSM." International Journal of Power Electronics and Drive System (IJPEDS) 11, no. 3 (2020): 1640–52. https://doi.org/10.11591/ijpeds.v11.i3.pp1640-1652.

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Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.

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Huang, Gang, Jiajun Li, Wei Huang, Yao Yang, and Kaihui Zhao. "Torque Control for Electric Drive System Used in Electric Vehicle in the Presence of Permanent Magnet Demagnetization Faults." Journal of Advanced Computational Intelligence and Intelligent Informatics 26, no. 2 (2022): 226–35. http://dx.doi.org/10.20965/jaciii.2022.p0226.

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The performance of conventional torque control for PMSM drive used in electric vehicles (EVs) from the viewpoint of permanent magnet (PM) demagnetization faults has not been satisfactory. Therefore, a combination method based on sliding-mode observer and active disturbance rejection control is presented. First, the model of the PMSM system with PM demagnetization faults is constructed. Then, a sliding-mode observer is designed based on a minimum extended flux linkage to estimate the torque and the PM flux linkages of the system. A current controller is presented based on active disturbance rejection control approach to reject the PM demagnetization faults. The method is useful to improve the control performance of the PMSM drive system. And the system is robust to system parameters variations. Finally, an RT-LAB real-time simulation is used to build a simulation model of hardware-in-the-loop based on the experimentally validated model that is derived from the actual development process for an electric bus. The simulation and experimental results demonstrate the effectiveness of the method.

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Tran, Duc Chuyen, and Duc Dien Nguyen. "Development of a position tracking drive system for controlling PMSM motor using dSPACE 1104-based variable structure." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 3 (2021): 1345–57. https://doi.org/10.11591/ijpeds.v12.i3.pp1345-1357.

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In industrial electric drive systems, it is common to find objects that need to solve the problem of angular position control, moving the object from one position to another asymptotically with no over-correction and guarantee. calculation of maximum fast impact. This is a multi-target optimization problem with many different solutions. This paper presents a method of constructing a PMSM motor position controller with a variable structure using dSPACE 1104 card. The system consists of a position control loop with a variable structure that is an outer loop and a speed control loop degree is the inner loop. In which, the speed adjustment loop uses adaptive law to compensate for uncertain functions and build a sliding mode observation to estimate load torque, friction and noise. The results of the simulation study were verified on Matlab-Simulink environment and experimented on dSPACE 1104 card to check the correctness of the built controller algorithm. The research results in the paper are the basis for the evaluation and setting up of control algorithms, design of electric drive systems in industry and the military.

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Ma, Chi, Baosheng Huang, Md Khairul Basher, Md Abdur Rob, and Yuqiang Jiang. "Fuzzy PID Control Design of Mining Electric Locomotive Based on Permanent Magnet Synchronous Motor." Electronics 13, no. 10 (2024): 1855. http://dx.doi.org/10.3390/electronics13101855.

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Achieving precise stopping of electric locomotives is crucial for the realization of intelligent and unmanned auxiliary transportation systems. Presently, human drivers play a central role in ensuring accurate stopping, presenting obstacles to automation and cargo location precision, especially within the coal mining sector. This article centers on achieving the precise stopping of electric locomotives under various conditions through the utilization of permanent magnet synchronous motor-driven locomotives. This approach introduces a novel stopping control method that integrates a fuzzy proportional–integral–derivative (F-PID) controller with a vector control model for permanent magnet synchronous motors (PMSM). Subsequently, we develop the F-PID controller using the PMSM technique, incorporating new fuzzy rules for each subsystem to enhance control accuracy and efficiency. Finally, extensive simulations and real-world experiments are conducted on an electric locomotive stopping test bed to validate the effectiveness of the proposed control method. The results show that the method consistently achieves precise stopping under diverse working conditions, with an error of less than 0.3 m, confirming its robustness and reliability.

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Agarwal, Ritik, Ghanishtha Bhatti, R. Raja Singh, et al. "Intelligent Fault Detection in Hall-Effect Rotary Encoders for Industry 4.0 Applications." Electronics 11, no. 21 (2022): 3633. http://dx.doi.org/10.3390/electronics11213633.

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Sensors are the foundational components of any smart machine system and are invaluable in all modern technologies. Consequently, faults and errors in sensors can have a significant negative impact on the setup. Intelligent, lightweight, and accurate fault diagnosis and mitigation lie at the crux of modern industries. This study aimed to conceptualize a germane solution in the domain of fault detection, focusing on Hall-effect rotary encoders. Position monitoring through rotary encoders is essential to the safety and seamless functioning of industrial equipment such as lifts and hoists, and commercial systems such as automobiles. This work used multi-strategy learners to accurately diagnose quadrature and offset faults in Hall-effect rotary encoders. The obtained dataset was then run through a lightweight ensemble classifier to train a robust fault detection model. The complete mechanism was simulated through interconnected models simulated in a MATLAB Simulink™ environment. In real time, the developed fault detection algorithm was embedded in an FPGA controller and tested with a 1 kW PMSM drive system. The resulting system is computationally inexpensive and achieves an accuracy of 95.8%, making it a feasible solution for industrial implementation.

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Lakshmipriya, N., N. P. Ananthamoorthy, S. Ayyappan, and P. Hema. "An intelligent fuzzy PI controller based 33 level switched capacitor multilevel inverter for PMSM drives." Materials Today: Proceedings 45 (2021): 2861–66. http://dx.doi.org/10.1016/j.matpr.2020.11.811.

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Flah, Aymen, and Lassaâd Sbita. "A novel IMC controller based on bacterial foraging optimization algorithm applied to a high speed range PMSM drive." Applied Intelligence 38, no. 1 (2012): 114–29. http://dx.doi.org/10.1007/s10489-012-0361-0.

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Gembalczyk, Grzegorz, Slawomir Duda, Eugeniusz Switonski, and Arkadiusz Mezyk. "Fuzzy controller for the treadmill speed adaptation system in mechatronic device for gait reeducation." Journal of Intelligent & Fuzzy Systems 39, no. 5 (2020): 7757–67. http://dx.doi.org/10.3233/jifs-201111.

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Training with use of mechatronic devices is an innovative rehabilitation method for patients with various locomotor dysfunction. High efficiency of training is noted in systems that combine a treadmill or orthosis with a body weight support system. Speed control is a limitation of such rehabilitation systems. In commercially available devices, the treadmill speed is constant or set by the therapist. Even better training results should be obtained for devices in which the speed of the treadmill will be automatically adjusted to the patient walking pace. This study presents a mechatronic device for locomotor training that uses an algorithm to adjust the speed of the treadmill. This speed is controlled with use of a sensor that measures the rope inclination. The end of rope is fastened to the orthopaedic harness. Speed control is realized in such a way that ensures the smallest possible swing angle of the rope. A fuzzy controller was applied to adjust the treadmill speed. The drive system of the treadmill is equipped in a servodrive with PMSM motor and energy recovery module, which allows smooth speed control, limiting acceleration and minimizing electricity consumption. The presented solution was implemented in a real object and subjected to experimental tests.

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Sain, Chiranjit. "Performance Optimization for Closed Loop Control Strategies towards Simplified Model of a PMSM Drive by Comparing with Different Classical and Fuzzy Intelligent Controllers." International Journal of Automation and Control 14, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijaac.2020.10020855.

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Sain, Chiranjit, Atanu Banerjee, Pabitra Kumar Biswas, and Valentina Emilia Balas. "Performance optimisation for closed loop control strategies towards simplified model of a PMSM drive by comparing with different classical and fuzzy intelligent controllers." International Journal of Automation and Control 14, no. 4 (2020): 469. http://dx.doi.org/10.1504/ijaac.2020.108281.

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Parvathy, Thampi Mooloor Sahridayan, and Gopal Raghavendra. "Modeling and analysis of field-oriented control based permanent magnet synchronous motor drive system using fuzzy logic controller with speed response improvement." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6010–21. https://doi.org/10.11591/ijece.v12i6.pp6010-6021.

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The permanent magnet synchronous motor (PMSM) acts as an electrical motor mainly used in many diverse applications. The controlling of the PMSM drive is necessary due to frequent usage in various systems. The conventional proportional-integral-derivative (PID) controller’s drawbacks are overcome with fuzzy logic controller (FLC) and adopted in the PMSM drive system. In this manuscript, an efficient field-oriented control (FOC) based PMSM drive system using a fuzzy logic controller (FLC) is modeled to improve the speed and torque response of the PMSM. The PMSM drive system is modeled using abc to αβ and αβ to abc transformation, 2-level space vector pulse width modulation (SVPWM), AC to DC rectifier with an inverter, followed by PMSM drive, proportional integral (PI) controller along with FLC. The FLC’s improved fuzzy rule set is adopted to provide faster speed response, less % overshoot time, and minimal steady-state error of the PMSM drive system. The simulation results of speed response, torque response, speed error, and phase currents are analyzed. The FLC-based PMSM drive is compared with the conventional PID-based PMSM drive system with better improvements in performance metrics.

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Mooloor Sahridayan, Parvathy Thampi, and Raghavendra Gopal. "Modeling and analysis of field-oriented control based permanent magnet synchronous motor drive system using fuzzy logic controller with speed response improvement." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6010. http://dx.doi.org/10.11591/ijece.v12i6.pp6010-6021.

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The permanent magnet synchronous motor (PMSM) acts as an electrical motor mainly used in many diverse applications. The controlling of the PMSM drive is necessary due to frequent usage in various systems. The conventional proportional-integral-derivative (PID) controller’s drawbacks are overcome with fuzzy logic controller (FLC) and adopted in the PMSM drive system. In this manuscript, an efficient field-oriented control (FOC) based PMSM drive system using a fuzzy logic controller (FLC) is modeled to improve the speed and torque response of the PMSM. The PMSM drive system is modeled using abc to αβ and αβ to abc transformation, 2-level space vector pulse width modulation (SVPWM), AC to DC rectifier with an inverter, followed by PMSM drive, <a name="_Hlk107566912"></a>proportional integral (PI) controller along with FLC. The FLC’s improved fuzzy rule set is adopted to provide faster speed response, less % overshoot time, and minimal steady-state error of the PMSM drive system. The simulation results of speed response, torque response, speed error, and phase currents are analyzed. The FLC-based PMSM drive is compared with the conventional PID-based PMSM drive system with better improvements in performance metrics.

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Wang, Wanli, Han Pang, Xincheng Li, Yipeng Wu, and Xiufu Song. "Research on speed control of permanent magnet synchronous motor based on RBF neural network tuning PID." Journal of Physics: Conference Series 2264, no. 1 (2022): 012018. http://dx.doi.org/10.1088/1742-6596/2264/1/012018.

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Abstract In order to solve the problem of insufficient speed regulation performance of conventional PID controller in multi gear switching of electric drive fracturing PMSM, RBF neural network parameter identification is used to set the PID parameters and improve the control effect of conventional PID controller. By analyzing the application characteristics of PMSM in electric drive fracturing truck, the RBF-PID controller and the speed control system model of PMSM are established based on s-function in MATLAB/SIMLINK, and the simulation research is carried out in combination with the application requirements. The results show that compared with the conventional PID controller, the RBF-PID controller has better real-time performance and robustness. The real-time response characteristics of the PMSM speed regulation control system are improved by 84% and the robustness is improved by 62%. The RBF-PID controller can effectively improve the working stability of PMSM.

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Zhu, Jun, Wan Kui Li, Hai Xing Wang, and Li Li Han. "The Hardware System Design of PMSM Controller Based on DSP2812." Applied Mechanics and Materials 273 (January 2013): 454–59. http://dx.doi.org/10.4028/www.scientific.net/amm.273.454.

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For the efficiency of PMSM, in the paper the matched controller was developed to improve the servo performance of permanent magnet synchronous servo system. According to the basic principle of vector control for PMSM, the hardware system of PMSM controller was constituted based on TMS320F2812, it contains power drive circuit, control circuit, feedback circuit and other auxiliary circuits. It can provide reference scheme for the design of PMSM controller, and laid the foundation for the industrial production of the PMSM controller.

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Lin, Chih Hong, and Chih Peng Lin. "The Hybrid RNN Control for a PMSM Drive Electric Scooter Using Rotor Flux Estimator." Applied Mechanics and Materials 145 (December 2011): 542–46. http://dx.doi.org/10.4028/www.scientific.net/amm.145.542.

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The hybrid recurrent neural network (HRNN) control for a permanent magnet synchronous motor (PMSM) drive electric scooter using rotor flux estimator was implemented in this paper. Firstly the dynamic models of a PMSM drive system were implemented. Then, a HRNN control control system using rotor flux estimator is developed to control PMSM drive system in order to drive electric scooter. The rotor flux estimator consists of the estimation algorithm of rotor flux position and speed based on the back electromagnetic force (EMF). Moreover, the HRNN controller consists of the RNN and compensated controller with variable structure control (VSC) is applied to PMSM drive system using rotor flux estimator. Finally, the effectiveness of the proposed control schemes is demonstrated by experimental results.

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Aguilar-Mejía, Omar, Hertwin Minor-Popocatl, Prudencio Fidel Pacheco-García, and Ruben Tapia-Olvera. "Neuroadaptive Robust Speed Control for PMSM Servo Drives with Rotor Failure." Applied Sciences 11, no. 23 (2021): 11090. http://dx.doi.org/10.3390/app112311090.

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In this paper, a neuroadaptive robust trajectory tracking controller is utilized to reduce speed ripples of permanent magnet synchronous machine (PMSM) servo drive under the presence of a fracture or fissure in the rotor and external disturbances. The dynamics equations of PMSM servo drive with the presence of a fracture and unknown frictions are described in detail. Due to inherent nonlinearities in PMSM dynamic model, in addition to internal and external disturbances; a traditional PI controller with fixed parameters cannot correctly regulate the PMSM performance under these scenarios. Hence, a neuroadaptive robust controller (NRC) based on a category of on-line trained artificial neural network is used for this purpose to enhance the robustness and adaptive abilities of traditional PI controller. In this paper, the moth-flame optimization algorithm provides the optimal weight parameters of NRC and three PI controllers (off-line) for a PMSM servo drive. The performance of the NRC is evaluated in the presence of a fracture, unknown frictions, and load disturbances, likewise the result outcomes are contrasted with a traditional optimized PID controller and an optimal linear state feedback method.

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Wang, Song. "ADRC and Feedforward Hybrid Control System of PMSM." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/180179.

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The permanent-magnet synchronous motor (PMSM) is a complex controlled object that is difficult to drive and control. In this study, the vector control strategy is adopted to drive the PMSM. The active disturbance rejection controller is used to achieve the closed-loop control of PMSM, which simplifies the computational complexity. A load torque observer and feedforward compensation component are designed to overcome the PMSM speed fluctuation of the load disturbance. An experimental system based on the DSP board is designed to test the controller performance. The results validate the control algorithm.

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Lin, Chih-Hong, and Chih-Peng Lin. "The Hybrid RFNN Control for a PMSM Drive Electric Scooter Using Rotor Flux Estimator." Advances in Fuzzy Systems 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/319828.

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The hybrid recurrent fuzzy neural network (HRFNN) control for permanent magnet synchronous motor (PMSM) drive system using rotor flux estimator is developed to control electric scooter in this paper. First, the dynamic models of a PMSM drive system were derived in according to electric scooter. Owing to the load of electric scooter exited many uncertainties, for example, nonlinear friction force of the transmission belt, and so forth. The electric scooter with nonlinear uncertainties made the PI controller to disable speed tracking control. Moreover, in order to reduce interference of encoder and cost down, an HRFNN control system using rotor flux estimator was developed to control PMSM drive system in order to drive electric scooter. The rotor flux estimator consists of the estimation algorithm of rotor flux position and speed based on the back electromagnetic force (EMF) in order to supply with HRFNN controller. The HRFNN controller consists of the supervisor control, RFNN, and compensated control with adaptive law is applied to PMSM drive system. The parameters of RFNN are trained according to different speeds in electric scooter. The electric scooter is operated to provide disturbance torque. To show the effectiveness of the proposed controller, comparative studies with PI controller are demonstrated by experimental results.

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Xu, Peng, Jian Xiao, Shan Li, and Yi Yang. "Human Simulated Intelligent Control for Permanent Magnet Synchronous Motor." Applied Mechanics and Materials 241-244 (December 2012): 1821–27. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.1821.

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This paper proposes a new speed control scheme for a Permanent Magnet Synchronous Motor(PMSM) by means of multi-mode control method,Human Simulate Intelligent Control. Similar to hierarchical intelligent control system,the proposed controller for PMSM is composed of three sections,Task Adapter Level (TA), Self-Tuning Level (ST) and Master Controller Level (MC).Simulation results clearly show that the controller guarantees the speed tracking errors asymptotically converge to zero despite time varying reference speed and load torque disturbance variation.Numerical simulations reveal the superiority of the proposed controller to traditional PI.

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Ji, H., and Zhi Yong Li. "Study on Intelligent Controller of Permanent Magnet Synchronous Motor." Advanced Materials Research 764 (September 2013): 149–53. http://dx.doi.org/10.4028/www.scientific.net/amr.764.149.

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This paper puts forward a novel design method of controller based on BP neural network, which is applied to the permanent magnet synchronous motor (PMSM) double closed loop speed regulation system of speed regulator, by using the neural network controller instead of traditional PID controller. It applies the nonlinear adaptive ability of neural network for optimizing the control parameters of PID controller for PMSM. The simulation model was established in Matlab/Simulink. The simulation results indicate that the neutral network PID controller, compared with the traditional PID, has strong robustness and adaptive ability to the model and environments, indicating the good dynamic and static characteristics and control effects.

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Quynh, Nguyen Vu. "Using radial basis function neural network for PMSM to overcome the changing load." Vietnam Journal of Science and Technology 59, no. 2 (2021): 234–48. http://dx.doi.org/10.15625/2525-2518/59/2/14921.

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This paper presents a using Radial Basis Function Neural Network (RBFNN) for PMSM to overcome the changing load. Firstly, a mathematic model of the PMSM drive is derived; then, to increase the performance of the PMSM drive system, a Fuzzy PI controller in which an RBFNN adjusts its parameters is applied to the speed controller for coping with the effect of the system dynamic uncertainty and the external load. Secondly, the Very high-speed integrated circuit Hardware Description Language (VHDL) is adopted to describe the behaviour of the speed control IC which includes the circuits of space vector pulse width modulation (SVPWM), coordinate transformation, RBFNN, and Fuzzy PI. Thirdly, the simulation work is performed by MATLAB/Simulink and ModelSim co-simulation mode, provided by Electronic Design Automation (EDA) Simulator Link. The PMSM, inverter, and speed command are performed in Simulink, and the speed controller of the PMSM drive is executed in ModelSim. Finally, the co-simulation results validate the effectiveness of the proposed algorithm based speed control system

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Zhang, X. Z., and Y. N. Wang. "Fuzzy variable structure control based on a Takagi-Sugeno model for permanent-magnet synchronous motors." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 223, no. 6 (2009): 773–83. http://dx.doi.org/10.1243/09596518jsce702.

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A fuzzy variable structure control (FVSC) scheme based on a Takagi-Sugeno (T-S) model is proposed in this paper for a permanent-magnet synchronous motor (PMSM) drive system in order to solve the speed tracking problem. A T-S fuzzy model is first formed to represent the non-linear system of the PMSM. To convert the tracking control into a stabilization problem, a new control design is proposed to define the internal desired states. Then, an FVSC controller for the PMSM system with parameter variation and load disturbances is designed on the basis of this fuzzy model. The FVSC scheme can drive the dynamics of the PMSM into a designated sliding surface in finite time, and guarantee the property of asymptotical stability. It is also shown that information on the upper bound of modelling errors, as well as on perturbations, is not required when using the FVSC controller. The performance of the proposed controller is verified by simulation and experimental results on a PMSM system.

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Yerri Veeresh, M., V. N. Bhaskar Reddy, and R. Kiranmayi. "Modeling and Analysis of Time Response Parameters of a PMSM-Based Electric Vehicle with PI and PID Controllers." Engineering, Technology & Applied Science Research 12, no. 6 (2022): 9737–41. http://dx.doi.org/10.48084/etasr.5321.

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This paper presents the mathematical modeling of a vector-controlled Permanent Magnet Synchronous Motor (PMSM) drive with either a Proportional Integral (PI) controller or a Proportional Integral Derivative (PID) controller as a propulsion system for an Electric Vehicle (EV). Most commercial drives use a standard PI controller as a speed regulator. The vector control system model consists of the PMSM, a PWM inverter, the speed controller, and vehicle dynamics for speed control. The performance analysis of the drive is evaluated under transient conditions for settling time, rise time, steady state error of speed, and the vehicle’s acceleration at the wheel axle for specifically designated values validated by MATLAB/Simulink.

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Ravikumar, N. V. A., Vasupalli Manoj, and Narendra Kumar Yegireddy. "Speed Control of 6-Phase PMSM using Fuzzy Controllers." E3S Web of Conferences 540 (2024): 02012. http://dx.doi.org/10.1051/e3sconf/202454002012.

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the article introduces a method for controlling the speed of a six-phase permanent magnet synchronous motor (PMSM) drive with the help of fuzzy logic controllers (FLCs). By utilizing the vector control technique, the fuzzy logic controller achieves a high level of dynamic performance. The FLC is implemented in the current and speed controllers of the six-phase PMSM drive. To evaluate its effectiveness under different operating conditions, the FLC with PMSM drives is designed and simulated using MATLAB. The FLC proves to be more robust and capable of overcoming the nonlinearity issues associated with the six-phase PMSM. The simulation outcomes confirm the efficiency of the suggested control technique for the PMSM drive system.

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Yadav, Deepti, and Dr Arunima Verma. "Performance Analysis of Permanent Magnet Synchronous Motor Drive using Particle Swarm Optimization Technique." Journal of Energy Technology Research 1, no. 2 (2017): 19. http://dx.doi.org/10.22496/jetr.v1i2.90.

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Permanent magnet synchronous motor (PMSM), a nonlinear speed controller design based on Particle Swarm Optimization (PSO) technique is presented in this paper. For tuning the PID controller, the speed control for PMSM was analyzed using PSO algorithm to optimize the parameters in terms of proportional gain (Kp), integral gain (Ki), and derivative gain (Kd). Moreover, the overall system is evaluated under various operating conditions such as starting, braking, load application and load removal. Besides this, comparison between speed control of PMSM using Ziegler-Nichols (Z-N) method and speed control of PMSM with PSO technique has been carried out. These analyses are estimated in terms of dynamic and static response. The transient response are examined in terms of settling time (ts), rise time (tr), peak time (tp), and peak overshoot (Mp). Overall, PID speed controller with PSO technique shows that the proposed method has improved the performance under the various operating conditions.

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Pilla, Ramana, Santukumari Killari, and K. B. Madhu Sahu. "Design and Simulation of the Control System for Inverter-fed Permanent Magnet Synchronous Motor Drive." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 3 (2018): 958. http://dx.doi.org/10.11591/ijeecs.v12.i3.pp958-967.

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Development in the field of power electronics, cost effective DSP’s and microprocessors have opened a new era in the design and implement modern control strategies for variable speed drives. This paper presents the design of a control system which includes a non-linear controller and observer for inverter fed Permanent Magnet Synchronous Motor (PMSM) Drive. The entire design is carried out by designing of Speed Controller, Non-linear controller (NLC), State feedback controller (SFC), H∞ controller as well as Non-linear full order observer (NFO). The proposed control scheme is extensively simulated under various conditions using MATLAB/Simulink, which shows better performance under all operating conditions for variable speed PMSM drive.

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42

Mohd Zaihidee, Fardila, Marizan Mubin, Hang Seng Che, and Tang Jing Rui. "Development of Closed-Loop Permanent Magnet Synchronous Motor Drive System Prototype." Jurnal Kejuruteraan si5, no. 2 (2022): 79–90. http://dx.doi.org/10.17576/jkukm-2022-si5(2)-09.

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Permanent magnet synchronous motors (PMSM) are widely used in low to mid-power applications and high-performance drives. They are preferred over brush-type motors and gradually replacing induction motors in various fields of application due to its advantages. Many researchers are proposing new control methods of PMSM drive system. However, the PMSM system is nonlinear and consists of time-varying parameters with high-order complex dynamics. Due to these factors, researchers cannot rely only on simulation results to prove superiority of their proposed controllers. To validate the results obtained by simulation, experimental validation is necessary, where a closed-loop PMSM drive system prototype has to be developed. This paper describes the development of a PMSM drive system prototype with closed-loop current, speed and position feedback using dSpace DS1104 controller board for a 1.93kW three-phase interior-mounted permanent magnet synchronous motor used for experimental validation of a proposed modified fractional order sliding mode speed controller. Using this prototype, the performance of any newly proposed control methods in real applications can be verified. Appropriate signal acquisition procedures of the feedback signals, as described in this work, are crucial to ensure the accuracy of closed-loop performance of the developed drive system.

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43

Cheng, Stone, and Chi-Wei Li. "Fuzzy PDFF-IIR controller for PMSM drive systems." Control Engineering Practice 19, no. 8 (2011): 828–35. http://dx.doi.org/10.1016/j.conengprac.2011.04.011.

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Marufuzzaman, Mohammad, Mamun Bin Ibne Reaz, Labonnah Farzana Rahman, and Tae Gyu Chang. "High-Speed CurrentdqPI Controller for Vector Controlled PMSM Drive." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/709635.

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High-speed current controller for vector controlled permanent magnet synchronous motor (PMSM) is presented. The controller is developed based on modular design for faster calculation and uses fixed-point proportional-integral (PI) method for improved accuracy. Currentdqcontroller is usually implemented in digital signal processor (DSP) based computer. However, DSP based solutions are reaching their physical limits, which are few microseconds. Besides, digital solutions suffer from high implementation cost. In this research, the overall controller is realizing in field programmable gate array (FPGA). FPGA implementation of the overall controlling algorithm will certainly trim down the execution time significantly to guarantee the steadiness of the motor. Agilent 16821A Logic Analyzer is employed to validate the result of the implemented design in FPGA. Experimental results indicate that the proposed currentdqPI controller needs only 50 ns of execution time in 40 MHz clock, which is the lowest computational cycle for the era.

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Yadav, Deepti, and Arunima Verma. "Comperative Performance Analysis of PMSM Drive Using MPSO and ACO Techniques." International Journal of Power Electronics and Drive Systems (IJPEDS) 9, no. 4 (2018): 1510. http://dx.doi.org/10.11591/ijpeds.v9.i4.pp1510-1522.

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This work proposes an optimization algorithm to control speed of a permanent magnet synchronous motor (PMSM) during starting and speed reversal of motor, as well as during load disturbance conditions. The objective is to minimize the integral absolute control error of the PMSM shaft speed to achieve fast and accurate speed response under load disturbance and speed reversal conditions. The maximum overshoot, peak time, settling time and rise time of the motor is also minimized to obtain efficient transient speed response. Optimum speed control of PMSM is obtained with the aid of a PID speed controller. Modified Particle Swarm Optimization (MPSO) and Ant Colony Optimization (ACO) techniques has been employed for tuning of the PID speed controller, to determine its gain coefficients (proportional, integral and derivative). Simulation results demonstrate that with use of MPSO and ACO techniques improved control performance of PMSM can be achieved in comparison to the classical Ziegler-Nichols (Z-N) method of PID tuning.

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Huang, Xiaochao, Gang Sun, Bi Wang, et al. "Fuzzy PID control based on variable universe for PMSM." Journal of Physics: Conference Series 2902, no. 1 (2024): 012053. https://doi.org/10.1088/1742-6596/2902/1/012053.

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Abstract This paper aims to design a speed controller for PMSM so that the motor can track the given speed signal. Based on vector control strategy, united with SVPWM (Space Vector Pulse Width Modulation) technology, an on-off of inverter switches was regularly controlled to form the vector voltage to drive PMSM. Finally, the PMSM double closed-loop vector control system was built. Specifically, by the design of the speed controller method, a fuzzy PID control, according to the variable universe, was proposed to realize the high precision control requirements of the PMSM speed control system. Firstly, on the ground of the traditional PID controller, a fuzzy controller was introduced to realize the self-tuning of control parameters, and then a new function variable domain module was built to reach the self-adjustment of the fuzzy controller domain and to achieve self-tuning of control rules, improving control accuracy and response speed.

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Lian, Yunxiao, Yong Zhou, Jianxin Zhang, Shangjun Ma, and Shuai Wu. "An Intelligent Nonlinear Control Method for the Multistage Electromechanical Servo System." Applied Sciences 12, no. 10 (2022): 5053. http://dx.doi.org/10.3390/app12105053.

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In order to meet the requirements of servo systems, including sensitive and rapid adjustment, high control and motion accuracy, and strong working adaptability, in special application fields, such as high thrust and long travel, an adaptive inversion control method is proposed for the lateral force and other nonlinear factors of multistage electromechanical servo system (MEMSS). The position tracking controller of permanent magnet synchronous motor (PMSM), based on an improved adaptive inversion method, was designed and its stability was analyzed, and the Luenberger load torque observer model of PMSM was established. The EMESS simulation model of an adaptive inversion controller was built using the Simulink platform, and the motor multibody dynamics model was established in ADAMS software. Through the joint simulation of Simulink and ADAMS software, the results of EMESS under adaptive inversion controller and traditional PID controller were compared, and the feasibility and reliability of the designed adaptive inversion controller were verified. Finally, the designed controller was tested based on the experimental platform. The experimental results show that the adaptive inversion controller designed in this paper has better robustness and stability than the traditional PID controller.

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Vo, Thanh Ha, and Thi Giang Pham. "A study on PMSM drive systems fed by multi-level inverter using linear quadratic regulator control for electric vehicle applications." TELKOMNIKA 21, no. 04 (2023): 917–25. https://doi.org/10.12928/telkomnika.v21i4.24432.

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This paper presents research on a permanent magnet synchronous motor (PMSM) by a 5-level T-type inverter using linear quadratic regulator (LQR) control for speed control. The space vector modulation (SVM) structure for the 5-level T-type inverter to improve the control quality of the PMSM drive system is presented. This paper aims to successfully design a state feedback controller to control motor speed in a permanent magnet synchronous motor drive system. Simulink results are performed with different speed ranges and the same torque load. These results will focus on evaluating quality when the PMSM drive operates at all speeds. MATLAB/Simulink proves the results.

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Li, Yan, and Zheng Yin Sheng. "Adaptive Backstepping Control for PMSM Integrated Starter Generator." Applied Mechanics and Materials 392 (September 2013): 425–30. http://dx.doi.org/10.4028/www.scientific.net/amm.392.425.

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In this paper a speed tracking controller is designed for Permanent Magnet Synchronous Motor (PMSM) integrated starter generator (ISG) operation in the starter based on adaptive backstepping technique. The PMSM drive system is often faced with some parameter variations and unknown disturbances. The designed controller can make the internal combustion engine (ICE) reach ignition speed quickly and meet the torque small pulsating and speed goes smoothly requirements. Then establish the controller model and simulate the ISG operation in the starter. Some simulation results verify the feasibility and illustrate the performance of the controller under the various conditions.

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Shi, Hong Mei, and Zu Jun Yu. "Design of PMSM Position Servo System Based on Fuzzy Adaptive PI Control." Advanced Materials Research 706-708 (June 2013): 737–41. http://dx.doi.org/10.4028/www.scientific.net/amr.706-708.737.

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A fuzzy adaptive PI controller for permanent magnet synchronous motor (PMSM) position servo system is proposed in this paper. Based on the analysis of PMSM mathematical model, the design of position loop controller is introduced in detail. To verify the effectiveness and accuracy of the fuzzy PI adaptive controller, an experimental system is designed using TMS320F2812 floating-point digital signal processor (DSP) as controller CPU and DR20A as integrated power drive module. The experimental results show that the designed AC position servo system has strong robustness, better speed performance and higher position precision, which can meet the requirements of high performance servo system.

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Journal articles on the topic 'Intelligent controller PMSM drive'

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