Modified Model Reference Adaptive Sensorless Control of PMSM Driven LEV with Online Self-Tuning Speed Controller

For permanent magnet synchronous motor speed and rotor position easily affected by the mechanical sensor signal transmission precision, to improve the performance of permanent magnet synchronous motor drive, the speed control system satisfies the requirement of fast response, and the complicated condition of frequent load disturbance has stronger resistance, this paper designed a small nerve network optimization of permanent magnet synchronous motor intelligent control system. The intelligent control system will be small neural networks applied to the model reference adaptive control of permanent magnet synchronous motor speed control system. On this basis, the structures, permanent magnet synchronous motor control system simulation, the simulation results show the system can accurately measure the rotational speed, rotor position and compared with the traditional model reference adaptive control, motor start-up speed no overshoot, has the stronger ability to resist load disturbance and load disturbance after speed restore faster (6 ms), in the motor control has strong practical application value.

This paper consists of modelling of PM synchronous motor drives (PMSM) with PI controller Fuzzy based Controller. PMSM has hysteresis controller which is used to estimate the speed and current controller errors. The common PI controller is used in industry reason that the ruggedness this regulator acquires. Controlling torque and flux is important in electrical drives due to that problem DTC method is used to control flux and torque estimated errors and fed to the power electronic converters. A PI and fuzzy controllers are used as a speed controller whose input is used as a speed controller whose input is the error between the speed command and feedback speed. Conventional DTC techniques are best compared to field oriented control (FOC) and basic block diagram of fuzzy based controller and PI controllers are presented.

The rising demand for high-performance permanent magnet synchronous motors (PMSMs) is responsible for the development of PMSM speed control. Although the proportional-integral controller is often used in field-oriented control (FOC) for motor speed regulation, it has drawbacks like slow response and instability. This paper proposed an enhanced sliding mode controller with a modified sliding surface to achieve better speed control performance. In comparison to proportional-integral or PI controller, fuzzy logic controller, conventional sliding mode controller, the proposed control approach uses a reaching law that incorporates a fuzzy logic controller. A smoother and faster response time is targeted by the proposed approach compared to conventional sliding mode control. Practical small-scale PMSM experiments certify the effectiveness of our proposed enhanced sliding mode control.

To enhance the dynamic performance and disturbance rejection capability of the permanent magnet synchronous motor speed control system, a novel speed control method based on a novel sliding mode control (NSMC) and load torque observer is proposed on the basis of model predictive current control (MPCC) with a sliding mode disturbance observer. First, on the basis of MPCC, the influence of parameters such as resistance, inductance, and flux linkage on MPCC is analyzed. To address the aggregated disturbance caused by parameter mismatches, a piecewise square-root switching function sliding mode disturbance observer (SMDO) is designed to enhance the robustness of the parameters. To address the poor dynamic performance and inadequate robustness resulting from the proportional-integral-controller (PI) velocity loop control in the MPCC, a novel NSMC velocity control method is proposed. This method utilizes the hyperbolic sine function and fractional-order integral sliding mode surface, resolving the dilemma faced by traditional slide mode controllers (SMC) in balancing fast response and reduced vibration. Additionally, to enhance the system’s disturbance rejection capability, a sliding mode torque observer (SMTO) is designed to continuously update the observed load torque value into the NSMC controller, achieving speed compensation control. Finally, through comparative experiments among the proportional integral controller (PI), SMC, NSMC, and NSMC + SMTO, the results indicate that the proposed NSMC + SMTO exhibits the best speed response, steady-state characteristics, and disturbance rejection capability.

This paper deals with the parameters of Permanent Magnet Synchronous Motor (PMSM) i.e. speed (&#x03C9;<inf>r</inf>), and q-axis inductance (L<inf>q</inf>) is to be estimated by using Reactive power based Model Reference adaptive Controller (MRAC). To improve the performance of speed sensor less permanent magnet synchronous motor drives, especially at low speeds by identifying stator resistance together with speed. Several speed estimation methods for sensor less PMSM drives have been proposed but the Performance is not satisfactory at low speed. Model-based speed and stator resistance estimators are the most common schemes used in the literature. The proposed technique is completely Independent of stator resistance (R<inf>s</inf>) and is less parameter sensitive, as the estimation-algorithm is only dependent on q-axis stator inductance (L<inf>q</inf>). Also, the method requires less computational effort as the simplified expressions are used in the MRAS. In this proposed scheme sensor less technique is used. The vector control technique is also used for the control the PMSM position and speed sensor. MATLAB/ simulink based simulation is discussed.

Permanent magnet synchronous motor (PMSM) servo system requires a high dynamic performance of speed. The control object of speed loop, which can be described using a two-order transfer function, is the PMSM regulated by current loop. PI controller is generally used in speed control, in which the performance improvement is limited by the strong coupling and nonlinearity of the system. In this paper, an adaptive model following speed controller (AMFC) with state feedback control and model following methods is designed based on the Popov hyperstability theory and modeled in the MATLAB. The simulation results show that, compared with PI control, AMFC raises the speed loop dynamic performance of PMSM by compensating the influence of coupling and nonlinearity, so it is more suitable for servo system.

High performance operation of a sensorless Permanent magnet synchronous motor (PMSM) drive demands accurate tuning of controller and observer parameters. This paper presents an Extended Kalman filter (EKF) based sensorless PMSM drive, wherein the dynamic performance of the closed loop controlled drive is enhanced from the dual perspective of the controller and the observer. To this effect, a modification of the speed controller is proposed to reduce the overshoot in speed which is otherwise present while using a conventional PI controller. The performance of the EKF observer is improved by a simple adaptive tuning, which effects fast dynamic response in speed estimation while providing better noise rejection in the steady state operation of the drive. The proposed techniques are validated using simulation and experiment, and results are presented for a Voltage Source Inverter fed 1.5 kW sensorless PMSM drive.

The three-link robotic manipulator plays an important role in industrial automation, where productivity and efficiency are directly related to precise motion control. However, its dynamics are highly nonlinear and strongly coupled, making the control problem challenging. In this work, a novel decoupling technique is introduced, where each joint acceleration is modeled as being primarily influenced by its own torque and velocity, while the remaining coupling dynamics are considered as uncertainties. Following this approach, simplified decoupled state-space equations are derived for all three links. A conventional Model Reference Adaptive Controller (MRAC) is then designed to track the desired reference model. While effective under ideal conditions, the conventional MRAC suffers from parametric divergence in the presence of external disturbances. To overcome this issue, a robust MRAC is proposed, which explicitly accounts for parametric uncertainties and disturbance effects. Simulation results demonstrate that the robust MRAC achieves superior performance compared to the conventional MRAC, maintaining stability and accurate trajectory tracking even under uncertainty and external disturbances.

Permanent Magnet Synchronous Motors (PMSM) have found widespread acceptance industrially. Vector control of PMSM allows for torque-speed decoupling, which is an important requirement in variable speed drives. This paper attempts to enhance the dynamic characteristics of a PMSM drive by replacing its speed PI controller. PI controllers usually satisfy most industrial requirements, but they are susceptible to variations in plant parameters. A fuzzy speed controller is identified as an alternative and is designed and implemented to replace the PI Speed controller. An improvement is observed in the dynamic characteristics, stability, and robustness. These tests have been performed on the Microsemi SmartFusion <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> platform using a reference design that uses a PI controller, which is available from its website. Currently, efforts are on to evaluate the effect of using a Fuzzy logic-based current controller in the PMSM drive.

This paper presented a vector controlled drives of permanent Magnet Synchronous Motor (PMSM) by using Proportional-Integral (PI) Speed controller based dSPACE implementation. The concept of vector control is applied to PMSM to obtain linear dynamics similar to that of a DC motor. The model consist of two control loops, hysteresis current controller is used for inner loop current control and PI controller for outer loop speed control. PI speed controller selected due to simplicity compare to fuzzy, neutral etc. to make sure dSPACE DS1103 successfully implemented. The PMSM vector control algorithm for a theoretical basic has been verified by experimental results and created a rapid control prototype environment by using MATLAB/ Simulink and the DS1103 DSP of dSPACE.

This paper presents the finite-time control problem for permanent magnet synchronous motor (PMSM) speed servo system using different kinds of finite-time control methods. Integral terminal sliding mode controller and continuous finite-time controller are designed respectively for the speed loop and d-axis current loop. The proof of finite-time stability for PMSM speed servo system is also given. Compared with the corresponding control method of asymptotical stability, the controller based on the finite-time control can make the output of system track the desired speed reference signal in finite time and obtain a better dynamic response and anti-disturbance performance. Meanwhile, considering the large chattering phenomenon caused by high switching gains, a composite integral terminal sliding mode control method based on disturbance observer is proposed to reduce chattering. Through feed-forward compensation based on disturbance estimation, the composite integral terminal sliding mode controller may take a smaller value for the switching gain without sacrificing disturbance rejection performance. TMS320F2808 DSP experimental results are provided to show the superiority of the proposed methods.

Introduction. This study introduces a sliding mode control (SMC) that utilizes multivariable system command estimation (MSCE-SMC) to create an innovative speed control system for the permanent magnet synchronous motor (PMSM). The motor operates through a 3-phase voltage source inverter when used in an electric vehicle (EV) model, with the goal of achieving fast speed regulation and high performance. Problem. The primary challenge is to achieve fast and accurate speed regulation for PMSMs while maintaining high performance, despite varying system parameters and external disturbances. The goal is to design a robust and adaptive speed control system for PMSMs using the SMC approach, which ensures precise speed tracking and high-performance regulation. Scientific novelty. The integration of MSCE-SMC approach, offering an innovative solution for speed control in PMSMs used in EVs. Methodology. SMC approach for the PMSM divides the system into 2 subsystems: electrical and speed. A d-q coordinate frame is used to model the PMSM, and its control strategy is outlined. A detailed model of the PMSM with SMC is presented after an in-depth review of the theoretical concepts and principles of sliding mode control. Results. To validate the proposed approach, MATLAB/Simulink is conducted, demonstrating the effectiveness and robustness of the method in PMSM speed regulation. The results confirm that the proposed method provides straightforward and precise control, accurate speed tracking, and high-performance regulation. It also shows adaptability to parameter variations and external disturbances. Practical value. The practical value of the proposed method is significant, as it provides a reliable and efficient control system for PMSMs. It offers precise speed control, robust performance under variable conditions, and high adaptability to external disturbances, making it suitable for real-world EV applications. References 22, table 1, figures 18.

Aiming at the motion control problem in permanent magnet synchronous motor speed control system, an improved deadbeat current predictive control algorithm based on fuzzy PID control is proposed. In this algorithm, the traditional PID control uses fuzzy control to realize real-time parameter adjustment, it eliminates the overshoot of the system; The improved deadbeat current predictive control is adopted in the current loop, and the control output of the speed loop is taken as the input of the current loop. the output speed of the motor is adjusted, so feedback control is formed to obtain accurate and fast track performance. The simulation results show that the control algorithm is fast and robust under no-load and disturbance conditions, which verifies the feasibility and effectiveness of the algorithm.

The development of electric and hybrid vehicles has gained increasing attention in recent years. This paper proposes an Electric drive for Hybrid vehicles application and its control strategy to achieve a wide speed range. In these vehicles, important requirements for the electric drive are low weight, small volume, high efficiency and low cost. When choosing the motor for the vehicle drive, the induction motor is an obvious alternative but a permanent magnet synchronous motor (PMSM) can offer advantages in terms of higher efficiency and specific power. In this paper a permanent magnet synchronous machine (PMSM) is used as an electric drive machine. The operation of a PMSM above the base speed is possible by weakening the permanent-magnet excitation by a demagnetizing field component supplied by the stator winding. This can be done by closed loop operation of PMSM. The speed and torque control of the PMSM drive used as hybrid vehicle is controlled by proper tuning the PI controllers. A three level diode clamped inverter using IGBT's has simulated, whose switching sequences are controlled by Space Vector Pulse Width Modulation (SVPWM). A mathematical model of PMSM drive suitable for hybrid vehicle has simulated and proper closed loop control is established by field oriented control method. The entire work is done in MATLAB/SIMULINK.

This work proposes a vector speed control scheme for Permanent Magnet Synchronous Motors (PMSM) which is robust against parameter uncertainties. It is based on a control law called VS-RMRAC (Variable Structure Robust Model Reference Adaptive Control). Such control law consists on a discrete time modification of the continuous control law presented in [1]. This paper main contribution is the proposal of a vector speed control scheme based on this controller for PMSM. Simulation and experimental results shows that the proposed scheme is robust against parameter uncertainties, which allows implementing this system without accurate plant knowledge. Obtained results show also system capability to compensate load disturbance applied to the motor axis.