Control Of Linear Synchronous Motor Research Articles

Current decoupling control of linear synchronous motor based on improved extended state observer

Current decoupling control of linear synchronous motor based on improved extended state observer

Improved predictive position control for linear synchronous motor with disturbance observer

Improved predictive position control for linear synchronous motor with disturbance observer

Current Decoupling Control of Linear Synchronous Motor Based on an Improved Sliding Mode Observer

This paper proposes an improved sliding mode observer (ISMO) for the current decoupling control of the linear synchronous motor (LSM) to improve the dynamic performance of the LSM system. The proposed ISMO is based on variable power and exponential terms. By comparing the convergence time of the proposed ISMO and the conventional sliding mode observer (CSMO), we find that the ISMO can achieve a high convergence rate than the CSMO with the appropriate parameter options. Because the ISMO is established based on the extended state equation of the lumped disturbances, which includes the current coupling interferences and parameter variation disturbances, the ISMO-based decoupling control (ISMO-DC) can suppress these two types of disturbances simultaneously. The stability analysis based on the Lyapunov stability theory guarantees the convergence of the proposed ISMO. The experimental results verify the effectiveness of the proposed method in achieving a better decoupling control performance for the LSM system.

Feedback Linearization Adaptive Dynamic Sliding Mode Control of Linear Synchronous Motor for CNC Machine Tools

Feedback Linearization Adaptive Dynamic Sliding Mode Control of Linear Synchronous Motor for CNC Machine Tools

Feedforward element design using learning controller for precision control of linear synchronous motor with nonlinear characteristics

This study presents a time-invariant feedforward (FF) element design for the high-speed and high-precision tracking control of an ultrahigh-acceleration, high-velocity linear synchronous motor (LSM). The linear motor can generate an acceleration greater than 70 G (= 686 m/s2) and move at a velocity above 10 m/s. To take advantage of this performance and realize high response, the design and usage of suitable FF elements is crucial. However, as the LSM includes highly nonlinear characteristics, it is difficult to provide an exact dynamic model for FF design. To overcome this problem, a control system with a learning controller (LC) as the FF element has been designed previously, demonstrating high-precision and high response motion. However, the motion performance can be achieved only with sufficient pre-learned motions. The integrator and the disturbance observer that were effective in suppressing disturbances were removed from the control system. In addition, the control system has some FF time-invariant elements along with the LC. This study proposes a design method for easy design of all FF elements using an LC. The designed FF elements are time invariant and are used with an integrator and a disturbance observer, without pre-learning. Using the proposed method, two sets of time-invariant FF elements are designed. The performances of two control systems, which include a set of time-invariant FF elements for each, and a simple disturbance observer are experimentally examined and compared with two previously designed control systems. Experimental results demonstrate that the performance of one of the control systems with a set of time-invariant FF elements designed in this study and a disturbance observer is good and almost comparable with that of the previously designed control system with high-precision and high response motion.

Intelligent fractional-order backstepping control for an ironless linear synchronous motor with uncertain nonlinear dynamics

This study aims to develop an intelligent fractional-order backstepping controller to control the mover position of an ironless permanent magnet linear synchronous motor. First, we investigated the operating principle and dynamic modeling of the linear synchronous motor based on the field-oriented control method. Next, to improve the convergence speed and control accuracy of the conventional backstepping controller, we designed a fractional-order backstepping controller that has more degrees of freedom in the control parameters. However, designing the switching control gain is difficult owing to the unknown degree of uncertainty. To address this problem, we proposed an intelligent fractional-order backstepping controller to further enhance the adaptiveness and robustness of the fractional-order backstepping controller. In this intelligent controller, we proposed a Hermite-polynomial-based functional-link fuzzy neural network as an uncertainty estimator that can directly estimate system uncertainty, thereby improving the disturbance rejection ability and requiring no uncertainty bound information. Additionally, to compensate for the estimation error introduced by the estimator, we designed an exponential compensator that employs a smooth exponential self-regulation mechanism. We utilized the Lyapunov theorem to derive estimation laws for the online tuning of the control parameters. Experimental results demonstrate the effectiveness and high positioning performance of the proposed intelligent fractional-order backstepping controller in comparison with the backstepping controller and fractional-order backstepping controller in the linear synchronous motor control system.

The Reseach on Model Predictive Control for Linear Synchronous Motor of Maglev Train

The PID controller with an advantage of simple structure and easy extension is difficult to meet the requirements of the speed control system during the parameters variation and load disturbance. This paper presents a model predictive control(MPC) strategy for motor speed control based on analysis of the mathematical model of long stator linear synchronous motor(LSLSM), which utilizes move-blocking strategy to reduce the degrees of freedom of the controller by fixing the system input to keep it constant over several time. Then a low-computation MPC controller is designed for the sake of controller implementation in practice. Finally, the simulation experiments are conducted to verify the effectiveness of the proposed controller by using Matlab. Results show that the MPC controller effectively improved the dynamic performance and steady state accuracy of the system and the low-computation MPC reduced the computational complexity with a decline in accuracy.

Control Platform for Tubular Permanent-Magnet Linear Synchronous Motor

In order to study the characteristics of the linear motor, this paper constructed the tubular permanent-magnet linear synchronous motor control experiment platform. Firstly, this paper introduces the structure and principle of the TPMLSM. Secondly, metal bracket is made. Magnetic grid scale is used as position sensor. Three closed-loop controller is constructed. Finally, controller make the linear motor to achieve pre-set target through the programming. The linear motor completed the intended target , and shows excellent characteristics.

이중 학습에 의한 선형동기모터의 위치제어

This paper proposes PID and RIC (Robust Internal-loop Compensator) based motion controller using dual learning algorithm for position control of linear synchronous motor respectively. Its gains are auto-tuned by using two learning algorithms, reinforcement learning and neural network. The feedback controller gains are tuned by reinforcement learning, and then the feedforward controller gains are tuned by neural network. Experiments prove the validity of dual learning algorithm. The RIC controller has better performance than does the PID-feedforward controller in reducing tracking error and disturbance rejection. Neural network shows its ability to decrease tracking error and to reject disturbance in the stop range of the target position and home.

A Nonlinear Controller for PMLSM Control System Based on Tracking Differentiator

This paper introduces tracking differentiator based on the classical PID control in order to arrange the transitional process according to the set point and control system parameters, solving the contradictions between speed and overshoot of the manipulated variable in the traditional PID control. At the same time, tracking differentiator provide an effective method of calculating differential with low noise amplification. Nonlinear PID controller adopts a nonlinear combination of error, error differential and error integral to calculate the controlled variable in a very effective way. Applying this kind of nonlinear PID controller to the permanent magnet linear synchronous motor control system , the experimental results show that PMLSM can follow the speed command quickly in no overshoot, and has strong robustness, good static and dynamic characteristics.

Recurrent fuzzy neural network controller design using sliding-mode control for linear synchronous motor drive

A sliding-mode recurrent fuzzy neural network control (SMRFNNC) is proposed to control the mover of a permanent-magnet linear synchronous motor (PMLSM) servo drive so as to track a periodic sinusoidal reference trajectory. First, the PMLSM drive system is identified by a recurrent fuzzy neural network identifier (RFNNI) to provide sensitivity information of the drive system to a recurrent fuzzy neural network controller (RFNNC). Next, a sliding-mode adjuster (SMA) is determined according to the sliding mode condition. Then, the SMA is backpropagated through the RFNNI to train the parameters of the RFNNC online. Simulated and experimental results show that the control effort and chattering of the SMRFNNC are smaller than those of sliding-mode control. Moreover, a robust control performance is achieved when uncertainties occur including a nonlinear friction force.

A novel two-degree-of-freedom controller design for a permanent magnet linear synchronous motor control system

This paper proposes a novel two-degree-of-freedom optimal controller design for a permanent magnet linear synchronous motor position-control system. The param-eters of the controller are obtained by using a frequency-domain optimization technique. A systematic design of the controller and the detailed implementation of the proposed system are discussed. The closed-loop control system possesses good transient responses and good load disturbance responses. In addition, the system has a good tracking ability. Several experimental results are provided to validate the theoretical analysis.

A novel two-degree-of-freedom controller design for a permanent magnet linear synchronous motor control system

This paper proposes a novel two-degree-of-freedom optimal controller design for a permanent magnet linear synchronous motor position-control system. The parameters of the controller are obtained by using a frequency-domain optimization technique. The systematic design of the controller and the detailed implementation of the proposed system are discussed. The closed-loop control system exhibits good transient responses and good load disturbance responses. In addition, the system has a good tracking ability. Several experimental results are provided to validate the theoretical analysis.

Robust recurrent fuzzy neural network control for linear synchronous motor drive system

A robust recurrent fuzzy neural network control (RFNNC) system is proposed to control the position of the mover of a permanent magnet linear synchronous motor drive system in this study. In the proposed RFNNC system, a RFNN controller is the main tracking controller, that is used to mimic an ideal feedback linearization control law, and a robust controller is proposed to confront the shortcoming of the RFNN controller. Moreover, to relax the requirement for the bound of lumped uncertainty, which comprises a minimum approximation error, optimal parameter vectors and higher order terms in Taylor series, a RFNNC system with adaptive bound estimation is investigated. In the control system a simple adaptive algorithm is utilized to estimate the bound of lumped uncertainty. In addition, simulated and experimental results due to periodic reference trajectories show that the dynamic behaviors of the proposed control systems are robust with regard to uncertainties.

Investigation of superconducting linear synchronous motor propulsion control via an exact mathematical model

This paper describes the performance of the superconducting linear synchronous motor control system used for a transportation vehicle by using an exact dq0-axis mathematical model. The paper first shows the detailed block diagram of the speed control system, which includes the blocks of propulsion force and speed emf computations. A detailed discussion is devoted to the design of the control system. A cascade control system with PI controllers is designed as a numerical demonstration. It is also pointed out that the cascade control structure is a natural form for the power feeding method with three inverters. Performance simulations are shown for severe track conditions such as tunnel and track gradients as well as in a normal case. It is demonstrated that integrator windup of the speed controller can occur in the case of a severe condition in which one of the inverters is disabled. We present a design with more robustly stable performance by designing an antiwindup controller. © 1999 Scripta Technica, Electr Eng Jpn, 128(2): 45–52, 1999

Investigation of Superconducting Linear Synchronous Motor Propulsion Control via an Exact Mathematical Model

This paper describes the performance of the superconducting linear synchronous motor control system used for a transportation vehicle by using an exact dqO-axis mathematical model. The paper firstly shows the detailed block diagram of the speed control system, which includes the blocks of propulsion force and speed emf computations. A detailed discussion is given to the design of the control system. A cascade control system with PI controllers is designed as a numerical demonstration. It is also pointed out that the cascade control structure is a natural form for the power feeding method with three inverters. Performance simulations are shown for severe track conditions like tunnel and track gradient as well as a normal case. It is demonstrated that an integrator windup of the speed controller can occur in the case of a severe condition that one of the inverters is disabled. We show a design with more robustly stable performance by designing an anti-windup controller.

ACTIVE DAMPING OF MAGLEV VEHICLES USING SUPERCONDUCTING LINEAR SYNCHRONOUS MOTORS

ABSTRACT This paper explores the use of linear synchronous motor control to provide active damping for magnetically-levitated vehicles. Using a single LSM, only heave and surge damping can be provided, but, with a dual LSM, roll and yaw damping can also be achieved. The paper gives design data applicable to the reference design of theCanadian 500 km/h Maglev system.