A new instantaneous torque control of PM synchronous motor forhigh-performance direct-drive applications

A new instantaneous torque-control strategy is presented for high-performance control of a permanent magnet (PM) synchronous motor. In order to deal with the torque pulsating problem of a PM synchronous motor in a low-speed region, new torque estimation and control techniques are proposed. The linkage flux of a PM synchronous motor is estimated using a model reference adaptive system technique, and the developed torque is instantaneously controlled by the proposed torque controller combining a variable structure control (VSC) with a space-vector pulse-width modulation (PWM). The proposed control provides the advantage of reducing the torque pulsation caused by the nonsinusoidal flux distribution. This control strategy is applied to the high-torque PM synchronous motor drive system for direct-drive applications and implemented by using a software of the digital signal processor (DSP) TMS320C30. The simulations and experiments are carried out for this system, and the results demonstrate the effectiveness of the proposed control     

A supervisory fuzzy neural network controller for slider-crank mechanism

A supervisory fuzzy neural network (FNN) controller is proposed to control a nonlinear slider-crank mechanism in this study. The control system is composed of a permanent magnet (PM) synchronous servo motor drive coupled with a slider-crank mechanism and a supervisory FNN position controller. The supervisory FNN controller comprises a sliding mode FNN controller and a supervisory controller. The sliding mode FNN controller combines the advantages of the sliding mode control with robust characteristics and the FNN with on-line learning ability. The supervisory controller is designed to stabilize the system states around a defined bound region. The theoretical and stability analyses of the supervisory FNN controller are discussed in detail. Simulation and experimental results are provided to show that the proposed control system is robust with regard to plant parameter variations and external load disturbance.     

Analysis and implementation of a real-time predictive currentcontroller for permanent-magnet synchronous servo drives

A real-time current controller for PWM inverter-fed permanent-magnet synchronous motor drives is presented and analyzed. The proposed current control scheme is based on predictive control with a parallel integral loop added to compensate for the inaccuracy of the motor model and for the variations of motor parameters and DC voltage source. The proposed current control scheme is analyzed and its performance is evaluated by computer simulation. An EPROM-based implementation is presented in which calculations and pulsewidth modulation are executed by lookup tables resulting in high-speed operation. The controller performance is evaluated using a prototype l kW PM synchronous servo drive. Experimental results are given and discussed     

A nonlinear speed control for a PM synchronous motor using a simpledisturbance estimation technique

A nonlinear speed control for a permanent-magnet (PM) synchronous motor using a simple disturbance estimation technique is presented. By using a feedback linearization scheme, the nonlinear motor model can be linearized in the Brunovski canonical form, and the speed controller can be easily designed based on the linearized model. This technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. An adaptive linearization technique and a sliding-mode control technique have been reported. Although good performance can be obtained, the controller designs are quite complex. To overcome this drawback, the controller parameters are estimated by using a disturbance observer theory where the disturbance torque and flux linkage are estimated. Since only the two reduced-order observers are used for the parameter estimation, the observer designs are considerably simple and the computational load of the controller for parameter estimation is negligibly small. The nonlinear disturbances caused by the incomplete linearization can be effectively compensated by using this control scheme. Thus, a desired dynamic performance and a zero steady-state error can be obtained. The proposed control scheme is implemented on a PM synchronous motor using a digital signal processor (TMS320C31) and the effectiveness is verified through the comparative simulations and experiments     

Fuzzy adaptive speed control of a permanent magnet synchronous motor

A fuzzy adaptive speed controller is proposed for a permanent magnet synchronous motor (PMSM). The proposed fuzzy adaptive speed regulator is insensitive to model parameter and load torque variations because it does not need any accurate knowledge about the motor parameter and load torque values. The stability of the proposed control system is also proven. The proposed adaptive speed regulator system is implemented by using a TMS320F28335 floating point DSP. Simulation and experimental results are presented to verify the effectiveness of the proposed fuzzy adaptive speed controller under uncertainties such as motor parameter and load torque variations using a prototype PMSM drive system.     

Robust control of permanent magnet motors: VSS techniques lead tosimple hardware implementations

It is shown how very simple velocity-tracking robust controllers for permanent magnet motors driving nonlinear loads can be designed based on variable structure systems techniques. Very fast dynamics, accurate and robust velocity-tracking are achieved with very simple hardware components without resorting to powerful digital signal processors and related interface hardware. A cascade control structure is used to ensure maximum flexibility. The controller for a DC motor is considered in great detail. Extension to AC synchronous PM motors is also presented. At the different control levels robustness is addressed with specific algorithms and the simplest solution is always selected. The controller architecture for both DC and AC synchronous motor are presented and discussed in the paper. Experimental results related to the control of a DC motor driving a nonlinear load are also shown. They demonstrate feasibility and excellent performances of the proposed approach     

Fuzzy neural network control of a motor-quick-return servomechanism

A quick-return mechanism, which is driven by a field-oriented control permanent magnet (PM) synchronous servomotor, with fuzzy neural network (FNN) control is proposed in this study. The rod and crank of the quick-return mechanism are assumed to be rigid. First, the machine design of the motor-quick-return mechanism is developed. Next, the kinematic analysis of the quick-return mechanism is introduced. Then, an FNN controller with varied learning rates is implemented to control the motor-quick-return servomechanism without using the complex mathematical model of the motor–mechanism coupled system. Finally, experimental results are provided to demonstrate the effectiveness of the FNN controller.     

Optimal controller design for a matrix converter based surface mounted PMSM drive system

This paper proposes a new control algorithm for a matrix converter permanent magnet synchronous motor (PMSM) drive system. First, a new switching strategy, which applies a backpropagation neural network to adjust a pseudo DC bus voltage, is proposed to reduce the current harmonics of the permanent magnet synchronous motor. Next, a two-degree-of-freedom controller is proposed to improve the system performance. The parameters of this controller are obtained by using a frequency-domain optimization technique. The controller design algorithm can be applied in an adjustable speed control system and a position control system to obtain good transient responses and good load disturbance rejection abilities. The controller design procedures require only algebraic computation. The implementation of this kind of controller is only possible by using a high-speed digital signal processor. In this paper, all the control loops, including current-loop, speed-loop, and position-loop, are implemented by a 32-b TMS320C40 digital signal processor. The hardware, therefore, is very simple. Several experimental results are shown to validate the theoretical analysis.     

Total sliding-mode controller for PM synchronous servo motor driveusing recurrent fuzzy neural network

In this paper, the dynamic responses of a recurrent-fuzzy-neural-network (RFNN) sliding-mode-controlled permanent-magnet (PM) synchronous servo motor are described. First, a newly designed total sliding-mode control system, which is insensitive to uncertainties, including parameter variations and external disturbance in the whole control process, is introduced. The total sliding-mode control comprises the baseline model design and the curbing controller design. In the baseline model design, a computed torque controller is designed to cancel the nonlinearity of the nominal plant. In the curbing controller design, an additional controller is designed using a new sliding surface to ensure the sliding motion through the entire state trajectory. Therefore, in the total sliding-mode control system, the controlled system has a total sliding motion without a reaching phase. Then, to overcome the two main problems with sliding-mode control, i.e., the assumption of known uncertainty bounds and the chattering phenomena in the control effort, an RFNN sliding-mode control system is investigated to control the PM synchronous servo motor. In the RFNN sliding-mode control system, an RFNN bound observer is utilized to adjust the uncertainty bounds in real time. To guarantee the convergence of tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RFNN. Simulated and experimental results due to periodic step and sinusoidal commands show that the dynamic behaviors of the proposed control systems are robust with regard to uncertainties     

A high-performance sensorless indirect stator flux orientation control of induction motor drive

A new method for the implementation of a sensorless indirect stator-flux-oriented control (ISFOC) of induction motor drives with stator resistance tuning is proposed in this paper. The proposed method for the estimation of speed and stator resistance is based only on measurement of stator currents. The error of the measured q-axis current from its reference value feeds the proportional plus integral (PI) controller, the output of which is the estimated slip frequency. It is subtracted from the synchronous angular frequency, which is obtained from the output integral plus proportional (IP) rotor speed controller, to have the estimated rotor speed. For current regulation, this paper proposes a conventional PI controller with feedforward compensation terms in the synchronous frame. Owing to its advantages, an IP controller is used for rotor speed regulation. Stator resistance updating is based on the measured and reference d-axis stator current of an induction motor on d-q frame synchronously rotating with the stator flux vector. Experimental results for a 3-kW induction motor are presented and analyzed by using a dSpace system with DS1102 controller board based on the digital signal processor (DSP) TMS320C31. Digital simulation and experimental results are presented to show the improvement in performance of the proposed method.     

High-Speed Control of IPMSM Drives Using Improved Fuzzy Logic Algorithms

This paper presents an improved fuzzy logic controller (FLC) for an interior permanent magnet synchronous motor (IPMSM) for high-performance industrial drive applications. In the proposed control scheme for high-speed operations above the rated speed, the operating limits of IPMSM are expanded by incorporating the maximum torque per ampere operation in constant torque region and the flux-weakening operation in constant power region. The power ratings of the motor and the inverter are considered in developing the control algorithm. A new and simple FLC is utilized as a speed controller. The FLC is developed to have less computational burden, which makes it suitable for real-time implementation, particularly at high-speed operating conditions. The complete drive is implemented in real-time using digital signal processor (DSP) controller board DS 1102 on a laboratory 1-hp IPM motor. The efficiency of the proposed control scheme is evaluated through both experimental and computer simulation results. The proposed controller is found to be robust for high-speed applications     

Identification, digital control and fuzzy logic techniques applied to a synchronous generator

The experimental results obtained in the design and implementation of an decoupled digital speed and voltage controller for a micro-energy system are reported in this work. The studied system is formed by a 9 Kw DC motor driving a 10 KVA synchronous machine. There are two control loops in the proposed controller: the speed control (speed governor) and the control of the stator's voltage (automatic voltage regulator). Each control loop was designed using linear control techniques and fuzzy control techniques. Tests on the system show the performance of the proposed controllers.     

An MRAC-based nonlinear speed control of an interior PM synchronous motor with improved maximum torque operation

A model reference adaptive control (MRAC)-based nonlinear speed control strategy of an interior permanent magnet (IPM) synchronous motor with an improved maximum torque operation is presented. In most servo systems, the controller is designed under the assumption that the electrical dynamics are neglected by the field-oriented control. This requires a high-performance inner-loop current control strategy. However, the separate designs for a high-performance current regulator and a robust speed controller need considerable effort. To overcome this limitation, an MRAC-based nonlinear speed control strategy for the IPM synchronous motor is presented, considering the whole nonlinear dynamics. Nonlinear speed control is achieved by an input–output linearization scheme. This scheme, however, gives an unsatisfactory performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters are estimated by an MRAC technique in which the disturbance torque and flux linkage are estimated. The adaptation laws are derived from Lyapunov stability theory. In view of the drive efficiency, the motor has to provide the maximum torque for a given input. To drive the IPM synchronous motor under improved maximum torque operation, the estimated flux linkage is employed for the generation of the d-axis current command. The robustness and output performance of the proposed control scheme are verified through simulation results.     

Loss minimization control of permanent magnet synchronous motordrives

This paper aims to improve efficiency in permanent magnet synchronous (PM) motor drives. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current vector. The control algorithm of the current vector minimizing the electrical loss is proposed and the optimal current vector can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to the experimental PM motor drive system, in which one digital signal processor is employed to execute the control algorithms, and several drive tests are carried out. The operating characteristics controlled by the loss minimization control algorithm are examined in detail by computer simulations and experimental results     

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 simple and robust digital current control technique of a PMsynchronous motor using time delay control approach

A simple and robust digital current control technique of a permanent magnet (PM) synchronous motor using a time delay control approach is presented. Among the various current control schemes for a voltage source inverter-fed PM synchronous motor drive, the predictive control is known to give a superior performance. This control technique, however, requires the full knowledge of machine parameters and operating conditions, and gives an unsatisfactory response under the parameter mismatch between the motor and controller. To overcome such a limitation, the disturbances caused by the parameter variations are estimated by using a time delay control approach and used for the computation of the reference voltages by a simple feedforward control. Thus, the steady-state control performance can be significantly improved in an extremely simple manner, while retaining the good characteristics of the predictive control such as the good transient response and stable inverter operation. The proposed control scheme is implemented on a PM synchronous motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative simulations and experiments     

基于龙贝格观测器的PMSM无位置传感器控制系统设计

针对基于低分辨率霍尔位置传感器的永磁同步电机系统在中高速时出现的估算精度低与响应速度慢等问题,在建立永磁同步电机数学模型的基础上,将龙贝格观测器与锁相环结构相结合,提出一种永磁同步电机无位置传感器控制算法。利用MATLAB/Simulink工具搭建控制系统仿真模型验证该控制系统的可行性,并通过搭建基于PAC5232的实物平台对比验证龙贝格观测器相对于霍尔位置传感器的优越性。实验结果表明,该无位置传感器控制系统有效地提高了系统的响应速度和估算精度,使其能够更好地跟踪转子速度以及转子位置信息。     

Adaptive fuzzy neural network control for motor-toggle servomechanism

In this study, the dynamic responses of an adaptive fuzzy neural network (FNN) controlled toggle mechanism is described. The toggle mechanism is driven by a permanent magnet (PM) synchronous servo motor. First, based on the principle of computed torque, an adaptive controller is developed to control the position of a slider of the motor-toggle servomechanism. Since the selection of control gain of the adaptive controller has a significant effect on the system performance, an adaptive FNN controller is proposed to control the motor-toggle servomechanism. In the proposed adaptive FNN controller, an FNN is adopted to facilitate the adjustment of control gain on line. Moreover, simulated and experimental results due to a periodic sinusoidal command show that the dynamic behaviors of the proposed adaptive and adaptive FNN controllers are robust with regard to uncertainties.     

A robust adaptive controller for PM motor drives in roboticapplications

The paper deals with theoretical development and practical implementation of an adaptive speed and position regulator suitable for robotic applications. The proposed adaptive control scheme is characterized by a reduced amount of computation and is based on the model reference adaptive control approach to compensate the variations of the system parameters, such as inertia and torque constant. A disturbance torque observer is employed to balance the required load torque and reduce the complexity of the adaptive algorithm. Simulation tests of a robotic drive, including an interior type permanent magnet synchronous (IPMS) motor, are reported in order to compare the proposed control scheme with standard speed and position regulators. Experimental results, obtained from a prototype based on a commercial PC board, are also reported in order to practically evaluate the feasibility and the features of the proposed adaptive control scheme     

Variable flux control of permanent magnet synchronous motor drivesfor constant torque operation

In this paper, a small signal model of permanent magnet synchronous machines is developed which includes both components of torque, i.e., magnet torque and reluctance torque. The effects of flux variations on the torque are analyzed by the use of the developed model. The off-line torque compensation method proposed for induction machines is then adapted to permanent magnet motor drives to achieve a constant torque, variable flux operation of the drives. A sensitivity analysis is performed to show that the off-line method is influenced considerably by machine parameter variations. Therefore the concept of forced compensation is introduced and an on-line torque compensation controller is proposed. Simulation results are presented to show the effectiveness of the proposed controller. An experimental vector controlled permanent magnet motor drive including the on-line torque compensation controller is implemented based on a TMS320C31 DSP to evaluate the method. The experimental results also confirm a desirable variable flux control of the motor drive under constant torque operation