Real-time IP position controller design with torque feedforwardcontrol for PM synchronous motor

A digital signal processor (DSP)-based permanent magnet (PM) synchronous motor (SM) drive with a proposed recursive least-square (RLS) estimator and real-time integral-proportional (IP) position controller is introduced in this study. First, the rotor inertia constant, the damping constant, and the disturbed load torque of the synchronous motor are estimated by the proposed RLS estimator, which is composed of an RLS estimator and a torque observer. Next, the IP position controller is real-time designed according to the estimated rotor parameters, to match the time-domain command tracking specifications. Then, the observed disturbance torque is fed forward, to increase the robustness of the synchronous motor drive     

New self-tuning fuzzy PI control of a novel doubly salient permanent-magnet motor drive

In a doubly salient permanent-magnet (DSPM) motor drive, it is difficult to get satisfied control characteristics by using a normal linear proportional plus integral (PI) controller due to the high nonlinearity between speed and current or torque. Hence, a new self-tuning fuzzy PI controller with conditional integral, which is performed by a single-chip N87C196KD, is proposed. The initial parameters of the controller are optimized by using genetic arithmetic. Simulation and experiments on the newly proposed 8/6-pole DSPM machine have shown that the proposed new self-tuning fuzzy PI controller offers better adaptability than the normal linear PI control and that the developed motor drive offers better steady-state and dynamic performances.     

A DSP-based adaptive controller for a smooth positioning system

The implementation of a self-tuning regulator for the positioning of a direct-drive servomotor is described. The servo motor is a permanent magnet DC motor in which no speed reducer is used. The auto-tuning regulator consists of two major loops. The inner loop contains a feedback (PD or PID) regulator with additional feedforward terms. The parameters of the feedforward compensation are adjusted by the outer loop, which contains an online parameter estimator. The estimator is based on a recursive least-squares equation, and the estimated parameters are the load inertia and viscous friction. This self-tuning regulator has been simulated with PC.MATLAB, and the results demonstrate the high performance of the scheme. Experimental results obtained with a small DC motor (Electrocraft E-576) are presented, and these results show good agreement with the digital simulation results. There are two innovative aspects to this work. First, parameter estimation is used to adapt the feedforward compensation terms instead of the gains of the feedback controller, as usually is the case in conventional indirect self-tuning regulators. Secondly, the complete adaptive controller has been implemented using a single-chip digital signal processor (DSP), which results in the reduction of system hardware and cost     

Robust control using neural network uncertainty observer for linearinduction motor servo drive

A robust controller, that combines the merits of integral-proportional (IP) position control and neural network (NN) observed technique, is designed for a linear induction motor (LIM) servo drive in this study. First, the secondary flux of the LIM is estimated using a sliding-mode flux observer on the stationary reference frame and the feedback linearization theory is used to decouple the thrust and the flux amplitude of the LIM. Then, the IP position controller is designed according to the estimated mover parameters to match the time-domain command tracking specifications. Moreover, a robust controller is formulated using the NN uncertainty observer, which is implemented to estimate the lumped uncertainty of the controlled plant, as an inner-loop force controller to increase the robustness of the LIM servo drive system. Furthermore, in the derivation of the online training algorithm of the NN, an error function is used in the Lyapunov function to avoid the real-time identification of the system Jacobian. In addition, to increase the speed and accuracy of the estimated flux, the sliding-mode flux observer is implemented using a 32 bit floating-point digital signal processor (DSP) with a high sampling rate. The effectiveness of the proposed control scheme is verified by both the simulated and experimental results     

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.     

Using interval phase margin assignment to self-tune a PI AQM controller for TCP traffic

We propose a self-tuning PI (Proportional-Integral) controller for an AQM (Active Queue Management) router supporting TCP traffic in the Internet. Classical control theory is applied in the controller design to meet the phase margin specification in the frequency domain. By assigning a proper interval of the phase margin, we can achieve good AQM performance by making the control system adapt to dramatic load changes. Our self-tuning PI controller self-tunes only when there is a great change in the network environment that would cause the phase margin of the AQM control system to drift outside the specified interval. Based on the knowledge of the queue size, our PI controller can regulate the TCP source window size by adjusting the packet drop probability, thus clamping the steady queue size around a desirable target buffer occupancy. We demonstrate by OPNET^® simulations that with our self-tuning PI controller applied, the network exhibits a good transient behavior. A simple PID (Proportional-Integral-Derivative) controller design method is also provided.     

On designing self-tuning controllers for AQM routers supporting TCP flows based on pole placement

This paper revisits the simple pole placement technique in the classical control theory, and exploits this technique to propose two kinds of controllers for active queue management (AQM) in Internet protocol (IP) routers: the self-tuning proportional controller based on pole placement (ST/spl I.bar/P/spl I.bar/PP) and the self-tuning proportional-plus-integral controller based on pole placement (ST/spl I.bar/PI/spl I.bar/PP). The damping ratio /spl xi/ and undamped natural frequency /spl omega//sub n/ can be appropriately chosen such that: 1) the transient response performance of the system is satisfied and 2) all the poles would lie in the left-half s-plane to guarantee the stability of the control system. The self-tuning controllers can assign proper intervals of /spl xi/ and /spl omega//sub n/ to achieve good AQM performance and thereby adapting the system to significant load changes very well. Furthermore, the ST/spl I.bar/PI/spl I.bar/PP controller can regulate the packet drop probability based on the knowledge of the instantaneous queue size, and clamp the steady value of the queue length to a specified reference value. We verify the effectiveness of these two controllers via OPNET simulation. Our simulation results show the following: 1) choosing appropriate /spl xi/ and /spl omega//sub n/ can successfully satisfy the transient response of the system and 2) when the network load changes, the ST/spl I.bar/P/spl I.bar/PP controller and the ST/spl I.bar/PI/spl I.bar/PP controller exhibit extremely short settling time.     

Sensorless speed control of nonsalient permanent-magnet synchronous motor using rotor-position-tracking PI controller

This paper presents a new velocity estimation strategy of a nonsalient permanent-magnet synchronous motor (PMSM) drive without a high-frequency signal injection or special pulsewidth-modulation (PWM) pattern. This approach is based on the d-axis current regulator output voltage of the drive system that has the information of rotor position error. Rotor velocity can be estimated through a rotor-position-tracking proportional-integral (PI) controller that controls the position error to zero. For zero and low-speed operation, the PI controller gains of rotor position tracking controller have a variable structure according to the estimated rotor velocity. In order to boost the bandwidth of the PI controller around zero speed, a loop recovery technique is applied to the control system. The proposed method only requires the flux linkage of the permanent magnet and is insensitive to parameter estimation error and variation. The designers can easily determine the possible operating range with a desired bandwidth and perform vector control even at low speeds. The experimental results show the satisfactory operation of the proposed sensorless algorithm under rated load conditions.     

A robust speed controller for induction motor drives

A speed controller considering the effects of parameter variations and external disturbance for indirect field-oriented induction motor drives is proposed in this paper. First a microprocessor-based indirect field-oriented induction motor drive is implemented and its dynamic model at nominal case is estimated. Based on the estimated model, an integral plus proportional (IP) controller is quantitatively designed to match the prescribed speed tracking specifications. Then a dead-time compensator and a simple robust controller are designed and augmented to reduce the effects of parameter variations and external disturbances. The desired speed tracking control performance of the drive can be preserved under wide operating range, and good speed load regulating performance can also be obtained. Theoretic basis and implementation of the proposed controller are detailedly described. Some simulated and experimental results are provided to demonstrate the effectiveness of the proposed controller     

Online self-tuning ANN-based speed control of a PM DC motor

This paper presents an online self-tuning artificial-neural-network (ANN)-based speed control scheme of a permanent magnet (PM) DC motor. For precise speed control, an online training algorithm with an adaptive learning rate is introduced, rather than using fixed weights and biases of the ANN. The complete system is implemented in real time using a digital signal processor controller board (DS1102) on a laboratory PM DC motor. To validate its efficacy, the performances of the proposed ANN-based scheme are compared with a proportional-integral controller-based PM DC motor drive system under different operating conditions. The comparative results show that the ANN-based speed control scheme is robust, accurate, and insensitive to parameter variations and load disturbances     

Fuzzy Logic-Based Torque Control System for Milling Process Optimization

This paper focuses on the design and implementation of a fuzzy-logic-based torque control system, embedded in an open-architecture computer numerical control (CNC), in order to provide an optimization function for the material removal rate. The control system adjusts the feed rate and spindle speed simultaneously as needed, to regulate the cutting torque using the CNC's own resources without requiring additional hardware overheads. The control system consists of two inputs (i.e., torque error and change of error), two outputs (i.e., the feed rate and spindle speed increment) fuzzy controller, and a self-tuning mechanism, all of which are embedded within the kernel of a standard open control. The self-tuning strategy is based on the measured peaks in the torque error signal of the closed-loop system response. The self-tuning fuzzy controller is applied to the milling process in a production environment in order to demonstrate the improvements in performance and effectiveness. Two approaches are tested, and their performance is assessed using several performance measurements. These approaches are the two-input/two-output for the fuzzy controller and a single-output fuzzy controller (i.e., only feed-rate modification), with and without the self-tuning mechanism. The results demonstrate that the proposed control strategy provides better transient performance, accuracy, and machining cycle time than the others, thus, increasing the metal removal rate.     

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     

A Design and Experiment of Speed Controller with PI-Plus Bang-Bang Action for a DC Servomotor with Transistorized PWM Drives

A speed controller with proportional-integral (PI)-plus bang-bang action is proposed for dc servomotors with transistorized pulse width modulated (PWM) drives. The controller employs the PI-action when the magnitude of the error between the reference signal and the speed output signal is smaller than some precribed value. Otherwise, the controller produces the maximum allowable control signal with the integrator reset. Specifically, a mathematical analysis of the motor system with the proposed speed controller is presented and a rule of thumb for parameter design is provided.     

Robust speed control of IM with torque feedforward control

The authors describe a digital signal processor-based (DSP-based) robust speed control for an induction motor (IM) with the load-torque observer and the torque feedforward control. In the proposed system, the load torque is estimated by the minimal-order state observer based on the torque component of a vector-controlled IM. Using the load-torque observer, a speed controller can be provided with a torque feedforward loop, thus realizing a robust speed control system. The control system is composed of a DSP-based controller, a voltage-fed pulsewidth modulated (PWM) transistor inverter and a 3.7 kW IM system. An eccentric load with an arm and a weight is coupled to the IM and it generates the sinusoidal gravitational fluctuating torque. Experimental results show robustness against disturbance torque and system parameter change     

Experimental evaluation of a self-tuning controller

A self-tuning control (STC) scheme is examined in real time by comparing its performance with that of two other control schemes. Experimental results show that the controller is superior to a well-known conventional self-tuning controller and a proportional-plus-integral (PI) self-tuning controller whose parameters are selected on the basis of a pole assignment method. The control scheme can be extended to multi-input multi-output systems     

开放平台下调速系统模糊控制的教学实践

本文介绍了基于开放式计算机控制直流调速系统教学实验平台,指导学生在传统PID调节器中加入模糊控制策略的教学实践.笔者分析了Matlab/SimuIink软件环境下参数在线自整定模糊PID控制器的设计过程,并对比分析了不同控制策略实验结果.开发的实验装置新功能可以有效提升实验教学水平.     

Dynamic control of electronic differential in the field weakening region

A simple and dynamic electronic differential control method for an outer rotor motor driven electric vehicle based on fuzzy gain scheduling of PI gains method is proposed for constant torque and power region operation using brushless direct current (BLDC) machine. The proposed method is quite insensitive to torque fluctuations and transient speed oscillations due to surface mounted permanent magnet (SMPM) BLDC machines constraints in the field weakening region. To improve the dynamics and stability of the electronic differential system and eliminate the skidding of the wheels and reduce the heating of electric machine in the wide speed range operation, a robust control method is developed. Moreover, PI controller gains are updated continuously by fuzzy gain scheduling approach which has phase advance angle, steering angle and measured speed as controller input parameters in order to eliminate the errors caused from the variable road conditions and torque oscillations in the field weakening region. The proposed method is implemented with 2 × 1.5 kW BLDC motor drive controlled by a TMS320F28335 digital signal processor (DSP). The experimental results show that the proposed method exhibits greater stability under various load, road and vehicle speed conditions.     

High-performance speed control of electric machine usinglow-precision shaft encoder

For a high-performance servo drive system, it is important to estimate and control the motor speed precisely over a wide-speed range. Therefore, the disturbance-rejection ability and the robustness to variations of the mechanical parameters such as inertia should be considered. This paper shows that the adaptive state estimator and self-tuning regulator based on the recursive extended least squares (RELS) parameter identification method can achieve high-performance speed control over a wide-speed range. The RELS method identifies the variations of mechanical parameters, and the estimated mechanical parameters are used to replace the role of manual tuning by adjusting the gain of the speed controller automatically for good dynamic response. Also, these estimated parameters are used to adapt the Kalman filter, which is an optimal state estimator, to provide good estimation performance for the rotor speed, rotor position and disturbance torque even in a noisy environment. Simulation and experimental results show an improved speed control performance in the wide-speed range     

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.     

Commissioning of a state-controlled high-powered electrical driveusing evolutionary algorithms

The subject of this research is the automated startup procedure of a PI state-controlled rolling-mill motor by using evolutionary algorithms. Compared to the conventional PI speed control, applying the method of deliberate pole placement to the state controller design succeeds in improving the transient response of setpoint and disturbance changes. To put the PI state-controlled drive with observer into operation to obtain a controller with a high robustness and dynamics, the precise knowledge of this physical parameter is necessary. An evolution-based system is used to solve the estimation problem. A high degree of reliability respecting multimodal characteristics and robustness against random noise is expected from the identification method. Evolutionary algorithms fulfill this requirement. With genetic operators like mutation, crossover, and selection, evolutionary algorithms mimic the principles of organic evolution in order to solve the optimization problem