采用MRAS速度观测器的异步电机无电压传感器DTC研究

为提高系统的抗干扰能力,降低运行成本,提出无电压传感器控制策略,通过逆变器的导通状态和直流侧电压估算三相定子电压,采用模型参考自适应系统（ MRAS）方法设计速度观测器,基于异步电机数学模型得到转子磁链的两种模型,根据合适的自适应机构得到精确的实际转速,实时调节模型参数,该控制方法简单,保持较高的控制精度。最后通过实验验证了控制策略的可行性。     

High performance of brain emotional intelligent controller for DTC-SVM based sensorless induction motor drive

This paper introduces the application of the induction motor (IM) drive brain emotional intelligent controller (BEIC). Intelligent regulation, modelled on the human brain, is capable of generating impulses and is used as a controller. A Model Reference Adaptive System is developed using stator current and stator voltages, which are further developed with BEIC to approximate the rotor rpm. This paper proposes that speed estimation using BEIC for direct torque control (DTC) of IM drive. The experimental work is conducted on a hardware-in-loop mechanism using a real-time digital simulator (Op-RTDS-OP5600). The simulation and test results are discussed. The proposed method is compared to the DTC-SVM-based IM drive speed control with the existing controllers.

     

Feedback controller design for variable voltage variable speed induction motor drive via Ant Colony Optimization

This paper deals with the development of feed back controller design for a voltage controlled induction motor drive employing an enhanced optimization algorithm derived from the principles of foraging of natural ants. A linearized incremental model of a voltage controlled induction motor drive is shown to exhibit parameter variation at different operating points of the drive system. A PI-controller derived at a typical operating point using traditional methods does not give satisfactory performance for a wide bandwidth of load and reference speed changes. The newly developed Ant Colony Optimization technique enforces continuous exploration of the solution space and identifies optimal controller structure. The development of optimization algorithm and its application to feed back controller design for a variable voltage induction motor drive is well documented in this paper. Experimental and simulation results are presented to validate the efficacy of the optimized controller.     

Microprocessor-based digital controller for DC motor speed control

The effectiveness of microprocessor-based systems for realizing digital random logic controllers is illustrated by the design of a controller based on an MC68B00, using E²PROM rather than RAM or ROM to enhance flexibility and avoid memory corruption or power interrupt. Moreover, the time response of the system (about 1 ms) can cover a wide spectrum of control applications. The paper is illustrated by a DC motor speed control system.     

异步电机鲁棒控制器及其Backstepp ing 设计

基于异步电机的精确模型,用Backstepping方法设计控制器,其误差系统在原点全局稳定。然而,由于反馈量的计算受参数不确定性和“可导条件”的影响,使得控制器鲁棒性较差,采用扩张状态观测器来增强鲁棒性,无需电机的精确模型,即可准确地获得反馈量,新控制器结合了Backstepping和扩张状态观测器的优点,能保证误差系统的稳定性,并具有很强的抗扰动能力,给出了控制器的详细设计过程和原理框图,并进行了数值仿真验证。     

基于高阶滑模速度控制器的异步电机模型预测转矩控制

针对三相异步电机驱动系统,提出一种基于高阶滑模速度控制器的模型预测转矩控制策略.为了降低负载扰动对系统运行性能的影响,设计一种基于二阶Super-Twisting滑模技术的速度环控制器,以代替传统PI速度控制器,并应用Lyapunov稳定性理论对其稳定性和鲁棒性进行分析,得到使速度控制系统收敛的参数范围.为了提升转矩控...     

Design of a novel adaptive TSK-fuzzy speed controller for use in direct torque control induction motor drives

This study proposes an adaptive Takagi-Sugeno-Kang-fuzzy (TSK-fuzzy) speed controller (ATFSC) for use in direct torque control (DTC) induction motor (IM) drives to improve their dynamic responses. The proposed controller consists of the TSK-fuzzy controller, which is used to approximate an ideal control law, and a compensated controller, which is constructed to compensate for the difference between the TSK-fuzzy controller and the ideal control law. Parameter variations and external load disturbances were considered during the design phase to ensure the robustness of the proposed scheme. The parameters of the TSK-fuzzy controller were adjusted online based on the adaptive rules derived in Lyapunov stability theory. The ATFSC, fuzzy control, and PI control schemes were experimentally investigated, using the root mean square error (RMSE) performance index to evaluate each scheme. The robustness of the proposed ATFSC was verified using simulations and experiments, which involved varying parameters and external load disturbances. The experimental results indicate that the ATFSC scheme outperformed the other control schemes.     

Hybrid control for speed sensorless induction motor drive

The dynamic response of a hybrid-controlled speed sensorless induction motor (IM) drive is introduced. First, an adaptive observation system, which comprises speed and flux observers, is derived on the basis of model reference adaptive system (MRAS) theory. The speed observation system is implemented using a digital signal processor (DSP) with a high sampling rate to make it possible to achieve good dynamics. Next, based on the principle of computed torque control, a computed torque controller using the estimated speed signal is developed. Moreover, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a recurrent fuzzy neural network (RFNN) uncertainty observer is utilized to adapt the lumped uncertainty online. Furthermore, based on Lyapunov stability a hybrid control system, which combines the computed torque controller, the RFNN uncertainty observer and a compensated controller, is proposed to control the rotor speed of the sensorless IM drive. The computed torque controller with RFNN uncertainty observer is the main tracking controller and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer instead of increasing the rules of the RFNN. Finally, the effectiveness of the proposed observation and control systems is verified by simulated and experimental results     

Implementation of speed controller for rotary hydraulic motor based on LS-SVM

The performance of a model-based control system depends strongly on the accuracy of the process model used. LS-SVM is a powerful method for modeling nonlinear systems. The main objective of this paper is to implement a conventional controller based on LS-SVM model for hydraulic motor. An off-line model is first identified based on LS-SVM, then via simulation tests the parameters of the discrete PI-Controller and its velocity-form are obtained then the controller parameters are applied experimentally for the hydraulic motor as a speed controller. The system performance has been evaluated; results show good performance over a wide range of operating conditions and load disturbances.     

Predictive direct torque control with reduced ripples for induction motor drive based on T‐S fuzzy speed controller

Finite‐state model predictive control (FS‐MPC) has been widely used for controlling power converters and electric drives. Predictive torque control strategy (PTC) evaluates flux and torque in a cost function to generate an optimal inverter switching state in a sampling period. However, the existing PTC method relies on a traditional proportional‐integral (PI) controller in the external loop for speed regulation. Consequently, the torque reference may not be generated properly, especially when a sudden variation of load or inertia takes place. This paper proposes an enhanced predictive torque control scheme. A Takagi‐Sugeno fuzzy logic controller replaces PI in the external loop for speed regulation. Besides, the proposed controller generates a proper torque reference since it plays an important role in cost function design. This improvement ensures accurate tracking and robust control against different uncertainties. The effectiveness of the presented algorithms is investigated by simulation and experimental validation using MATLAB/Simulink with dSpace 1104 real‐time interface.     

基于Delta算子的永磁直线同步电机非脆弱保性能速度控制器设计

利用Delta算子离散化系统采样周期是显式参数的特点,基于Delta算子方法对永磁直线同步电机(PMLSM)不同采样周期下的非脆弱保性能速度控制器的统一化设计问题进行研究.以线性矩阵不等式(LMI)给出该控制器的存在条件.通过对PMLSM闭环系统极点的分析,表明所设计的非脆弱保性能速度控制器不但能保证PMLSM在其对象参数和控制器参数同时发生范数有界摄动时闭环系统仍保持渐近稳定,而且系统的二次型性能指标上界的数学期望值不超过某个给定的上界,而不考虑控制器参数摄动情况所设计的控制器在其参数摄动时闭环系统将无法保持稳定.     

Self-constructing fuzzy neural network speed controller forpermanent-magnet synchronous motor drive

A self-constructing fuzzy neural network (SCFNN) which is suitable for practical implementation is proposed. The structure and the parameter learning phases are performed concurrently and online in the SCFNN. The structure learning is based on the partition of input space and the parameter learning is based on the supervised gradient decent method using a delta adaptation law. Several simulation and experimental results are provided to demonstrate the effectiveness of the proposed SCFNN control stratagem with the implementation of a permanent-magnet synchronous motor speed drive. Moreover, the simulation results of time varying and nonlinear disturbances are given to show the dynamic characteristics of the proposed controller over a broad range of operating conditions     

Ant colony based feedback controller design for soft-starter fed induction motor drive

The objective of this work is to design and implement a closed loop system for induction motor starting at rated current. Thyristorized AC voltage regulator is used as the starting equipment and motor current regulation is carried out using an optimally tuned Proportional-Integral (PI) controller. Since, AC voltage controller fed starting of induction motor is a non-linear process, identification of optimal values of PI controller constants is performed using a novel ant colony based optimization technique. The complete drive system including AC voltage controller fed induction motor in conjunction with optimal PI controller is first simulated in MATLAB and subsequently verified experimentally. The successful implementation with a low cost microcontroller illustrates the feasibility of the new approach.     

感应电机全阶观测器低速稳定运行的仿真

针对基于全阶磁链观测器的感应电机无速度传感器矢量控制系统低速不稳定问题,采用波波夫(Popov)超稳定性理论分析了观测器在低速发电区域不稳定原因,提出了一种保证观测器低速稳定运行的反馈增益设计准则。为了简化该系统稳定性分析过程,基于转子磁通定向,利用劳斯赫尔维茨(Routh-Hurwitz)判据将一个关于系统极点稳定的多维问题转化为系统零点稳定的一维问题进行处理,推导了转速估算系统稳定性条件,并给出了反馈增益设计方法。仿真结果表明,该系统在低速50r/min和极低速10r/min时均能稳定运行,相对于传统的基于极点配置方法,在低速发电区域的收敛性和稳定性更优,改善了无速度传感器矢量控制系统低速区域的动、静态性能。     

基于时间尺度的感应电机自抗扰控制器的参数整定

自抗扰控制器(ADRC)在感应电机控制中取得了优良的控制效果, 但控制器参数整定比较困难. 本文从时间尺度的概念入手分析ADRC参数整定问题, 通过理论分析得出感应电机的时间尺度, 并结合时间尺度与ADRC参数的关系进行参数整定, 得到了感应电机按定子磁场定向矢量控制的ADRC控制器参数整定方法, 该方法尤其适于多台电机的参数整定. 仿真结果表明该方法可行, 为感应电机ADRC提供了一种参数整定方法.     

Physiological hemostasis based intelligent integrated cooperative controller for precise fault-tolerant control of redundant parallel manipulator

This paper focuses on precise fault-tolerant control for actual redundant parallel manipulator. Based on kinematic redundancy, some unnoticed influences such as mechanical clearance have been considered to design a more precise and intelligent fault-tolerant plan for actual plants. According to regulation principles in human hemostasis system, a bio-inspired intelligent integrated cooperative controller (BIICC) is developed including system structure, algorithm and step in parameter tuning. The proposed BIICC optimises partial error signal and improves control performance in each sub-channel. Moreover, the new controller transfers and disposes cooperative control signals among different sub-channels to achieve an intelligent integrated fault-tolerant system. The proposed BIICC is applied to an actual 2-DOF (degrees of freedom) redundant parallel manipulator where the feasibility of the new controller is demonstrated. The BIICC is beneficial to control precision and fault-tolerant capability of redundant plant. The improvements are more obvious in cases where extra actuators of redundant manipulator are broken.     

Neural speed estimator for line-connected induction motor embedded in a digital processor

Estimating the electrical and mechanical parameters involved in three-phase induction motors is frequently employed to avoid measuring every variable in the process. Among mechanical parameters, speed is an important variable: it is involved in control, diagnosis, condition monitoring, and can be measured or estimated by sensorless methods. These technologies offer advantages when compared with direct measurement, such as lower cost or more robust systems. This paper proposes the use of artificial neural networks to estimate rotor speed by using current sensors for balanced and unbalanced voltage sources with a wide mechanical load range in a line-connected induction motor. This paper also presents two case analyses: (i) a single current sensor; and (ii) a multiple currents sensors. Simulation and experimental results are presented to validate the proposed approach. A neural speed estimator embedded in a digital processor is also presented.     

基于滑模与自适应观测器的感应电机非线性控制新策略

提出一种结合滑模变结构和自适应观测技术的感应电机非线性控制新方法. 以定子电流与定子磁链为状态变量建立感应电机模型, 采用非线性分析方法建立转矩与磁链误差方程, 使用自适应滑模技术设计转矩与磁链控制器, 推导出定子电压控制量. 基于模型参考技术设计自适应观测器, 向控制器提供准确的转速辨识与磁链观测值,并给出了控制系统的稳定性证明. 该方法具有转矩脉动小、定子磁链畸变不明显的优点, 低速时也具有良好的控制性能, 且对参数与负载变化有较强的鲁棒性. 仿真与实验结果证明了该控制策略的正确性与有效性.     

一种简易路灯智能控制器设计

设计了一种基于89C51单片机的路灯智能控制器,并对该智能控制器硬件及软件部分进行了说明.在2009年全国电子设计竞赛中,使用该控制器模拟路灯控制,取得了很好的控制效果.