Application of Diagonal Recurrent Neural Network toDC Motor Speed Control Systems

A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct Current) speed control system with the ability to auto-tune PI (Proportion Integral) parameters based on combining DRNN with PI controller. The simulation results of DRNN show better control performances and potential practical use in comparison with PI controller.

Current Search: Performance Evaluation and Application to DC Motor Speed Control System Design

This paper proposes the current search (CS) metaheuristics conceptualized from the electric current flowing through electric networks for optimization problems with continuous design variables. The CS algorithm possesses two powerful strategies, exploration and exploitation, for searching the global optimum. Based on the stochastic process, the derivatives of the objective function is unnecessary for the proposed CS. To evaluate its performance, the CS is tested against several unconstrained optimization problems. The results obtained are compared to those obtained by the popular search techniques, i.e., the genetic algorithm (GA), the particle swarm optimization (PSO), and the adaptive tabu search (ATS). As results, the CS outperforms other algorithms and provides superior results. The CS is also applied to a constrained design of the optimum PID controller for the dc motor speed control system. From experimental results, the CS has been successfully applied to the speed control of the dc motor.

Frequency-Speed Control Model Identification of Ultrasonic Motor Using Step Response

Control model of ultrasonic motor is the foundation for high control performance.The frequency of driving voltage is commonly used as control variable in the speed control system of ultrasonic motor.Speed control model with the input frequency can significantly improve speed control performance.Step response of rotating speed is tested.Then,the transfer function model is identified through characteristic point method.Considering time-varying characteristics of the model parameters,the variables are fitted with frequency and speed as the independent variables,and the variable model of ultrasonic motor system is obtained,with consideration of the nonlinearity of ultrasonic motor system.The proposed model can be used in the design and analysis of the speed control system in ultrasonic motor.

Dynamic Model Identification for Ultrasonic Motor Frequency-Speed Control

The mathematical model of ultrasonic motor(USM)is the foundation of the motor high performance control.Considering the motor speed control requirements,the USM control model identification is established with frequency as the independent variable.The frequency-speed control model of USM system is developed,thus laying foundation for the motor high performance control.The least square method and the extended least square method are used to identify the model.By comparing the results of the identification and measurement,and fitting the time-varying parameters of the model,one can show that the model obtained by using the extended least square method is reasonable and possesses high accuracy.Finally,the frequency-speed control model of USM contains the nonlinear information.

Fuzzy-Logic Based Speed Control of Induction Motor Considering Core Loss into Account

Rotor flux and torque of an induction motor (IM) are decoupled to obtain performance of DC motor. The decoupling strategy has been developed in terms of stator current components where the core loss is neglected. Many different controllers including fuzzy logic controller (FLC) with neglecting core loss have been designed to control the speed of induction motor. The outcome of investigation about the effect of core loss on indirect field oriented control (IFOC) has been concluded that the actual flux and torque are not reached to the reference flux and torque if core loss is neglected. Thus, the purpose of this paper is to propose a fuzzy logic speed controller of induction motor where flux and torque decoupling strategy is decoupled in terms of magnetizing current instead of stator current to alleviate the effects of core loss. The performances of proposed fuzzy-logic-based controller have been verified by computer simulation. The simulation of speed control of IM using PI and FLC are performed. The simulation study for high-performance control of IM drive shows the superiority of the proposed fuzzy logic controller over the conventional PI controller.

Virtual Speed Sensorless Desired Control Strategy of Maglev Single-sided Linear Induction Motors

单边短初级长次级直线感应电机己普遍应用于低速磁悬浮的驱动系统。由于在动态纵向边端效应影响下等效电路不对称，单边直线感应电机（single-sided linear inductionmotor，SLIM）的一些参数非线性变化。传统的应用于旋转电机的无速度传感器方法不再适用。首先分析了SLIM的M／T轴等效电路，选择次级磁链作为速度观测器状态变量。根据李雅普诺夫系统稳定性判据，推导出适用于SLIM的无速度传感器辨识；然后，采用反馈广义积分观测器控制稳态辨识速度的双幅脉振幅值；引入虚拟期望变量（virtualdesiredvariable，VDV）法，利用估算速度参与SLIM的恒滑差频率矢量控制。仿真与实验对所提控制算法的有效性和实用性进行了验证，所得结论可为磁悬浮的无速度传感器控制提供参考。

Application of Super-Synchronization Speed Control Technology in Two 80 MVA Motor-Generator Units of HL-2A

Two sets of super-synchronization speed control assemblies for two 80 MVA motor-generator units have been developed successfully in order to satisfy the demand of the toroidal field system in the HL-2A tokamak. Based on the three-phase logical no-circumfluence a.c./a.c. cycloconverter, the speeds of two 2500 kW double fed drive motors have been regulated by means of the vector control technology. The maximum operating speed of each motor- generator unit has been raised from 1488 rpm （revolutions per minute） to 1650 rpm and the released energy of each unit during a pulsed discharge can reach 500 MJ. As a result, the toroidal field system has the capacity to provide 2.8 tesla （T） in HL-2A experiments.

Single Phase Induction Motor Drive with Restrained Speed and Torque Ripples Using Neural Network Predictive Controller

In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.

CAN-based Synchronized Motion Control for Induction Motors

A control area network （CAN） based multi-motor synchronized motion control system with an advanced synchronized control strategy is proposed. The strategy is to incorporate the adjacent cross-coupling control strategy into the sliding mode control architecture. As illustrated by the four-induction-motor-based experimental results, the multi-motor synchronized motion control system, via the CAN bus, has been successfully implemented. With the employment of the advanced synchronized motion control strategy, the synchronization performance can be significantly improved.

FPGA Based Speed Control of SRM with Optimized Switching Angles by Self Tuning

The electromagnetic torque and speed in Switched Reluctance Motor (SRM) greatly depend on the excitation parametersi.e. turn-on angle, turn-off angle, dwell angle and magnitude of the phase currents of its phases. At lower speeds, a change in the current contributes the torque requirement which can be achieved either by voltage control (pulse width modulation) or instantaneous current control techniques. At high speeds, due to high back EMF, the regulation of current is crucial and achieved with the control of switching angles of phases. This type of control is referred as average torque control, where the torque is averaged over one stroke (2π/Nr). With constant dwell angle, advancing the phase angle influences the current into the phase winding at minimum inductance position. It has more time to get the current out of the phase winding before the rotor reaches the negative inductance slope. To maintain the speed of the motor at different load conditions, the turn-on and turn-off angles are adaptively varied. The change in dwell angle may be required where the turn-on and turn-off angle may not be sufficient to reach the required speed. In this paper, a new algorithm is proposed for self tuning of switching parameters of SRM. The proposed algorithm is simulated in MATLAB-Simulink and experimentally validated with Field Programmable Gated Array (FPGA) using MATLAB- system generator environment.

Sensorless Vector Control of Parallel-Connected Multiple Induction Motors Fed by a Single Inverter

A method of improving the stability of multiple-motor drive system fed by a 3-leg single inverter has been devised that employs the averages and differences of estimated parameters for field-oriented control. The parameters of each motor (stator current, rotor flux, and speed) are estimated using adaptive rotor flux observers to achieve sensorless control. The validity and effective of the proposed method have been demonstrated through simulations and experiments.

Backstepping Adaptive Controller of Electro-Hydraulic Servo System of Continuous Rotary Motor

In order to consider the influence of the continuous rotary motor electro-hydraulic servo system parameters change on its performance,the design method of backstepping adaptive controller is put forward.The mathematical model of electro-hydraulic servo system of continuous rotary motor is established,and the whole system is decomposed into several lower order subsystems,and the virtual control signal is designed for each subsystem from the final subsystem with motor angular displacement to the subsystem with system control input voltage. Based on Lyapunov method and the backstepping theory,an adaptive backstepping controller is designed with the changed parameters adaptive law. It is proved that the system reaches the global asymptotic stability,and the system tracking error asymptotically tends to zero. The simulation results show that the backstepping adaptive controller based on the adaptive law of the changed parameters can improve the performance of continuous rotary motor,and the proposed control strategy is feasible.

The Joint Control of Variable Speed and On-Ramp Metering for Urban Expressway

The traffic performance of urban expressway is subject to non-recurring and recurring events, which may cause heavy congestion and vehicles long queuing on ramps. The low performance may bring more traffic delay to the whole network of urban road. This paper presents a new method, the joint control of variable speed control and on-ramp metering, which attempts to improve the level of traffic operations on urban expressway. By analyzing traffic flow on urban expressway, an optimum control strategy of variable speed and on-ramp metering is established in the paper.

Design and implementation of a position sensorless control method for brushless DC motors

Because brushless direct current(BLDC) motors have the advantages of a compact size, high power density, high efficiency, and long operating life time, they are widely used in many industrial products and electric traction systems. It is known that the BLDC motors have no brushes for commutation. They are commutated with electronically commutation. So, the rotor position information of the BLDC motors must be known to understand which winding will be energized according to the energizing sequence. In most of the existing BLDC motor drivers, rotor position information is detected by Hall effect sensors. This kind of mechanical position sensors will bring additional connections and costs, reliability decrease and noise increase. In order to improve the control performance and extend the range of speed regulation for BLDC motors, a position sensorless control method is proposed in this paper. In the proposed control method, rotor position information of the BLDC motors is detected from the back electromagnetic forces(back-EMFs) which are estimated by an unknown-input observer with line to line currents and line to line voltages. For the purpose of verifying the effectiveness of the proposed control method, a model is built and simulated on the Matlab/Simulink platform. The simulation results show that the speed regulation performance of BLDC motors is improved compared with using Hall effect sensors. At the same time, the reliability of the BLDC motors is improved and the costs of them are reduced because the position sensor is eliminated.

PMSM speed control using adaptive sliding mode control based on an extended state observer

In this study,a composite strategy based on sliding-mode control( SMC) is employed in a permanent-magnet synchronous motor vector control system to improve the system robustness performance against parameter variations and load disturbances. To handle the intrinsic chattering of SMC,an adaptive law and an extended state observer( ESO) are utilized in the speed SMC controller design. The adaptive law is used to estimate the internal parameter variations and compensate for the disturbances caused by model uncertainty. In addition,the ESO is introduced to estimate the load disturbance in real time. The estimated value is used as a feed-forward compensator for the speed adaptive sliding-mode controller to further increase the system's ability to resist disturbances. The proposed composite method,which combines adaptive SMC( ASMC) and ESO,is compared with PI control and ASMC. Both the simulation and experimental results demonstrate that the proposed method alleviates the chattering of SMC systems and improves the dynamic response and robustness of the speed control system against disturbances.

基于粒子群算法的电机控制策略研究

针对电机速度控制存在的响应慢、精度差等问题,采用PSO优化PID控制器参数实现对无刷直流电机的速度控制。构建了直流电机的数学模型与控制模型,在此基础上提出了PSO优化PID参数的流程。在MATLAB/Simulink平台下搭建无刷直流电机控制系统仿真模型,对比传统PID控制、GA优化PID参数控制、PSO优化PID参数控制3种电机控制策略在电机空载工况、转速发生阶跃变化工况、电机负载发生阶跃工况下的仿真结果。结果表明,PSO优化PID参数控制相对于其它两种控制策略,其转速响应速度快、抗负载干扰能力强。

基于径向基函数神经网络算法的高频转阀阀芯稳定性

针对伺服电机驱动高频转阀时受液动力矩变化影响造成高频输出精度下降的问题,以液压马达作为动力源,提出一种基于径向基函数神经网络算法的转阀阀芯转速控制策略。首先,搭建高频转阀阀芯转速控制系统的数学模型;其次根据数学模型在MATLAB/Simulink平台搭建仿真模型,对不同算法作用下阀芯转速控制特性进行仿真分析;最后建立高频转阀转速控制系统实验台,对不同算法作用下阀芯转速控制特性进行实验研究和理论验证。结果表明:与常规PID控制方法相比,基于径向基函数神经网络的高频转阀转速控制策略转速控制系统阶跃响应所需调整时间最少为0.16 s,超调量小;三角波与正弦波转速跟踪误差均值下降最大值分别为46.51%、53.69%;6 MPa、10 MPa下,转速稳态误差均值分别下降34.92%、38.26%。径向基函数神经网络算法有效提高了高频转阀阀芯转速控制精度。

永磁同步电机非线性增益非奇异快速终端滑模控制

为了研究传统滑模控制中系统误差在有限时间内无法收敛至0以及传统滑模控制中系统抖振与收敛速度互不兼容的问题,提出一种非奇异快速终端滑模控制与扰动观测器结合的速度控制器。通过将参数可变的非线性函数作为增益代替固定增益加入滑模控制策略中从而改善系统响应速度同时减小系统的抖振。针对转矩扰动对系统的影响,加入负载转矩扰动观测器并补偿到q轴电流中以进一步提高控制器抗负载扰动能力。根据李雅普诺夫稳定性理论对提出的新型滑模控制器进行稳定性证明,经过仿真和实验证明,电机在启动时响应快、无超调且抖振较小,在突加转矩时转速波动小且恢复时间迅速,证明了改进后的变增益非奇异终端滑模控制与传统非奇异快速终端滑模控制策略相比可以提高动态性能的同时抑制系统抖振、增强系统的鲁棒性。

水稻精量施肥喷药同步机插控制系统的设计与试验

研究了一种水稻精量侧深施肥、喷药除草同步机插控制系统,以单片机STM32为控制核心硬件,基于FreeRTOS多线程任务,获取插秧机的作业速度,根据插秧施肥、喷药除草的农艺措施要求,确定同步作业数据模型,控制螺旋施肥电机和喷药泵电机的转速,实现施肥量和喷药量与插秧的实时调控,同时开展了不同作业速度、施肥和喷药量条件下的控制系统静态试验。结果表明:各行排肥量稳定性变异系数为1.94%~6.46%,总排肥量稳定性变异系数为3.34%~5.27%,各行喷药量稳定性变异系数为5.21%~7.63%,控制系统性能稳定;田间试验结果表明,施肥准确率为97.61%,喷药准确率为94.47%,能够满足水稻精量侧深施肥和喷药除草同步机插的技术要求;与常规机插种植相比,作业35 d后的杂草防效均在98.00%以上;在减少20%氮肥量、50%除草剂的情况下,能确保水稻产量,提高水稻种植效益。