Decoupling and tracking control of induction motor drive

This work introduces an adaptive observation system and a robust control system for achieving the favorable decoupling control and high-precision speed tracking property of an induction motor (IM) drive system. First, an adaptive observation system with an inverse rotor time-constant observer is derived on the basis of model reference adaptive system (MRAS) theory to preserve the decoupling control characteristic of an indirect field-oriented IM drive. The adaptive observation system is implemented using a digital signal processor (DSP) with a high sampling rate to make it possible to achieve good dynamics. Moreover, a robust control system is developed based on the principle of computed torque control. In the robust control system, a grey uncertainty predictor is utilized to adapt the lumped uncertainty on line to relax the requirement of the lumped uncertainty in the design of a computed torque speed controller. In addition, the effectiveness of the proposed observation and control systems is verified by simulated and experimental results.     

基于逆动力学的柔性连杆机械臂的混合模糊控制

利用假设模态法建立了柔性连杆机械臂的逆动力学方程,提出了一种并行于常规开环逆动力学控制的混合模糊控制方法对其进行末端轨迹跟踪。设计的控制器由两部分组成,一部分为根据结构的逆动力学以及机械臂末端所需跟踪的轨迹计算出控制力;另一部分为通过末端位置的实测与给定轨迹的偏差,利用一个辅助模糊控制对控制量进行调整,构成输出反馈部分。通过数字仿真,并与常规模糊控制结果的比较,表明借助于结构逆动力学,可以降低模糊控制器对知识库的需求,获得较好的控制稳态性能。     

基于RVM回归误差补偿的航空发动机分布式控制系统多步预测控制

针对具有随机有界双侧时延的航空发动机分布式控制系统,提出了一种基于多步预测和关联向量机(RVM)回归误差补偿的控制方案.首先建立航空发动机分布式控制系统(DCS)的神经网络非线性自回归滑动平均(NARMA)模型,利用当前的系统输出和控制量对N步之后的系统输出进行预测;其次用改进的RVM回归多步预测算法估计NARMA模型的的预测误差,并对预测结果进行误差补偿;最后利用补偿之后的预测值和设定值对控制参数进行滚动优化,设计系统的神经网络逆控制器实现系统的自适应控制.仿真结果证明该控制策略能够避免随机有界双侧时延对控制系统的影响,实现对设定值的稳定跟踪,且控制器具有较好的实时性和鲁棒性.低压转子转速阶跃响应的稳态绝对误差小于0.04%,响应时间小于0.3s.      

基于目标状态方程的SRM非线性预测控制

提出了一种基于目标状态方程的开关磁阻电机非线性预测控制方法,根据建立开关磁阻电机的非线性数学模型,按照非线性控制理论,定义转矩偏差和速度偏差为目标状态方程。以此状态方程为基础,结合预测控制理论对开关磁阻电机控制系统进行非线性预测控制设计,得到了以转速和转矩为反馈变量的非线性预测控制规律。根据所设计的控制器,通过软件仿真进行了验证。仿真结果表明,采用基于目标状态方程的开关磁阻电机非线性预测控制方法设计的SRM控制系统具有良好的动态和静态性能,对抑制开关磁阻电机转矩脉动有很好的效果。     

On-line gain-tuning IP controller using RFNN

In this study an integral-proportional (IP) controller with on-line gain-tuning using a recurrent fuzzy neural network (RFNN) is proposed to control the mover position of a permanent magnet linear synchronous motor (PMLSM) servo drive system. The structure and operating principle of the PMLSM are first described in detail. A field-oriented control PMLSM servo drive is then introduced. After that, an IP controller with on-line gain tuning using an RFNN is proposed to control the mover of the PMLSM for achieving high-precision position control with robustness. The backpropagation algorithm is used to train the RFNN on line. Moreover to guarantee the convergence of tracking error for the periodic step-command tracking, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RFNN. Furthermore, the proposed control system is implemented in a PC-based computer control system, Finally, the effectiveness of the proposed PMLSM servo drive system is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line learning capability of the RFNN. In addition, the proposed on-line gain-tuning servo drive system is robust with regard to parameter variations and external disturbances     

Sensorless synchronous reluctance drive with standstill starting

This paper presents a novel sensorless synchronous reluctance drive system. Based on the dynamic model of the synchronous reluctance motor (SRM), a new rotor position estimator is proposed. This estimator is only related to the rate change of the stator currents. It is not related to the parameters, speed, voltage, and external load of the motor. As a result, the estimator is simple and robust. Based on the proposed estimator, a sensorless synchronous reluctance drive has been implemented. This drive system can start from standstill and accelerate to a rated speed; the traditional open-loop starting method, therefore, is unnecessary. A digital signal processor, TMS-320-C30, is used to implement the estimating and control algorithms. Experimental results show that the proposed system works well. The adjustable speed range can be from 1 r/min to 1800 r/min. Moreover, by adding the position-loop controller the proposed system can perform as a position control drive as well. Several experimental results validate the theoretical analysis.     

Nonlinear controller design for switched reluctance drive systems

A nonlinear speed-loop controller for a switched reluctance motor (SRM) drive system is proposed. The details of the controller design and analysis are discussed. In addition, to extend the controllable speed range, the commutating angle of the drive system is suitably adjusted as the motor speed goes beyond base-speed. By using a 32-bit microprocessor, a fully digital drive system including a digital speed-loop controller and a digital current-loop controller is implemented here. The hardware circuit of the drive system is very simple. The system has satisfactory performance in both the pulsewidth modulated (PWM) region and the single pulse region. The adjustable speed range of the system is from 10 r/min to 3000 r/min. In addition, the proposed drive system performs well in tracking ability, load disturbance rejection capability, and robustness. Several experimental results are presented to validate the theoretic analysis.     

Design and implementation for a digital synchronous reluctancedrive

A systematic controller design for a synchronous reluctance drive system is presented. This controller consists of two parts: a forward-loop H^∞ controller to improve the transient response, and a load compensator to reduce the load disturbance. Based on a simplified model of the drive system, a control algorithm has been derived. Detailed analysis of the characteristics of the closed-loop system is presented. The effects of the parameter variations are also studied. A digital signal processor, TMS-320-C30, is used to implement the control algorithm. Both the speed control and the position control of the drive system can be implemented by using the proposed control method. Furthermore, all the control loops are executed by the digital signal processor. The system, as a result, is very flexible. The whole drive system performs well although its hardware is very simple. For speed control, the system can be operated at a speed as low as 1 r/min. For position control, the system can accurately control a one-axis table. In addition, the system also has good position tracking ability. Several experimental waveforms validate the simulated results     

变旋翼转速飞行控制对涡轴发动机输出响应的影响

为探明变旋翼转速条件下飞行控制对涡轴发动机输出响应的影响,在变旋翼转速直升机/传动机构/发动机综合仿真平台的基础上,考虑系统不确定因素的存在,提出并设计了增量式非线性动态逆飞行控制器,提高对系统的控制效果,控制器主要包括角速率控制器、姿态角控制器和航迹控制器;由于执行机构的物理限制,引入伪控制模块,以提高系统的稳定性。典型的飞行任务下的仿真结果表明：相对于增量式非线性动态逆飞行控制器而言,伪控制模块不仅可显著提升飞行控制效果,使爬升速度的超调量减小50%以上,还可有效减小动力涡轮转速的超调量9.0%左右,有助于增强发动机的动态控制品质。     

飞机纵向非线性系统的鲁棒输出跟踪控制器设计

研究了单输入单输出非线性不确定系统的鲁棒输出跟踪控制。在标称系统可输入/输出线性化、不确定性项有界且满足广义匹配条件的情况下,可得到系统的高增益鲁棒输出跟踪控制器。鲁棒控制器仅依赖于设计参数和不确定性的界。将该方法应用于飞机纵向高阶非线性动态的控制器设计,并进行了数字仿真。结果表明了该方法的有效性。     

基于神经网络逆控制的发动机直接推力控制

首次将动态神经网络逆控制用于航空发动机直接推力控制。为了有效消除由于神经网络逆模型构造误差(即神经网络逆模型不可能完全逼近航空发动机的逆模型)而产生的稳态误差和解决航空发动机推力不易测量的困难,分别设计了积分补偿器和推力估计器,从而实现航空发动机直接推力控制。飞行包线内数字仿真结果表明,此控制方案具有良好的动静态性能、精度高、跟踪快。     

Design and implementation of a robust controller for a synchronousreluctance drive

A robust controller design for a synchronous reluctance drive system is presented. Based on a simplified model of the system, a robust position controller has been derived. A digital signal processor (DSP), TNO-320-C30, is used to implement the control algorithm. Furthermore, all the current, velocity, and position control loops are executed by the DSP. The system, as a result, is very flexible. Although the hardware circuit of the system is very simple, the synchronous reluctance drive system can accurately control a one-axis table. In addition, the system also has good transient response, load disturbance response, and tracking ability. Several experimental results validate the theoretical analysis     

MIMO随机振动试验控制的逆多步预测模型法

多输入多输出（MIMO）随机振动试验在产品可靠性验证中扮演重要角色。逆系统方法作为一种时域方法，直接由参考信号（即期望得到的响应信号）生成驱动信号，但容易产生不稳定的结果。本文以系统的有限差分模型为基础，推导了逆多步预测模型，并建立了该逆模型与矩阵幂次算法结合的MIMO随机振动试验方法。通过悬臂梁模型进行双输入双输出仿真试验，验证了逆多步预测模型进行MIMO随机振动试验驱动生成的可行性。在三轴振动台上进一步验证该方法进行MIMO随机振动试验控制的能力。     

基于改进型趋近律与负载观测器的永磁同步电机滑模速度控制器设计

为了提高三相永磁同步电机(PMSM)调速系统的动态品质,改善传统滑模速度控制器的控制性能,抑制系统抖振,提高控制精度,设计了基于新型趋近律与负载观测器的改进型滑模速度控制器。利用MATLAB/Simulink仿真软件,搭建控制系统模型并进行仿真分析。仿真验证了所设计的改进型PMSM速度控制器的有效性。该控制器可获得较好的速度跟踪精度和抗负载扰动能力,提高系统的稳定性和鲁棒性。     

电动车开关磁阻电机驱动和保护控制策略研究

传统开关磁阻电机(SRM)起动时采用电流斩波控制(CCC),中高速阶段采用角度位置控制(APC)对转速进行调节。但在电动车领域的SRM驱动控制中,通常采用基于脉宽调制(PWM)控制的方式来实现电机的开环调速。在传统SRM控制方式的基础上,提出了一种动态斩波的起动方式以及一种PWM控制与APC控制相结合的中高速运行的综合控制策略,可确保电机在不同负载下平稳起动、瞬间提速和稳定运行。与此同时,对控制器保护环节中最为关键的过流保护和堵转保护进行了设计,提升了整个驱动系统的可靠性。为了验证所提驱动控制策略和保护方法的可行性,在以STM32F103处理器为控制核心的控制器和1台12/8结构电动车SRM上进行了系统的试验。试验结果表明在该控制算法下,电机能够快速起动和稳定运行,且能检测到故障并及时保护,证明了该算法的正确性。     

Attitude tracking control for variable structure near space vehicles based on switched nonlinear systems

An adaptive robust attitude tracking control law based on switched nonlinear systems is presented for a variable structure near space vehicle (VSNSV) in the presence of uncertainties and disturbances. The adaptive fuzzy systems are employed for approximating unknown functions in the flight dynamic model and their parameters are updated online. To improve the flight robust performance, robust controllers with adaptive gains are designed to compensate for the approximation errors and thus they have less design conservation. Moreover, a systematic procedure is developed for the synthesis of adaptive fuzzy dynamic surface control (DSC) approach. According to the common Lyapunov function theory, it is proved that all signals of the closed-loop system are uniformly ultimately bounded by the continuous controller. The simulation results demonstrate the effectiveness and robustness of the proposed control scheme.     

过失速机动飞机的鲁棒非线性控制律设计

 采用非线性动态逆和结构奇异值综合方法设计了过失速飞行条件下飞控系统控制律,解决了飞控设计中面临的非线性和鲁棒性问题。应用非线性动态逆的目的就是对过失速机动飞行条件下高度非线性的飞机动力学进行线化;从而围绕线性的快逆回路应用结构奇异值综合方法设计相应的鲁棒控制器,以提供对驾驶员指令的鲁棒跟踪。所设计的飞控系统将达到期望的飞行品质,确保系统对过失速机动飞行过程中因非定常气动力效应引起的系统参数摄动鲁棒性良好。高逼真度、非线性的仿真验证了这一点。     

基于多模型切换的鲁棒自适应控制器

系统参数发生跳变时,为了解决多变量系统暂态响应变差的问题,提出一种基于多模型切换的鲁棒自适应控制器。该控制器由多个鲁棒自适应控制器组成,鲁棒自适应控制器保证系统存在未建模动态时能够使自适应系统稳定运行,引入的多模型策略保证系统参数跳变时具有良好的暂态性能。仿真结果表明,所提出的多模型鲁棒自适应控制器能够加快系统的响应速度,提高系统的暂态性能。     

火箭弹电动舵机模糊单神经元PID控制算法

针对制导火箭弹电动式舵机,为提高其响应速度和精度,文章在模糊PID控制基础上,提出了模糊单神经元PID控制方法。首先,建立了火箭弹舵机系统模型;然后,将模糊推理、单神经元自学习算法和PID控制相结合,建立智能控制系统,以实现对舵机输入指令的精确、快速响应。经仿真实验表明:在此智能控制下,舵机位置在阶跃响应的调节时间、超调量以及正弦跟踪上相对于传统模糊PID控制均得到有效改进,具有良好的动静态性能、自适应性和稳定性。