基于递归型小波神经网络的感应电动机伺服驱动系统自适应控制

针对感应电动机伺服驱动系统具有的多变、强耦合、慢时变等非线性特性和不确定性扰动,传统的位置速 度PID控制策略不能保证轨迹跟踪的精度和良好的动态品质的问题;保证系统对系统内部参数波动和外界不确定 性扰动具有较好的鲁棒性,在矢量控制策略的基础上,提出了基于递归型小波神经网络的自适应控制方案。神经 网络参数的在线学习机制采用delta自适应律并结合了BP算法和梯度下降法,算法简单,计算量大大减少。仿真 的结果验证了方案的有效性。     

Fuzzy-PID多模态控制器在永磁同步电机中的应用

传统的永磁同步电机矢量控制系统采用比例积分（PI）速度控制器,其动态响应性能比较差。针对这一问题,设计了一种基于Fuzzy—PID的多模态自适应控制器,作为永磁同步电机矢量调控系统的速度调节器。这种控制器可以利用模糊逻辑处理不确定信息,对速度控制器的输出进行实时校正。仿真结果表明：利用该控制器建立的矢量控制系统不仅结构简单,而且具有良好的动、静态特性。     

交流调速系统的模糊自校正PID控制

分析了异步电动机的变频调速原理,在利用矢量控制技术实现转矩和磁通解耦的基础上,增加模糊自校正PID算法实现了对速度的精确控制。通过MATLAB与传统PID速度控制算法进行仿真比较,证明了模糊自校正PID的控制性能要优越于传统PID的控制效果。     

Fault tolerant control for modified quadrotor via adaptive type-2 fuzzy backstepping subject to actuator faults

In this paper, a robust attitude and position control of a novel modified quadrotor unmanned aerial vehicles (UAV) which has higher drive capability as well as greater robustness against actuator faults than conventional quad-rotor UAV has been developed. A robust backstepping controller with adaptive interval type-2 fuzzy logic is proposed to control the attitude and position of the modified quadrotor under actuator faults. Besides globally stabilizing the system amid other disturbances, the insensitivity to the model errors and parametric uncertainties are the asset of the backstepping approach. The adaptive interval type-2 fuzzy logic as fault observer can effectively estimate the lumped faults without the knowledge of their bounds for the modified quadrotor UAV. Additionally, the type-2 fuzzy systems are utilized to approximate the local nonlinearities of each subsystem under actuator faults, next and in order to achieve the expected tracking performance, we used Lyapunov theory stability and convergence analysis to online adjust adaptive laws. As a result, the uniformly ultimate stability of the modified quadrotor system is proved. Finally, the performances of the proposed control method are evaluated by simulation and the results demonstrate the effectiveness of the proposed control strategy for the modified quadrotor in vertical flights in presence of actuator faults.     

基于模糊神经网络的超声电机位置控制

由于超声马达的时变和非线性。使其速度与位置的高精度控制成为难题。为了提高超声马达伺服系统的精度，把模糊逻辑控制应用到神经网络中，设计了模糊神经网络控制器．通过模糊逻辑部分获得专家知识．神经网络部分调整参数。通过改变超声电机的驱动频率来实现精确的位置控制。在控制系统中采用5层网络结构和误差反向传播算法，算法的收敛速度很快。通过实验和仿真验证了这种方法的可行性。     

采用模糊逻辑调节器的直接转矩控制感应电动机

介绍了基于直接转矩控制(DTC)的感应电机驱动器,并对其进行模糊逻辑控制仿真分析。直接转矩控制的感应电机使用的内置控制器为AC4的驱动模型,使用模糊逻辑控制的直接转矩控制系统产生的电磁转矩脉动纹波比传统的DTC少。     

Adaptive fuzzy approach for a class of uncertain nonlinear systems in strict-feedback form

Adaptive fuzzy control is proposed for a class of affine nonlinear systems in strict-feedback form with unknown nonlinearities. The unknown nonlinearities include two types of nonlinear functions: one satisfies the "triangularity condition" and can be directly approximated by fuzzy logic system, while the other is assumed to be partially known and consists of parametric uncertainties. Takagi-Sugeno type fuzzy approximators are used to approximate unknown system nonlinearities and the design procedure is a combination of adaptive backstepping and generalized small gain design techniques. It is proved that the proposed adaptive control scheme can guarantee the uniformly ultimately bounded (UBB) stability of the closed-loop systems. Simulation studies are shown to illustrate the effectiveness of the proposed approach.     

单定子三自由度超声电机位置控制的研究

介绍了单定子三自由度超声电机实现 3个自由度运动的原理 ,根据控制目标设计并实现了该超声电机的运动信号的检测结构 ,利用逐点比较法分解控制指令并采用模糊控制方法对电机进行了位置控制 ,取得了较好的结果 ,实验结果表明电机的输出轴在一定范围内能够精确地按照预定轨迹达到空间的任一位置     

异步电动机矢量控制系统中转速控制器的研究

针对异步电动机矢量控制中的转速控制器进行了研究,在异步电动机矢量控制系统中,将传统的转速PID控制器转换为模糊PID控制器,并利用Matlab/Simulink建立仿真模型,通过仿真实验验证了模糊PID控制具有减小转速超调量,提高稳态精度的优点.     

Novel fuzzy feedback linearization strategy for control via differential geometry approach

The study investigates a novel fuzzy feedback linearization strategy for control. The main contributions of this study are to construct a control strategy such that the resulting closed-loop system is valid for any initial condition with almost disturbance decoupling performance, and develop the feedback linearization design for some class of nonlinear control systems. The feedback linearization control guarantees the almost disturbance decoupling performance and the uniform ultimate bounded stability of the tracking error system. Once the tracking errors are driven to touch the global final attractor with the desired radius, the fuzzy logic control is immediately applied via a human expert’s knowledge to improve the convergence rate. One example, which cannot be solved by the first paper on the almost disturbance decoupling problem, is proposed in this paper to exploit the fact that the almost disturbance decoupling and the convergence rate performances are easily achieved by the proposed approach.     

基于模糊神经网络系统的三相感应电机矢量控制

为实现三相感应电机稳定控制,提出了一种基于自适应模糊神经网络推理系统（ANFIS）的感应电机矢量控制方法。ANFIS结合了模糊逻辑的调节能力与神经网络的自适应能力,被广泛的应用到电机的参数估计、转速、转矩和磁链控制中。在分析感应电机工作原理的基础上,推导出其数学模型,在Matlab/Simulink上采用基于ANFIS的矢量控制对三相感应电机进行系统仿真,仿真结果表明,该控制策略转矩波动小,转速响应快,具有良好的动态和静态性能。     

多参数变化下基于参数辨识的永磁同步 电机偏差解耦控制方法

针对矢量控制下永磁同步电机d-q轴电流无法动态解耦,导致电机参数的动态变化影响其控制系统稳定性问题,提出一种基于参数辨识的永磁同步电机偏差解耦控制(PI-DDC)方法。以d-q轴电流控制器耦合系数为零推导完全解耦下偏差解耦项的传递函数,由此考虑电阻、电感和永磁体磁链等电机参数的动态变化对偏差解耦效果的影响,引入带遗忘因子递推最小二乘法在线辨识电机各参数,通过实时修正偏差解耦控制模型中的电机参数实现d-q轴电流解耦。以一台永磁同步电机为例,不同工况下的仿真和实验结果表明,所提的PI-DDC方法相比于传统偏差解耦控制方法,d-q轴电流响应时间缩短约50%,超调量分别减小约60%和70%,最大波动幅值分别减小约30%和37%,具有更好的控制精度和动态性能。     

交流电机矢量控制调速系统的仿真研究

根据异步电机矢量变换控制原理,利用Simulink和电力系统工具箱（Sire Power Systems）构造了转速闭环、磁链开环的间接矢量连续控制系统的仿真模型,介绍了转速和电流调节器参数的整定过程,对系统在外加扰动及参数变化下进行了仿真。仿真结果验证了该建模方法的有效性和正确性,为高效的交流调速系统的开发与设计提供了一种实现方法。     

Nonlinear robust control of hypersonic aircrafts with interactions between flight dynamics and propulsion systems

This paper addresses the nonlinear robust tracking controller design problem for hypersonic vehicles. This problem is challenging due to strong coupling between the aerodynamics and the propulsion system, and the uncertainties involved in the vehicle dynamics including parametric uncertainties, unmodeled model uncertainties, and external disturbances. By utilizing the feedback linearization technique, a linear tracking error system is established with prescribed references. For the linear model, a robust controller is proposed based on the signal compensation theory to guarantee that the tracking error dynamics is robustly stable. Numerical simulation results are given to show the advantages of the proposed nonlinear robust control method, compared to the robust loop-shaping control approach.     

非线性机械系统的模糊保代价控制

研究了具有不确定参数的非线性机械系统的稳定模糊保代价控制问题。采用T-S模糊模型描述非线性机械系统，对具有范数有界、时变参数不确定性的机械系统，得到了存在稳定模糊保代价控制器的充分条件，推算出了相应的线性矩阵不等式(LMI)形式。在非线性质量-弹簧-阻尼机械系统中的应用，验证了算法的有效性。     

交流变频调速系统中的自适应模糊控制研究

针对交流电动机矢量控制系统因电机参数变化和负载波动等因素性能变差的问题,设计了一种二维自适应模糊控制器作为交流电动机矢量控制系统的速度调节器,并由电压空间矢量脉宽调制(SVPWM)逆变器作为电动机的供电电源来实现变频调速。仿真实验表明,系统不仅动态和态性能都得到提高,而且具有良好的鲁棒性。     

Research on the effects of coordinate deformation on radial-axial ring rolling process by FE simulation based on in-process control

The boundary layer approach is the most popular method to reduce the chattering phenomenon in sliding mode control (SMC) for uncertain nonlinear systems. This paper applies the fuzzy sliding mode structure based on the boundary layer theory which is used as speed controller of an indirect field-oriented control (IFOC) of an induction motor (IM) drive. A fuzzy inference system is assigned for reaching the controller part of the fuzzy sliding mode controller (FSMC) to eliminate the chattering phenomenon in spite of the small and large uncertainties in the system. The applied fuzzy system acts like a saturation function technique in a thin boundary layer near the sliding surface so that the stability of the system is guaranteed. Also, the equivalent control part is estimated to avoid the computational burden by an averaging filter. On the other hand, the averaging filter assists to improve the tracking performance despite the possibility of large uncertainties in the system so that the stability of the system is guaranteed. The main advantages of the proposed chattering-free speed controller are robustness to parameter variations and external load disturbance. The simulation results are shown to verify the effectiveness of the proposed speed controller, and its advantages are shown in comparison with the FSMC system and the conventional SMC.     

基于背靠背PWM矿井提升机变频调速系统设计

针对我国大部分矿井提升机调速系统效率低、成本高、体积大、能源浪费的现状,有必要对其调速方案进行改造.该文设计了PWM整流器和异步电机的解耦矢量控制系统,进而搭建了背靠背PWM变频调速系统,并对该系统进行了仿真分析.仿真结果表明,该系统动、静态性能良好,实现了网侧单位功率因数和能量的双向流动,验证了此调速系统设计的有效性...     

Design of interval type-2 fuzzy precompensated PID controller applied to two-DOF robotic manipulator with variable payload

The interval type-2 fuzzy logic controller (IT2-FLC), with footprint of uncertainty (FOU) in membership functions (MF), has increasingly recognized for controlling uncertainties and nonlinearities. Within the ambit of this, the efficient interval type-2 fuzzy precompensated PID (IT2FP-PID) controller is designed for trajectory tracking of 2-DOF robotic manipulator with variable payload. A systematic strategy for optimizing the controller parameters along with scaling factors and the antecedent MF parameters for minimization of performance metric integral time absolute error (ITAE) is presented. Prominently, recently proposed optimization technique hybridizing grey wolf optimizer and artificial bee colony algorithm (GWO–ABC) is utilized for solving this high-dimensional constrained optimization problem. In order to witness effectiveness, the performance is compared with type-1 fuzzy precompensated PID (T1FP-PID), fuzzy PID (FPID), and conventional PID controllers. More significantly, the robustness of IT2FP-PID is examined for payload variation, model uncertainties, external disturbance, and noise cancellation. After experimental outcome, it is inferred that IT2FP-PID controller outperforms others and can be referred as a viable alternative for controlling nonlinear complex systems with higher uncertainties.     

Fuzzy control of multivariable process by modified error decoupling

In this paper, a control concept for the squared (equal number of inputs and outputs) multivariable process systems is given. The proposed control system consists of two parts, single loop fuzzy controllers in each loop and a centralized decoupling unit. The fuzzy control system uses feedback control to minimize the error in the loop and the decoupler uses an adaptive technique to mitigate loop interactions. The decoupler predicts the interacting loop changes and modifies the input (error) of the loop controller. The controller was tested on the simulation model of "single component vaporizer" process. The results indicate that the decoupling controller shows better performance for set point and load changes.