基于永磁同步电机的LPV转速观测器设计

针对提高永磁同步电机无位置传感器速度跟踪控制精度问题,提出了一种基于线性变参数(Linear Parameter Varying,LPV)转速观测器设计方法。该方法借助状态估计实现对旋转坐标系下定子电流、转子角转速等状态的重构。首先根据LPV电机模型,推导出观测器的LPV状态模型方程,然后根据Lyapunov稳定性理论,获得闭环系统的稳定性条件,再利用奇异值分解方法,将Lyapunov稳定性条件转化为线性矩阵不等式条件,通过求解不同凸胞形顶点处的观测器增益矩阵,最终合成反馈增益,实现对电机的高精度的速度跟踪控制。仿真结果表明,该观测器能够快速准确的跟踪上电机转速。     

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.为了提升转矩控制精度,基于异步电机的数学模型,采用模型预测转矩控制理论,以转矩和定子磁链为控制目标设计评价函数,得到最优输出电压矢量驱动电机运行.仿真结果表明,所提出的控制方法能有效提升系统对负载扰动的鲁棒性,并有效降低转矩波动,使电机具有良好的动态和静态运行性能.     

基于LPV观测器的永磁同步电机反推控制

针对永磁同步电机(Permanent Magnet Synchronous Motor,PMSM)无速度传感器转速跟踪控制精度问题,提出了一种基于线性变参数(Lineeo Parameteo Varying,LPV)转速观测器的永磁同步电机反推控制方法。该方法首先根据PMSM的LPV模型,推导出电机的凸胞形顶点方程;然后利用Lyapunov稳定性理论,获得了基于线性矩阵不等式(Lineeo Matrix Inequality,LMI)的观测器设计方法,构造了PMSM的LPV观测器,实现对电机转速及定子交轴电流的重构;最后运用反推控制策略,设计电机闭环系统控制器,实现对电机转速的高精度跟踪控制。仿真结果表明,该方法相较与传统PI矢量控制,跟踪精度高、响应快、抗负载扰动强,对实现PMSM的无速度传感器高精度转速跟踪控制具有重要意义。     

Torque tracking control of electric load simulator with active motion disturbance and nonlinearity based on T‐S fuzzy model

This paper develops a high performance nonlinear control method for an electric load simulator (ELS). The tracking performance of the ELS is mainly affected by the actuator's active motion disturbance and friction nonlinearity. First, a nonlinear model of ELS is developed, and then the Takagi‐Sugeno fuzzy model is used to represent the friction nonlinearity ofthe ELS. A state observer is constructed to estimate the speed of the load system. For converting the tracking control into a stabilization problem, a new control design called virtual desired state synthesis is proposed to define the internal desired states. External disturbances are attenuated based on an H_∞ criterion and the stability of the entire closed‐loop model is investigated using the well‐known quadratic Lyapunov function. Meanwhile, the feedback gains and the observer gains are obtained separately by solving a set of linear matrix inequalities (LMIs). Both a simulation and experiment were performed to validate the effectiveness of the developed algorithm.     

A Parameter Dependent Controller Design Approach for Delayed LPV System

This paper investigates the memory state feedback controller synthesis problem for linear parameter‐varying (LPV) systems with time‐varying input delay. A novel state transformation is proposed to reduce the influence of time delay, and two types of Lyapunov‐Krasovskii functional are employed to guarantee the stability of the closed‐loop system and induced L₂ norm performance. The controller gain is formulated to parameter dependent, and design method is then led to a convex optimization problem and solved by parameter gridding technique. A numerical example is provided to validate the effectiveness of the proposed approach.     

An improved robust model predictive control for linear parameter‐varying input‐output models

This paper describes a new robust model predictive control (MPC) scheme to control the discrete‐time linear parameter‐varying input‐output models subject to input and output constraints. Closed‐loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal set, which are solved offline, for the underlying online MPC optimization problem. The main attractive feature of the proposed scheme in comparison with previously published results is that all offline computations are now based on the convex optimization problem, which significantly reduces conservatism and computational complexity. Moreover, the proposed scheme can handle a wider class of linear parameter‐varying input‐output models than those considered by previous schemes without increasing the complexity. For an illustration, the predictive control of a continuously stirred tank reactor is provided with the proposed method.     

Adaptive Nonlinear Control of Induction Motors Through AC/DC/AC Converters

The problem of controlling induction motors, together with associated AC/DC rectifiers and DC/AC inverters, is addressed. The control objectives are threefold: (i) the motor speed should track any reference signal despite mechanical parameter uncertainties and variations; (ii) the DC Link voltage must be tightly regulated; and (iii) the power factor correction (PFC) w.r.t. the power supply net must be performed in a satisfactory way. First, a nonlinear model of the whole controlled system is developed within the Park coordinates. Then, a multi‐loop nonlinear adaptive controller is synthesized using the backstepping design technique. A formal analysis based on Lyapunov stability and average theory is carried out to exhibit the control system performances. In addition to closed‐loop global asymptotic stability, it is proven that all control objectives (motor speed tracking, rotor flux regulation, DC link voltage regulation and unitary power factor) are asymptotically achieved, up to small but unavoidable harmonic errors (ripples).     

A scheduling quasi–min-max model predictive control algorithm for nonlinear systems

In this paper, a model predictive control algorithm is designed for nonlinear systems. Combination of a linear model with a linear parameter varying model approximates the nonlinear behavior. The linear model is used to express the current nonlinear dynamics, and the linear parameter varying model is used to cover the future nonlinear behavior. In the algorithm, a “quasi-worst-case” value of an infinite horizon objective function is minimized. Closed-loop stability is guaranteed when the algorithm is implemented in a receding horizon fashion by including a Lyapunov constraint in the formulation. The proposed approach is applied to control a jacketed styrene polymerization reactor.     

Multiple Lyapunov Functions with Blending for Induced L2‐norm Control of Switched LPV Systems and its Application to an F‐16 Aircraft Model

This paper studies the induced L₂‐norm problem for switched linear parameter varying (LPV) systems using a blending method. For a switched LPV system where the parameters are grouped into slow‐varying and fast‐varying parameters, the blending method is used to construct blended Lyapunov functions based on the multiple Lyapunov functions conditions in terms of linear matrix inequalities (LMIs). The proposed method is applied to an F‐16 aircraft longitudinal model and the simulation results demonstrate the effectiveness of the approach.     

Backstepping Control of Speed Sensorless Permanent Magnet Synchronous Motor Based on Slide Model Observer

This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor(PMSM) in d-q frame and its space-state equation are established. The slide model control method is used to estimate the electromotive force of PMSM under static frame, while the position of rotor and its actual speed are estimated by using phase loop lock(PLL) method. Next,using Lyapunov stability theorem, the asymptotical stability condition of the slide model observer is presented. Furthermore, based on the backstepping control theory, the PMSM rotor speed and current tracking backstepping controllers are designed, because such controllers display excellent speed tracking and anti-disturbance performance. Finally, Matlab simulation results show that the slide model observer can not only estimate the rotor position and speed of the PMSM accurately, but also ensure the asymptotical stability of the system and effective adjustment of rotor speed and current.     

Robust control of synchronous motor through AC/DC/AC converters

The problem of controlling synchronous motors, driven through AC/DC rectifiers and DC/AC inverters is addressed. The control objectives are threefold: (i) forcing the motor speed to track a varying reference signal in presence of motor parameter uncertainties; (ii) regulating the DC Link voltage; (iii) assuring a satisfactory power factor correction (PFC) with respect to the power supply net. First, a nonlinear model of the whole controlled system is developed in the Park-coordinates. Then, a robust nonlinear controller is synthesized using the damping function version of the backstepping design technique. A formal analysis based on Lyapunov stability and average theory is developed to describe the control system performances. Despite parameter uncertainties, all control objectives are proved to be asymptotically achieved up to unavoidable but small harmonic errors (ripples).     

无速度传感器电励磁同步电机模型预测电流控制

为了提高电励磁同步电机控制系统的可靠性,优化电励磁同步电机的调速性能,提出了一种带无速度传感器的电励磁同步电机模型预测电流控制策略.以模型预测电流控制作为电流环,取代传统的PI调节器,有效抑制电流纹波,提高了电流的跟踪性能.基于模型参考自适应理论,设计电励磁同步电机无速度传感器,对电机运行转速进行在线辨识,实现对转速准确估计.仿真结果表明:控制系统具有较好的快速性和可靠性.     

基于滑模观测器的直线伺服系统反馈线性化速度跟踪控制

在许多高速、高精的直线伺服系统中,要求能实现对速度的快速精确跟踪,但其模型的非线性和变量间的耦合给控制带来难度.对高速、高精速度跟踪控制中,电流和速度的变化过程在时间尺度上相对接近,不能简单地采用磁场定向矢量控制方法实现静态解耦,否则电流和速度间的非线性耦合将破坏速度跟踪品质.采用状态反馈线性化方法来实现永磁直线同步电动机(PMLSM)模型的精确线性化和动态解耦.利用非线性坐标变换和非线性反馈将系统解耦成独立的线性电流子系统和速度子系统.通过扩展滑模观测器来实现对所需要的动子速度、加速度和负载扰动的鲁棒观测.并利用李雅普诺夫理论对由反馈线性化和滑模观测器构成的非线性闭环系统的稳定性进行了证明.仿真结果表明该方案使PMLSM伺服系统具有良好的鲁棒速度跟踪性能.     

ON STABILITY AND PERFORMANCE OF INDUCTION MOTOR SPEED DRIVES WITH SLIDING MODE CURRENT CONTROL

A novel inner loop sliding mode current control scheme for induction motor speed drives is proposed in this paper. The controller design is based on the nonlinear mathematical model of an induction motor in a coordinate system oriented along the rotor flux. The parameters of the PI speed controller are taken into consideration in the inner loop sliding mode current control. Rigorous stability verification for the overall system is provided in this paper. The chattering in sliding mode control is attenuated using the reaching law design method. The experimental results show that the proposed approach exhibits robust tracking performance in the presence of motor parameter variations and load disturbances.     

Stabilization of linear time varying systems over uncertain channels

In this paper, we study the problem of control of discrete‐time linear time varying systems over uncertain channels. The uncertainty in the channels is modeled as a stochastic random variable. We use exponential mean square stability of the closed‐loop system as a stability criterion. We show that fundamental limitations arise for the mean square exponential stabilization for the closed‐loop system expressed in terms of statistics of channel uncertainty and the positive Lyapunov exponent of the open‐loop uncontrolled system. Our results generalize the existing results known in the case of linear time invariant systems, where Lyapunov exponents are shown to emerge as the generalization of eigenvalues from linear time invariant systems to linear time varying systems. Simulation results are presented to verify the main results of this paper. Copyright © 2012 John Wiley & Sons, Ltd.     

基于重置算法的感应电机转速自适应观测器

常规并联双模型转速自适应观测器在电机启动、加速或突加负载时存在观测转速滞后性大、精度低的问题, 使得感应电机无速度传感器控制系统的调速性能变差. 针对上述问题, 提出一种重置自适应转速观测器对转子磁链进行观测, 同时通过自适应机构得到电机转速, 并利用Lyapunov 稳定性定理证明了系统的稳定性. 仿真和实验结果表明, 所提出的重置自适应观测器的观测误差小、稳定性好, 改善了在电机启动、加速或突加负载时的转速观测性能.

     

Adaptive Nonlinear Control of Wind Energy Conversion System Involving Induction Generator

This paper presents a theoretical framework for adaptive control of a wind energy conversion system (WECS), involving a squirrel cage induction generator (SIG) connected with an AC/DC/AC IGBT‐based PWM converter. A multi‐loop nonlinear controller is designed to meet two main control objectives, i.e., (i) speed reference optimization in order to extract a maximum wind energy whatever the wind speed, and (ii) power factor correction (PFC) to avoid net harmonic pollution. These objectives must be achieved despite the mechanical parameters uncertainty. First, a nonlinear model of the whole controlled system is developed within the Park coordinates. Then, a multi‐loop nonlinear controller is synthesized using the adaptive backstepping design. A formal analysis based on Lyapunov stability is carried out to describe the control system performances. In addition to closed‐loop global asymptotic stability, it is proven that all control objectives (induction generator speed tracking, rotor flux regulation, DC link voltage regulation and unitary power factor) are asymptotically achieved.     

Fuzzy approach-based optimal robust control for permanent magnet synchronous motor with experimental validation

This paper presents an optimal robust control for a permanent magnet synchronous motor (PMSM) with uncertainties and external disturbances which can be described by fuzzy approach. The fuzzy approach based on fuzzy set theory is distinguish from probability theory or fuzzy logic theory. Firstly, a dynamical model of the PMSM with uncertainties is established using a fuzzy approach. Then, a robust controller with an optimizable parameter is designed for PMSM to handle the uncertainties. The stability of the proposed control is proven using the Lyapunov theory. Furthermore, the controller gain is optimized by minimizing performance index, which contains the control performance and cost. Finally, the numerical simulations and experimental results are presented to validate the effectiveness of the proposed control with an optimal parameter.     

永磁同步电机自抗扰反步控制

为实现永磁同步电机的高性能控制,提出一种复合控制策略。在永磁同步电机矢量控制基础上,设计反步控制器用于电流环控制,得到同步旋转坐标系下定子电压,并能保证系统全局稳定。设计结构优化的线性自抗扰控制器用于速度环控制,提高系统抗干扰能力。采用二阶环节平滑速度指令,实现转速无超调。仿真结果表明该控制策略较传统PI控制具有转速适应范围广、无超调、抗扰动性能强等优点。     

智能RLED动态目标中机器手的模糊鲁棒控制系统

给出了一种电机驱动机器手中非线性机电模型的模糊鲁棒闭环控制系统,此控制系统可处理非结构环境下的三个主要的智能机器人导航问题：自动化规划、快速连续导航中的避障、处理结构和（或）非结构不确定性。