基于自适应滑模观测器无位置传感器PMSM控制方法研究

针对无位置传感器永磁同步电机控制存在的转子位置与转速估计精度不高的问题,结合自适应算法设计了一种新型的自适应滑模观测器。滑模自身机制引起的系统抖振问题是影响电机转子位置与转速估计的最大因素。为了降抖减振,采用连续的sigmoid阈值函数代替sign符号函数;提出一个反电动势自适应估计环节代替传统的低通滤波器,提高反电动势估计精度;此外为了降低转子位置及其转速的估计误差,采用锁相环对其进行估计。最后,基于200W的PMSM搭建实验平台对上述改进算法进行验证。结果表明:电机转子位置与转速估计稳态误差分别为0.129 rad、79 r/min,能够实现无位置传感器PMSM高精度控制。     

Distributed adaptive state estimation and tracking by using active-passive sensor networks

Heterogeneous sensor networks (HSN) find a wide range of applications in the field of military and civilian environments, where sensor nodes are utilized to estimate the position of a target with both dynamics and control input being unknown for the purposes of tracking. In the HSN, nodes are considered active depending upon their ability to sense the target output while the others are taken passive. Accurate estimation requires local information exchange among the spatially located sensor nodes, so that the active nodes as well as the passive nodes converge simultaneously to the same value. The local information exchange among the nodes is dictated by a connected graph. By using the criterion of collective observability, a novel distributed adaptive estimation scheme is introduced via adaptive observer where the nodes are allowed to have different sensor modalities. Using the estimated information, a subset of active and passive nodes, referred to as mobile nodes, can track the moving target. By using a constant state feedback controller at each mobile node, the state and parameter estimation as well as the tracking errors are shown to be uniformly ultimately bounded. Simulation results verify theoretical claims.     

Distributed data-driven observer for linear time invariant systems

This paper is concerned with distributed data-driven observer design problem. The existing data-driven observers rely on a common assumption that all the information about the system, and the calculations based upon this information are centralized. Therefore the resulting algorithms cannot be applied to the distributed systems in which each local observer receives only a part of the output signal. On the other hand, traditional model-based distributed state estimation methods generally assume that the processes are decomposed according to the known process models, while in data-driven approaches there is no such information available. The main goal of this paper is to extend the centralized data-driven observer design approach to the distributed framework. The stability of the proposed data-driven distributed observer is also proved analytically. A quadruple-tank process is simulated to demonstrate the performance of the proposed scheme.     

Novel fuzzy adaptive finite-time nonsmooth control for uncertain nonlinear systems

In this article, a novel fuzzy adaptive finite-time nonsmooth controller is developed to handle the finite-time tracking problem for a class of uncertain nonlinear systems. Different from traditional fuzzy adaptive approximation methods, proposed method contains only one adaptive parameter, no matter how many states there are in the system. By constructing a new Lyapunov function with prescribed performance bound, the transient and steady performances of control system can be ensured. Further, based on a criterion of finite-time semiglobal practical stability and backstepping technology, a novel fuzzy adaptive finite-time nonsmooth control method is designed. It can be demonstrated that proposed control can effectively ensure tracking error tends to small neighborhood in a finite time. Finally, two examples have been simulated by the proposed control method, and it shows effective tracking performance.     

Output feedback tracking control for rigid body attitude via immersion and invariance angular velocity observers

A novel immersion and invariance (I&I) angular velocity observer is presented for the attitude tracking control of a rigid body with the lack of angular rate. Global exponential convergence of angular velocity estimate errors are guaranteed by an innovative filter design for the estimates' Euclidean norm. The proposed method requires fewer filter states compared with existing I&I angular velocity observer designs, which achieves a simpler closed-loop structure (dynamic reduction). The observer synthesis and convergence are independent of the control torque, which leads to much convenience in establishing “separation property” when combining a proportional-derivative attitude tracking controller driven by angular velocity estimates. A rigorous stability analysis is provided to ensure the (almost) global asymptotic convergence of the overall closed-loop tracking errors, and several numerical simulations are carried out to demonstrate the effectiveness of the combined implementation of proposed angular velocity observer and full-state feedback attitude tracking controller.     

基于转矩补偿的永磁同步电机自抗扰控制研究

电动汽车永磁同步电动机( PMSM) 驱动系统运行在复杂多变的工况下,存在负载转矩扰动的问题。为减小负载转矩扰动引起的转速脉动,提高电动汽车抗干扰能力,提出了基于转矩前馈补偿的自抗扰控制(ADRC)策略。该控制方法使用自抗扰控制技术设计了速度控制器能实时补偿系统的扰动;并通过设计降维负载观测器来实时观测电机负载转矩变化,并将观测值反馈到电流环中,对负载扰动进行前馈补偿,增加了系统的抗干扰能力,提高了系统的鲁棒性。仿真结果表明,该方法可以增强系统的鲁棒性,提高系统的抗扰动能力。     

永磁同步电动机无位置传感器控制系统的一种算法研究

为了准确检测的位置信息,在分析永磁同步电动机数学模型的基础上,将滑模变结构控制应用于永磁同步电动机的控制系统.采用滑模状态观测器算法对电动机转子位置进行估算,从而实现了对无位置传感器型永磁同步电动机的转子磁场定向矢量控制.实验结果表明,滑模状态观测器算法对转子位置跟踪准确,系统具有较好的鲁棒性.     

高精确度伺服转台控制系统中的扰动力矩补偿

摩擦力矩和电机波动力矩是影响高精确度伺服转台控制系统位置跟踪精确度的主要因素。针对系统中摩擦力矩和电机波动力矩等扰动力矩补偿问题,提出一种综合的扰动力矩补偿控制策略。基于摩擦观测器提出一种PD前馈控制方法,对系统中的动态摩擦力矩进行了补偿,并利用Lyapunov稳定性理论对所提出的方法进行了系统稳定性分析。结合基于重复控制器的扰动观测器进一步提出一种综合的扰动力矩补偿控制策略。一方面,摩擦补偿方法可以对系统中的摩擦力矩进行补偿;另一方面,插入的重复控制器可以很好地抑制系统中的周期性波动力矩,而扰动观测器则用来补偿重复控制及摩擦补偿时给系统带来的不确定性。仿真结果证明了所提出的方法的有效性。     

应用自抗扰控制器的双级矩阵变换器闭环控制

对双级矩阵变换器(two-stage matrix converter,TSMC)输出电压产生影响的扰动因素很多,而闭环控制是抑制多种扰动的有效方法。TSMC是一非线性、多变量、强耦合的系统,其精确的数学模型难以建立,采用基于对象模型的控制律难以得到好的控制效果。该文提出了一种基于自抗扰控制技术的TSMC闭环控制策略,利用自抗扰控制器(auto disturbances rejection control,ADRC)的非线性鲁棒控制技术实现TSMC这种不确定性系统的控制。该文建立了TSMC逆变级电路的数学模型,把系统模型中的耦合项、不确定项都看作是系统的模型内扰,将输入电压、负载变化等扰动看成不确定外扰,利用ADRC对内外综合扰动进行观测,并对其进行补偿。仿真结果表明,在相同的非理想运行条件和扰动情况下,ADRC展现出比经典PI控制器更优异的动静态性能,可以满足TSMC系统高性能的控制要求。     

交流电机无传感器控制的新进展

无(位置、速度)传感器控制是当前国内外交流电机传动的热点,在20世纪末已经形成了以交流电机的Park方程为基础的基于电机基波模型的无传感器控制和以高频信号注入法为基础的基于电机谐波模型的无传感器控制两大体系.在介绍无传感器控制的基本策略的基础上,以近两年发表在国际重要学术刊物和学术会议的相关学术论文以及其引文为主要调研对象,按照基于基波模型和谐波模型的两大方向,介绍了近年来国际上无传感器控制策略的新进展,并进行了分析比较,进而揭示了无传感器控制发展的新特点和新趋势.