永磁同步电动机的直接转矩控制研究

永磁同步电动机是一个强耦合的非线性系统。本文针对永磁同步电动机的特点,结合直接转矩控制方案,对永磁同步电动机直接转矩控制方法和调速控制问题进行了深入地研究。文中首先介绍了永磁同步电动机的基本结构,并根据电机基本理论建立了三相永磁同步电动机在转子坐标系下的数学模型,再以三相永磁同步电动机为基础,分析了直接转矩控制的基本理论,最后提出了永磁同步电动机直接转矩控制系统的原理。仿真结果表明,并且在不同参考转速给定下系统具有更好的适应性。     

永磁同步电机的有限时间动态面位置跟踪控制

针对永磁同步电机的非线性特性,研究了一种永磁同步电机有限时间动态面位置跟踪控制的方法。动态面技术的引入解决了在传统电机反步控制中存在的"计算爆炸"问题,神经网络技术用于近似系统中的非线性项。采用有限时间技术加快了系统的收敛速度,同时改善了系统的控制效果,并提高了系统的抗干扰能力。仿真结果表明该控制方法可以有效实现对永磁同步电动机的位置跟踪控制。     

永磁同步电动机的有限时间跟踪控制

针对永磁同步电动机绕组相电流和转速强耦合特性，基于永磁同步电动机精确的数学模型，依据中继切换控制机制和有限时间收敛的终端滑动模态控制机制，研究了永磁同步电动机的有限时间跟踪问题，给出了其终端滑模控制器的设计方案。在所设计的控制作用下，闭环系统将在有限时间内达到平衡状态，保证了闭环系统所有信号的有界性和平衡点的全局稳定性，系统在有限时间内精确地跟踪给定的参考信号。对永磁同步电动机模型进行了数值仿真，结果表明，在所设计的终端滑模控制器作用下，系统的跟踪误差在有限时间内达到零，验证了所提算法的正确和有效性。     

基于免疫遗传模糊神经网络的永磁同步电机控制

在分析永磁同步电动机(PMSM)数学模型的基础上,提出了一种基于免疫遗传算法(IGA)的递归模糊神经网络(RFNN)控制器的设计方法,并应用于永磁同步电动机双闭环矢量控制系统中的转速控制器中,对永磁同步电动机实现精确的速度控制.在与传统PI控制和递归模糊神经网络控制仿真比较中,采用该方法的系统显示出良好的控制性能和控制效果.     

永磁同步电动机的神经模糊矢量控制研究

通过分析永磁同步电动机（PMSM）的数学模型,提出神经网络模糊控制器的设计方法,并应用于永磁同步电动机双闭环矢量控制系统中的转速控制器,用来精确实现永磁同步电动机的速度控制。仿真实验表明,该方法得到的各项性能指标均优于PI控制和递归模糊神经网络控制,具有很强的适应性和鲁棒性,取得了比较理想的控制效果,为实现永磁同步电动机的智能化调速控制提供了切实可行的技术方案。     

永磁同步电动机的混沌数学模型及其线性反馈同步控制

通过分析永磁同步电动机的非线性特性,推导出其对应的数学模型,对其进行复杂动力学分析后得出其是混沌数学模型的结论,从而将控制永磁同步电动机系统转化为对混沌系统的控制,用线性反馈同步控制方法对永磁同步电动机的三种运行状态进行控制,利用Matlab仿真达到了控制永磁同步电动机的目的。结果表明,利用线性反馈可以很好地消除混沌,使系统达到一个稳定的状态。该控制策略能有效地改善永磁同步电动机系统的动态性能,增强其鲁棒性与抗干扰能力。     

永磁同步电动机的自抗扰控制研究

为了解决永磁同步电动机(PMSM)低速时控制性能差的问题,提出了用自抗扰控制器代替永磁同步电动机控制系统速度控制环中的PI控制器。根据永磁同步电动机的强耦合性、非线性的特点,研究了直接转矩控制技术(DTC)和自抗扰控制(ADRC)技术,设计了基于ADRC-DTC的永磁同步电动机的控制系统,并构建了其仿真模型。仿真结果表明:在低速时,基于ADRC-DTC的永磁同步电动机的控制系统比基于PI-DTC的控制系统转速响应快且超调量小,转矩脉动小,电流畸变小,有较好的鲁棒性。     

高阶滑模消抖控制在永磁同步电动机中的应用

针对永磁同步电动机滑模控制系统抖振问题,利用具有消抖作用的高阶滑模控制算法,提出一种永磁同步电动机的高阶滑模控制策略.在对同步电动机非线性模型分析的基础上,进行反馈线性化解耦控制,设计基于高阶滑模算法的永磁同步电动机控制器.进行基于半物理仿真平台dSPACE的任意阶滑模控制的实验研究,并与传统滑模控制方法进行对比分析....     

基于反推控制的永磁同步电动机速度的模糊控制

在永磁同步电动机速度跟踪系统中,电机参数的变化会导致系统出现一定的波动.针对此问题,本文提出了把模糊控制和反推控制相结合的控制策略,通过模糊控制器调节反推控制系统中的反推参数来改善系统的速度跟踪性能.该方法不仅能够实现永磁同步电动机系统的完全解耦,保证系统全局渐进稳定;并且通过模糊控制器对系统中反推参数的实时调整,能够在电机参数发生变化时实现快速的速度跟踪,使系统具有较强的鲁棒性和良好的伺服性能.通过Matlab仿真及实验结果验证了系统设计的有效性和可行性.     

电动汽车驱动用永磁同步电动机系统效率优化控制研究

为提高电动汽车续行里程,提出一种电动汽车驱动用永磁同步电动机系统的自适应效率优化控制策略,在电动汽车任何工况下都能够快速找到电机系统最大效率运行点.为提高效率优化的快速性,本策略采用了永磁同步电动机电气损耗数学模型结合模糊逻辑控制及转矩补偿的方法.开发了基于TMS320F240DSP的电动汽车驱动用永磁同步电动机效率优化控制系统.实验结果证明了本策略的有效性.     

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.     

Adaptive finite-time consensus tracking control for nonlinear multiagent systems in nonstrict feedback form with full-state constraints

In this article, the fuzzy adaptive finite-time consensus tracking control problem for nonstrict feedback nonlinear multiagent systems with full-state constraints is studied. The finite-time control based on command filtered backstepping is proposed to guarantee the finite-time convergence and eliminate the explosion of complexity problem caused by backstepping process, and the errors in the filtering process are compensated by using error compensation mechanism. Furthermore, based on the fuzzy logic systems, the uncertain nonlinear dynamics are approximated and the problem of state variables in nonstrict feedback form is solved by using the property of basis functions. The barrier Lyapunov functions are introduced to guarantee that all system states and compensated tracking error signals are constrained in the designed regions. A simulation example is given to verify the superiority of the proposed algorithm.     

永磁同步电机位置伺服系统的有限时间控制

针对永磁同步电机位置伺服系统控制问题,对有限时间控制技术的应用进行了研究.依据有限时间控制理论,利用反步构造法,对系统的位置环提出了一种基于反馈线性化和有限时间控制技术的策略.对干扰情况下闭环系统的性能进行了严格的数学分析.仿真结果表明:与传统的基于PD和反馈线性化的控制方案相比,基于有限时间控制技术的控制方案不仅使得闭环系统的位置跟踪误差具有更快的收敛速度,而且通过调节控制器参数可以使稳态误差的边界更小,系统具有更强的抗干扰能力.仿真结果验证了该方法的有效性.     

Adaptive fuzzy finite-time consensus tracking for multiple Euler-Lagrange systems with unknown control directions

In this paper, the problem of adaptive fuzzy finite-time consensus tracking control for multiple Euler-Lagrange systems (ELSs) with uncertain dynamics and unknown control directions (UCDs) is investigated. The computational complexity problem in conventional backstepping is avoided by using finite-time command filter (FTCF), and the error in the filtering process is eliminated through error compensation signals. The fuzzy logic system combined with the adaptive control technique is applied to approximate and estimate the unknown nonlinear dynamics of ELS. The Nussbaum function-based continuous and nonsmooth input control torque is established to eliminate the influence of UCDs, and the proposed control scheme can guarantee the consensus tracking errors converge to the desired neighborhood of the origin within a finite time. Numerical simulation is used to test the effectiveness of the given algorithm.     

Adaptive finite-time control for output regulation of nonlinear systems with completely unknown control directions

This article studies the finite-time output regulation problem for nonlinear strict-feedback systems with completely unknown control directions and unknown functions. First, according to the necessary conditions for the solvability of the output regulation problem, the output regulation problem of nonlinear strict-feedback systems and the external system is transformed into a stabilization problem of nonlinear systems. Second, an internal model with external signals is designed. Third, based on finite time, fuzzy control, output feedback control, and Nussbaum gain functions, the control law is designed so that all signals of the closed-loop system are the semi-global practically finite-time stable (SGPFS), and the tracking error converges to a small neighborhood of the origin in a finite-time. Finally, the proposed algorithm is applied to the finite-time tracking problem of Chua's oscillator system.     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

Adaptive fuzzy finite-time quantized control for stochastic nonlinear systems with full state constraints

This article studies the adaptive fuzzy finite-time quantized control problem of stochastic nonlinear nonstrict-feedback systems with full state constraints. During the control design process, fuzzy logic systems are used to identify the unknown nonlinear functions, integral barrier Lyapunov functions are employed to solve the state constrained problem. In the frame of backstepping design, an adaptive fuzzy finite-time quantized control scheme is developed. Based on the stochastic finite-time Lyapunov stability theory, it can be guaranteed that the closed-loop system is semiglobal finite-time stable in probability, and the tracking errors converge to a small neighborhood of the origin in a finite time. Finally, two simulation examples are provided to testify the effectiveness of the developed control scheme.     

永磁同步电动机逆系统解耦控制

提出了一种永磁同步电动机（PMSM）的逆系统线性化解耦控制方法。首先,通过非线性状态反馈获得PMSM的逆系统,将多变量、非线性、强耦合的PMSM动态解耦成转速与定子电流两个低阶的线性子系统,然后,分别设计线性控制器对转速与定子电流子系统进行闭环控制。仿真结果表明：提出的控制方案具有优良的动态和静态性能,且对负载变化具有较强鲁棒性。     

永磁同步电机模糊变阶次分数阶滑模控制研究

分数阶滑模控制在永磁同步电机(PMSM)中的应用得到广泛研究,但目前该类方法中分数阶次大多为常数。为了进一步提高分数阶滑模控制器的全局控制性能,提出一种新的模糊变阶次分数阶滑模控制方法。首先基于PMSM的数学模型设计了变阶次分数阶滑模速度控制器;然后通过分析不同阶次时分数阶滑模控制器的性能,获得了最优阶次的变化规律;最后构建了以速度误差为输入、阶次为输出的模糊推理规则,并设计了模糊变阶次分数阶滑模控制器。仿真结果证明所提方法在控制性能上优于常数阶次分数阶滑模控制方法。     

基于DSP永磁同步电机模糊PI控制系统研究

提出了一种基于DSP的永磁同步电机(PMSM)的模糊PI复合控制方法。在PMSM双闭环控制系统中，电流环采用矢量控制，速度环采用模糊PI控制。文中给出了控制系统结构及软硬件设计方案。实验结果表明，这种新型的模糊PI复合控制方法响应快、鲁棒性强，具有很好的动、静态特性。