多机电力系统模糊自适应控制

发电机组的励磁控制对于提高电力系统的暂态稳定性起着至关重要的作用.针对多机电力系统励磁控制模型,设计模糊自适应控制器.考虑到电力系统的状态不可测及多变量、非线性等特点,设计状态观测器,而后根据多机电力系统互联的实际情况,运用蚁群算法的寻优功能优化模糊规则,一定程度上改善了多变量系统控制中模糊规则繁多的问题.此方法使系统在保证了良好暂态稳定性的同时,降低了控制器的设计难度.仿真结果表明所设计的控制器能够快速有效地改善系统在大干扰下的暂态稳定性.     

多机电力系统变结构励磁控制器的设计研究

基于多机电力系统的非线性模型,利用状态反馈精确线性化方法和变结构控制理论,提出了一种新的电力系统变结构励磁控制器设计方法。在设计中取消了参考机,并实现了多机系统的分散控制。3机系统的仿真结果表明,提出的变结构励磁控制器可以有效地改善系统在大干扰下的暂态稳定性。     

多机电力系统变结构励磁控制器的设计研究

基于多机电力系统的非线性模型,利用状态反馈精确线性化方法和变结构控制理论,提出了一种新的电力系统变结构励磁控制器设计方法.在设计中取消了参考机,并实现了多机系统的分散控制.3机系统的仿真结果表明,提出的变结构励磁控制器可以有效地改善系统在大干扰下的暂态稳定性.     

HVDC模糊协调阻尼控制器的设计

分析了区间振荡和暂态能量函数的关系,通过削减系统的区间振荡暂态能量为控制目标来制定阻尼控制策略,设计了高压直流(HVDC)模糊逻辑协调控制器,以提高交直流并联电力系统动态稳定性水平.该控制方案不需要精确的模型参数,充分考虑HVDC系统整流侧直流电流调制和该侧发电机的励磁控制特性,通过模糊规则去协调两个控制系统,实现对系统低频振荡的有效抑制.仿真结果表明,该控制器能有效提高交直流并联系统的动态稳定性水平.     

具有双励机的混合多机电力系统非线性综合控制器的研究

本文以电力系统的非线性模型为基础，依据坐标变换和反馈控制理论，推导设计了具有双轴励磁同步发电机（双励机）的混合多机电力系统的励磁和汽门非线性综合控制器。仿真表明，本文提出的控制方案不仅可以提高电力系统的暂态稳定性，而且可以有效地改善系统的动态特性。     

基于模糊控制的多机系统暂态稳定分析

电力系统暂态稳定性的研究,对保证电网的安全与稳定具有重要的意义。文中提出了一种基于模糊控制的多机系统暂态稳定分析方法,该方法将模糊控制和电力系统稳定性理论有机的结合在一起,以模糊集合论、模糊语言变量及模糊逻辑推理为基础,将发电机励磁系统的控制策略转化为模糊规则的形式,从而实现对多机系统的模糊控制。通过Matlab软件对三机系统进行数值仿真表明,与独立设计的AVR/PSS励磁控制器相比,以△ω、△ω为输入变量的模糊控制能更加有效的提高系统的暂态稳定性能,系统在不同的故障情况下具备较强的鲁棒性。     

提高交直流电力系统稳定性的HVDC模糊逻辑控制器

提出一种附加在高压直流(HVDC)系统上的辅助型模糊逻辑控制器以提高交直流互联电力系统稳定性。在控制器的设计中应用能量函数法，通过增大振荡的减速能量来提高系统的稳定性水平。借助于HVDC线路的快速控制能力，采用模糊规则平滑地调整HVDC输送的功率，并使用自适应控制技术以提高控制器的稳定性。在4机和8机交直流电力系统上的仿真结果表明，该控制器在平抑系统小信号振荡的同时也可在一定程度上改进系统的暂态稳定性。     

复杂系统非线性励磁控制的数字仿真研究

对一个IEEE典型的13机系统进行了数字仿真。比较了在其中一台发电机上装设比例积分微分控制器(PID)、电力系统镇定器(PSS)、线性最优励磁控制器(LOEC)和非线性励磁控制器(NEC)四种励磁控制器，对整个系统的暂态稳定的影响。仿真结果表明，非线性励磁控制器与采用其他三种控制器相比，电力系统的暂态稳定性有较明显的改善。在多机系统中的主力发电机组上装设非线性励磁控制器，将对整个系统的大干扰稳定性有明显的改善，从而揭示了非线性励磁控制(NEC)较其它3种励磁控制方式具有更优越的性能。     

模糊控制技术在发电机励磁系统中的应用

通过对模糊控制技术的原理分析,设计了发电机励磁系统的模糊控制器,在普通励磁系统的基础上加入模糊控制器,并在MATLAB/Simulink环境下,对该励磁系统进行了分析和仿真,结果表明:模糊控制器对于提高同步发电机的响应速度,改善电力系统的暂态和稳态性能有明显效果。     

UPFC与发电机励磁多指标协调控制设计

针对统一潮流控制器(UPFC)与同步发电机励磁控制系统,结合控制系统控制特性及多指标控制设计理念,选取多个目标状态量线性组合为输出函数,运用多指标非线性控制算法,设计了统一潮流控制器(UPFC)的新控制策略,最后在单机无穷大系统上对其进行暂态仿真.仿真结果表明,所设计的多指标协调控制系统能够很好的解决接入点静态偏移的问题,并有效地控制节点电压和线路的潮流,改善了电力系统的暂态稳定性.     

Adaptive fuzzy output feedback backstepping control of pure‐feedback nonlinear systems via dynamic surface control technique

In this paper, an adaptive fuzzy backstepping dynamic surface control approach is considered for a class of uncertain pure‐feedback nonlinear systems with immeasurable states. Fuzzy logic systems are first employed to approximate the unknown nonlinear functions, and then an adaptive fuzzy state observer is designed to estimate the immeasurable states. By the combination of the adaptive backstepping design with a dynamic surface control technique, an adaptive fuzzy output feedback backstepping control approach is developed. It is proven that all the signals of the resulting closed‐loop system are semi‐globally uniformly ultimately bounded, and the observer and tracking errors converge to a small neighborhood of the origin by choosing the design parameters appropriately. Simulation examples are provided to show the effectiveness of the proposed approach. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive fuzzy output‐feedback tracking control for switched stochastic pure‐feedback nonlinear systems

This paper considers the problem of adaptive fuzzy output‐feedback tracking control for a class of switched stochastic nonlinear systems in pure‐feedback form. Unknown nonlinear functions and unmeasurable states are taken into account. Fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy observer is designed to estimate the immeasurable states. Based on these methods, an adaptive fuzzy output‐feedback control scheme is developed by combining the backstepping recursive design technique and the common Lyapunov function approach. It is shown that all the signals in the closed‐loop system are semiglobally uniformly ultimately bounded in mean square in the sense of probability, and the observer errors and tracking errors can be regulated to a small neighborhood of the origin by choosing appropriate parameters. Finally, a simulation result is provided to show the effectiveness of the proposed control method.     

有源电力滤波器模糊软启动控制

为了解决传统控制方式下有源滤波器投入时引起的电压超调和电流冲击问题,增强整个系统的鲁棒性,采用带有自调整因子的模糊控制规则设计了直流侧电容电压的模糊软启动控制器.此控制器可以根据系统的实际情况对控制规则进行自动、实时调整.最后将模糊控制和PI控制相结合,构建了复合控制器,其具有PI控制稳态精度高、模糊控制鲁棒性强及自适应的优点.仿真结果验证了文中所提出的复合控制策略的有效性和可行性.     

Observer‐based fuzzy adaptive quantized control for uncertain nonlinear multiagent systems

This paper focuses on consensus quantized control design problem for uncertain nonlinear multiagent systems with unmeasured states. Every follower can be denoted through a system with unmeasurable states, hysteretic quantized input, and unknown nonlinearities. Fuzzy state observer and Fuzzy logic systems are employed to estimate unmeasured states and approximate unknown nonlinear functions, respectively. The hysteretic quantized input can be split into two bounded nonlinear functions to avoid chattering problem. By combining adaptive backstepping and first‐order filter signals, an observer‐based fuzzy adaptive quantized control scheme is designed for each follower. All signals exist in closed‐loop systems are semiglobally uniformly ultimately bounded, and all followers can accomplish a desired consensus results. Finally, a numerical example is employed to elaborate the effectiveness of proposed control strategy.     

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.     

基于模糊滑模变结构的直流伺服系统控制器设计

针对直流伺服系统中参数时变性和外部扰动等造成的电机模型变化,设计了一种采用滑模变结构控制策略来控制直流伺服电机的方法,并且对系统稳定性进行了分析。为了削弱抖振,采用模糊控制方法将切换控制模糊化。对所设计的模糊滑模变结构控制系统进行仿真表明,采用模糊控制能大大削弱系统抖振,另外对具有电机参数大范围摄动的系统,滑模变结构控制系统具有较强的鲁棒性和快速性。     

可控励磁直线同步电机磁悬浮系统合成模糊控制的研究

可控励磁直线同步电机磁悬浮控制系统具有非线性以及扰动不确定性的特点,采用模糊PID控制具有很强的针对性,然而,模糊PID控制器为三输入单输出控制器,其规则数太多,使得控制器设计非常复杂。因此,对可控励磁直线同步电机磁悬浮控制系统提出合成模糊控制。研究可控励磁直线同步电机的结构,建立磁悬浮直线同步电机的数学模型。合成模糊控制器采用模糊PD控制器和模糊积分器的合成构成模糊PID控制器,在减少模糊控制规则数的同时提高磁悬浮控制系统的稳态精度,因此分别设计模糊PD控制器和模糊积分控制器,包括模糊化、模糊推理、去模糊化等。在MATLAB中建立可控励磁直线同步电机磁悬浮控制系统的仿真模型并进行仿真研究。结果表明合成模糊控制器具有良好的控制效果,可以减小稳态误差提高控制精度。     

Adaptive fuzzy FTC design of nonlinear stochastic systems with actuator faults and unmodeled dynamics

This paper investigates an adaptive fuzzy control method for accommodating actuator faults in a class of uncertain stochastic nonlinear systems with both immeasurable states and unmodeled dynamics. The considered faults are modeled as both loss of effectiveness and lock‐in‐place. To deal with the immeasurable states, a novel state observer containing the actuator faults is designed. Combining with the backstepping technique and stochastic small‐gain theorem, an adaptive fuzzy output feedback control method is developed. The presented design scheme can guarantee that the closed‐loop system is input‐to‐state practically stable in probability. Finally, a simulation example is shown to verify the effectiveness of the proposed control method.     

Reinforcement learning-based optimized output feedback control of nonlinear strict-feedback systems with event sampled states

This article focuses on the event-triggered optimized output feedback control problem for nonlinear strict-feedback systems. First, a fuzzy state observer is designed to estimate the unmeasurable states. Then, the fuzzy-based reinforcement learning is performed under critic-actor architecture to realize the optimized control. In addition, a novel event-triggered mechanism is developed for the system states to greatly economize communication resources. By means of the Lyapunov stability theory, it can be proved that all signals of the closed-loop system are bounded, and the Zeno behavior can be successfully avoided. Lastly, an inverted pendulum example is provided to confirm the effectiveness of the derived algorithm.     

Integral barrier Lyapunov function-based adaptive fuzzy output feedback control for nonlinear delayed systems with time-varying full-state constraints

In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time-delay systems with time-varying full state constraints and input saturation. To overcome the problem of time-varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov-Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods.