基于自适应Backstepping设计的TCSC非线性鲁棒控制器

电力系统是强非线性的动态大系统,在运行中总要受到外部干扰和内部干扰的影响,从而对其稳定运行造成严重威胁.本文针对带有TCSC单机无穷大母线系统的三阶鲁棒模型,在考虑阻尼系数未知及系统受外部扰动的情况下,将自适应backstepping方法与非线性L₂增益干扰抑制理论融合,构造出系统的存贮函数,并获得非线性自适应鲁棒控制器及参数替换律.所得控制器不仅能够保证系统状态有界,而且能够有效抑制干扰对系统输出的影响.通过对单机系统的仿真结果表明采用该方法的控制器优于传统的控制器.     

A robust adaptive dynamic surface control for linear systems

In this article, a robust output-feedback adaptive dynamic surface control (DSC) is proposed for linear time-invariant single-input single-output plants with unmodelled dynamics and unmeasurable output disturbance. With the proposed adaptive DSC scheme, the ‘explosion of terms’ problem inherent in backstepping control is eliminated and the adaptive law is necessary only at the first design step, which significantly reduces the design procedure. More importantly, it is proved that with an initialisation technique, the ?_∞ performance of the tracking error can be guaranteed even with unmodelled dynamics, bounded output disturbance exists and the plant high-frequency gain is unknown.     

发电机和静止无功补偿器鲁棒非线性协调控制

采用Hamilton函数方法研究发电机励磁和静止无功补偿器(SVC)的鲁棒协调控制问题。首先建立系统的不确定非线性微分代数系统控制数学模型;然后通过预置状态反馈完成系统的耗散Hamilton实现,并基于耗散实现设计鲁棒非线性协调控制器。仿真结果表明,该控制器能有效提高电力系统的暂态稳定性。     

基于间接自适应鲁棒的永磁同步电机电流控制器设计

针对永磁同步电机(PMSM)电流环非理想反电势的抑制问题,本文提出一种基于鲁棒最小二乘(RRLS)自适应律的间接自适应鲁棒控制(IARC)方法.该控制方法基于自适应鲁棒控制(ARC)理论,根据电机状态方程构造最小二乘型自适应律,加入修正因子增强自适应律对系统中扰动的鲁棒性.本文理论证明了该方法的稳定性.通过建立含有非理想反电势的电机模型,设计IARC电流控制器,并分析说明IARC具有比直接ARC更好的输出跟踪性能和扰动抑制能力.最后,通过仿真和实验验证了该方法的有效性.     

非脆弱递归滑模动态面自适应神经网络控制

针对一类非匹配不确定非线性系统的跟踪控制问题, 提出了一种递归滑模动态面自适应控制算法. 采用神经网络(neural network, NN)在线逼近系统不确定项, 通过设计递归滑模动态面有效综合反推步骤中每步跟踪误差之间相互影响和制约的关系. 该方法避免了反推法存在的“微分爆炸”问题, 克服了传统动态面方法对其低通滤波器时间常数和神经网络自适应参数摄动脆弱的缺点. 稳定性分析证明了该方法能够保证闭环系统所有状态半全局一致最终有界, 且跟踪误差可以收敛至原点的任意小邻域.     

基于自适应动态规划的非线性鲁棒近似最优跟踪控制

为克服现有近似最优跟踪控制方法只能跟踪连续可微参考输入的局限,本文针对一类具有未知动态的连续时间非线性时不变仿射系统,提出了一种新的基于自适应动态规划的鲁棒近似最优跟踪控制方法.首先采用递归神经网络建立系统模型,然后建立评价神经网络对最优性能指标进行估计,从而得到最优性能指标偏导数的估计值,进而得到近似最优跟踪控制器,最后利用系统输出与参考输入之间的跟踪误差设计鲁棒项对神经网络建模误差进行补偿.分别针对两个非线性系统进行仿真实验,仿真结果表明了所提方法的有效性和优越性.     

双重强跟踪滤波励磁及速度非线性鲁棒控制

针对传统移动电站存在励磁、调速控制相互独立、缺乏联系的不足,研究和建立了励磁及机电复合调速非线性模型,提出了基于状态参数双重强跟踪滤波估计的非线性鲁棒综合控制策略.采用双重强跟踪滤波的方法,实现了模型中关键状态参量的间接获取,依据多输入多输出系统的精确反馈线性化、非线性鲁棒控制理论,对励磁、机电复合调速综合控制律进行了推导,并进行了仿真验证.仿真结果表明:负载突变时,强跟踪滤波能够快速跟踪和估计状态参数;在外部干扰存在情况下,通过求解线性矩阵不等式,本文得到的控制律在保证励磁、转速控制系统稳定的同时,能够实现L2增益干扰抑制.     

汽轮发电机主汽门开度非线性鲁棒控制

由于外界干扰以及各种故障的影响, 电力系统的结构并不是不变的, 因此其中的一些重要参数, 如输电线路电抗等, 总是包含某种不确定性. 针对含有参数不确定性的汽轮机调速系统, 使用自适应逆推方法及Lyapunov方法设计了非线性鲁棒汽门控制器, 基于该方法的设计, 设计过程系统、简明, 且不必对原系统进行线性化, 通过对单机无穷大系统的仿真表明了该控制器的有效性.     

非线性系统有限时间自适应动态面容错控制

针对具有传感器故障的一类严格反馈非线性系统, 提出一种有限时间自适应动态面容错控制策略. 考虑的 传感器故障包括: 固定偏差故障、漂移故障、精度下降及失效故障. 以反步法为主要设计依据, 利用模糊逻辑系统处 理模型中的未知函数. 该控制策略的显著优势在于结合有限时间理论、容错控制、模糊逻辑控制及动态面控制, 使 得系统无论发生故障与否, 均使得系统在原点处是半全局实际有限时间稳定, 同时保证系统的实际输出信号在有限 时间内跟踪期望信号, 且跟踪误差收敛于坐标原点的小邻域内. 另外, 通过采用动态面控制技术克服了传统反步法 中的计算复杂问题. 最后, 仿真算例证明了该设计方案的有效性.     

一种简化的自适应模糊动态面控制

针对一类不确定非线性时变时滞系统,提出了一种简化的自适应模糊动态面控制方法.该方法取消了对系统时滞常做的假设.仅采用一个模糊逼近器便使所有的未知函数得到补偿,简化了控制器的结构.通过构造合适的Lyapunov-Krasovskii泛函,闭环系统的所有信号被证明为半全局一致最终有界.仿真实例进一步验证了控制方案的有效性.     

船舶航向控制的多滑模鲁棒自适应设计

针对带有未知虚拟控制增益和常参数不确定的非匹配不确定船舶航向非线性控制问题,设计了一种新的多滑模鲁棒自适应控制算法.该算法利用神经网络来逼近系统模型的不确定性;应用逐步递推的多滑模控制算法降低了控制器的复杂性;尤其是采用Nussbaum函数处理系统中符号未知的问题,避免了可能存在的控制器奇异值问题;然后借助Lyapunov稳定性分析方法,理论分析证明了所得闭环系统全局一致最终有界,且跟踪误差收敛到零.仿真试验结果表明,该方法具有较好的控制效果.     

Advances in attractive ellipsoid method for robust control design

Our contribution is devoted to a further theoretic development of the attractive ellipsoid method (AEM). We consider dynamic models given by nonlinear ordinary differential equations in the presence of bounded disturbances. The resulting robustness analysis of the closed‐loop system incorporates the celebrated Clarke invariancy concept (an analytic extension of the celebrated Lyapunov methodology). We finally obtain a new general geometric characterization of the AEM‐based approach to the robust systems design. Moreover, we also discuss the corresponding numerical aspects of the proposed theoretical extensions of the method. The theoretic results obtained in this contribution are finally illustrated by a practically oriented computational example.     

Observer‐based adaptive robust control of a class of nonlinear systems with dynamic uncertainties

In this paper, a discontinuous projection‐based adaptive robust control (ARC) scheme is constructed for a class of nonlinear systems in an extended semi‐strict feedback form by incorporating a nonlinear observer and a dynamic normalization signal. The form allows for parametric uncertainties, uncertain nonlinearities, and dynamic uncertainties. The unmeasured states associated with the dynamic uncertainties are assumed to enter the system equations in an affine fashion. A novel nonlinear observer is first constructed to estimate the unmeasured states for a less conservative design. Estimation errors of dynamic uncertainties, as well as other model uncertainties, are dealt with effectively via certain robust feedback control terms for a guaranteed robust performance. In contrast with existing conservative robust adaptive control schemes, the proposed ARC method makes full use of the available structural information on the unmeasured state dynamics and the prior knowledge on the bounds of parameter variations for high performance. The resulting ARC controller achieves a prescribed output tracking transient performance and final tracking accuracy in the sense that the upper bound on the absolute value of the output tracking error over entire time‐history is given and related to certain controller design parameters in a known form. Furthermore, in the absence of uncertain nonlinearities, asymptotic output tracking is also achieved. Copyright © 2001 John Wiley & Sons, Ltd.     

基于复合自适应律的直线电机自适应鲁棒控制

自适应鲁棒控制(ARC)能克服参数不确定性与扰动对系统的影响, 具有良好的输出跟踪性能. 然而常规ARC的参数估计值难以逼近真值. 为实现高性能的控制与准确的参数估计, 本文提出了基于复合自适应律的自适应鲁棒控制(CAARC). 该方法同时采用了输出误差与参数估计误差的相关信息构造自适应律, 具有比常规ARC更好的参数估计效果. 本文在理论上证明了CAARC的闭环稳定性与参数估计误差的收敛性, 并通过分析表明CAARC具有比常规ARC更好的输出跟踪性能, 最后通过仿真验证了该方法的有效性.     

H2/H∞保性能控制理论在静止无功发生器控制中的应用

利用H₂/H_∞保性能控制理论和直接反馈线性化, 给出了单机无穷大系统中, 具有参数摄动的静止无功发生器(STATCOM)的非线性控制模型. 使用MATLAB软件得出H₂/H_∞保性能控制律, 表示为线性矩阵不等式(LMI).在扰动及参数摄动的条件下进行了仿真. 结果表明这种控制方法同时具有鲁棒性和最优性能, 降低了单纯H_∞控制方法的保守性, 提高了电力系统的稳定性, 并满足电压精度的要求.     

Hybrid adaptive robust control of static var compensator in power systems

To improve the transient response of an electric power transmission system, a hybrid adaptive robust control method is proposed in this paper for the static var compensator by incorporating the immersion and invariance adaptive (I&I adaptive) and L₂‐gain control. In contrast to the standard I&I adaptive control algorithm, establishing a target system is not required in constructing the robust control law with the proposed method. Thus, the procedure of solving PDEs to satisfy the immersion condition can be avoided. In addition, both parametric and non‐parametric uncertainties, which commonly exist in electric power transmission systems, are considered. The parametric uncertainty induced by the damping coefficient of the system is estimated by the designed adaptive law, which is constructed by ensuring the estimation error converges to zero. The non‐parametric uncertainty is caused by external disturbances and approximation errors in modeling the uncertain structure. By assuming that the L₂‐gain of the system to the non‐parametric uncertainties satisfies a dissipation inequality, we found that the robustness of the controller can be guaranteed. It is proved that all the system states are globally bounded and converge to a new stable equilibrium. Simulation results are also presented to show the effectiveness of the proposed control method in improving the transient response of the system and the convergence speed of the system states. Copyright © 2013 John Wiley & Sons, Ltd.     

改进的非线性鲁棒自适应动态面控制

针对不确定多输入多输出严格反馈块控非线性系统,提出一种鲁棒自适应动态面控制方法.该方法在反推自适应神经网络控制中引入动态面控制简化控制律,同时对自适应律进行改进以改善系统的过渡过程动态品质,保证了系统在简化的控制律下仍具有良好的动态特性.通过Lyapunov方法证明了闭环系统所有信号均有界,系统的跟踪误差指数收敛到有界紧集内.最后给出的某新型战斗机六自由度仿真结果表明了该方法的有效性.     

Disturbance-observer-based adaptive finite-time dynamic surface control for PMSM with time-varying asymmetric output constraint

This article presents a disturbance-observer-based adaptive finite-time dynamic surface control scheme, capable of guaranteeing transient behavior for the PMSM with arbitrary asymmetric time-varying output constraint and unmatched external disturbance. The major challenge of this paper is devising efficient strategies to tackle the nonsymmetric output restraints with arbitrary characteristics and unmatched external perturbation for the system under the finite-time backstepping framework. Given this, a nonlinear transformation function is adopted to coordinate from the output-constrained dynamic model to an uncontained one, and a finite-time disturbance observer is introduced to evaluate the unmatched external perturbation. Then, a dynamic surface control approach having adaptive properties for PMSM is conceived by combing a neural network to evaluate the nonlinear functions and a first-order filter to handle the “explosion of complexity.” Additionally, it is proved that the signals in the closed-loop system can narrow down to a bounded region and the tracking error can merge in a limited time to tiny vicinity of zero by employing a fast finite-time stability principle. Eventually, simulation cases and contrast results reveal the tracking performance and immunity to the disturbance of the devised controller.     

An uncertainty compensator for robust control of wheeled mobile robots

This paper proposes an uncertainty compensator to design a novel robust control for mobile robots with dynamic and kinematic uncertainties. A novel gradient-based adaptive fuzzy estimator is developed to compensate uncertainties with minimum required feedback signals. As a novelty, the proposed approach uses the tracking error and its first time derivative to form the estimation error of uncertainty, and guarantees that both the estimation error and tracking error converge asymmetrically to ignorable value. Advantages of the proposed robust control are simplicity in design, robustness against uncertainties, guaranteed stability, and good control performance. The control approach is verified by stability analysis. Simulation results and experimental results illustrate the effectiveness of the proposed control. Experimental evaluation of the proposed controller is expressed for two different low-cost nonholonomic wheeled mobile robots. The proposed control design is compared with an adaptive control approach to confirm the superiority of the proposed approach in terms of precision, simplicity of design, and computations.     

Nonlinear robust state feedback control system design for nonlinear uncertain systems

This paper presents a systematic approach to the design of a nonlinear robust dynamic state feedback controller for nonlinear uncertain systems using copies of the plant nonlinearities. The technique is based on the use of integral quadratic constraints and minimax linear quadratic regulator control, and uses a structured uncertainty representation. The approach combines a linear state feedback guaranteed cost controller and copies of the plant nonlinearities to form a robust nonlinear controller with a novel control architecture. A nonlinear state feedback controller is designed for a synchronous machine using the proposed method. The design provides improved stability and transient response in the presence of uncertainty and nonlinearity in the system and also provides a guaranteed bound on the cost function. An automatic voltage regulator to track reference terminal voltage is also provided by a state feedback equivalent robust nonlinear proportional integral controller. Copyright © 2016 John Wiley & Sons, Ltd.