基于自适应高增益观测器的永磁同步电机预测电流控制方法

针对永磁同步电机(permanentmagnetsynchronous motor,PMSM)预测控制系统的模型失配、时变矩阵及观测器增益选择问题,提出基于自适应高增益观测器的预测电流控制方法(predictive current control based on an adaptive high-gain observer,AHGOPCC)。通过构建PMSM的前馈型扩张数学模型,集成考虑电机电阻、电感、磁链参数扰动项。提出基于前馈型扩张标称数学模型的高增益观测器,有效跟踪和估计电流与扰动状态及抑制转速变化引起的扰动。同时,设计自适应观测器增益矩阵满足全速工况的高增益条件,简化观测器的增益选择。在此基础上,构建离散化电流模型和成本函数,实现预测电流控制算法。实验结果证明了该方法的有效性,在多种工况下具备更优的快速性、鲁棒性及稳定性。     

一类非线性相似组合系统的自适应状态观测器设计

针对由若干个输出反馈相似的控制系统互联而成的带有未知参数的非线性组合系统，设计出一种具有分散自适应律的状态观测器，结果表明这类观测器在某种程度上仍具有相似结构，相似结构可以简化系统的分析和设计。最后的仿真算例说明了所采用方法的有效性。     

一类不确定非线性系统的动态面输出调节方法

针对一类由线性中性稳定的外系统驱动的具有未建模动态和外界扰动的非线性不确定系统的输出调节问题,结合动态面控制法和内模原理提出一种具有动态面控制的设计方法.根据非线性输出调节问题可解的必要条件,运用状态变换和标准内模将输出调节问题转化为镇定问题.运用动态面控制法将一阶滤波器引入反步设计中,避免了反步设计中所存在的"膨胀项...     

基于Taylor展开的纯滞后系统增益自适应内模PID控制

本文将纯滞后环节进行一阶Taylor逼近后，根据内模控制原理，得到了单位反馈PID控制器的参数整定值，然后运用仿人智能的方法得到被控对象的静态增益，由此来自动调整控制器的比例系数。仿真结果表明，增益自适应内模PID控制器能克服增益变化对控制性能的影响，显著改善控制品质。     

一种具有时变观测器增益的摩擦补偿方法

为有效抑制摩擦扰动对光电平台性能的影响,针对环架轴系间的摩擦由LuGre模型描述的情况,设计自适应摩擦补偿控制器.提出一种采用具有时变增益摩擦状态观测器的摩擦补偿方法,通过类李雅普诺夫分析证明整个闭环系统跟踪误差的渐近收敛性.仿真结果表明,通过对时变增益函数中设计参数的适当选择,相比采用具有常数增益的观测器,系统的角速...     

具有增益调度切换增益的永磁同步电机滑模控制

滑模控制器的切换增益需要随着参数摄动和外部扰动变化,但是增大切换增益会加剧系统抖振。针对这一问题,采用增益调度和自适应相结合的方法对永磁同步电机滑模控制器的切换增益进行实时整定。该方法根据自适应律在线调整切换增益系数的边界范围,同时以关于直轴、交轴电流的积分滑模面函数作为调度变量,在允许边界范围内对切换增益系数进行增益调度。所设计方法在保证系统鲁棒性的前提下,削弱了系统抖振,改善了控制性能。     

一类不确定非线性系统的有限时间输出调节方法

针对一类外系统是中性稳定的不确定非线性系统的输出调节问题,提出一种有限时间收敛的输出调节器的设计方法。该方法结合内模原理和有限时间稳定性理论,先根据输出调节问题可解的必要条件,将原受控系统和外系统的输出调节问题转化为增广系统的镇定问题;再利用动态面技术设计一种鲁棒有限时间稳定的镇定器,从而保证闭环系统的信号是全局最终有界的,并且使调节误差在有限的时间内收敛至任意给定的范围内。仿真结果说明了所设计调节器的有效性和可行性。     

动态不确定发电机系统的小增益控制

对于包含动态不确定的发电机系统,运用Backstepping方法和小增益相结合的设计方法,设计了发电机系统的非线性控制器,使其达到功角和输出电压的稳定性.采用改进的Backstepping方法设计励磁控制输入,通过小增益方法对动态不确定部分加以控制,使得整个系统达到渐近稳定.仿真结果验证了该设计方法不仅保证了功角、转子角速度和输出电压的稳定性,而且对于动态不确定部分实现了有效控制,说明了设计思想正确、控制方案有效.     

便携式车载高增益DC-DC变换器大信号稳定控制策略:基于扰动观测器的反步技术EI北大核心CSCD

充电效率低和可用里程短等问题严重阻碍了电动汽车的进一步发展。由于前级电动汽车输出电压较低,需采用便携式高增益DC-DC变换器实现电动汽车间快速能量交互。该文以交错并联双升压变换器为研究对象,采用基于扰动观测器的反步控制算法,提高变换器抵抗内外干扰的能力。扰动观测器对系统寄生参数进行等效估计,提高了系统抵抗内部参数扰动的鲁棒性;同时实时估计输出功率和输入电压,减少使用传感器以降低系统成本。利用扰动观测器的输出,进一步设计了反步控制器,以严格保证系统大信号意义上的稳定性。此外,文中采用相电流平衡补偿器,解决了六通道之间的均流问题,减少热损失并提高了设备的使用寿命。最后,仿真和实验结果验证了提出控制器的有效性。     

双轴励磁同步发电机非线性鲁棒自适应控制

利用Backstepping和扰动抑制方法设计了双轴励磁同步发电杌的自适应控制器。对于含有各种不确定参数和有界扰动的非线性双轴励磁同步杌模型，实现了对转子同步的鲁棒调节。文中的方法可用于其他不确定电力系统的控制设计。     

Sliding mode control for a class of uncertain nonlinear system based on disturbance observer

In this paper, a sliding mode control (SMC) scheme is proposed for a class of nonlinear systems based on disturbance observers. For a nonlinear system, the disturbance that cannot be directly measured is estimated using a nonlinear disturbance observer. By choosing an appropriate nonlinear gain function, the disturbance observer can well approximate the unknown disturbance. Based on the output of the disturbance observer, an SMC scheme is presented for the nonlinear system, and the stability of the closed‐loop system is established using Lyapunov method. Finally, two simulation examples are presented to illustrate the features and the effectiveness of the proposed disturbance‐observer‐based SMC scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

基于神经网络的一类非线性系统自适应滑模控制

针对可以分解为标称系统和不确定系统两部分的SISO非线性系统,提出了一种基于神经网络的自适应滑模控制方案。控制器由标称控制律和补偿控制律组成,标称控制律用来控制标称系统,补偿控制律是基于Lyapunov稳定性理论设计的自适应神经滑模控制律,用来控制不确定系统,而神经网络用来逼近系统的不确定性。理论分析和计算机仿真都证明,本文提出的控制策略不但能解决这类系统的轨迹跟踪控制问题,而且可以保证闭环系统的渐近稳定性。     

一类不确定非线性系统的自适应模糊跟踪控制

针对一类不确定非线性连续系统，用模糊系统对未知函数进行逼近的基础上，利用Lyapunov稳定性理论，提出了一种新的自适应模糊跟踪控制算法，此算法的特点是，无论取多少条模糊系统的规则，自适应学习的参数只有一个，便于实现，而且还能确保闭环系统渐近稳定，并使系统的跟踪误差为零，仿真研究表明，所提出的算法是有效的。     

Adaptive state tracking of switched systems based on a hyperstability criterion

The adaptive state tracking problem of switched systems is studied in this paper. The desirable state trajectory is generated by a switched reference model. First, a condition for asymptotical hyperstability of switched systems is proposed and a switching law is designed, which is a generalization of the classical hyperstability condition for non‐switched systems. Then, the result is applied to uncertain switched systems to achieve state tracking. An individual adaptive law is designed for each subsystem such that the Popov inequality is satisfied. Asymptotical state tracking is achieved under non‐persistent exciting input when the error system switches in a certain way. The result is demonstrated by a numerical example and a practical system of Highly Maneuverable Aircraft Technology vehicle, respectively. Copyright © 2013 John Wiley & Sons, Ltd.     

Observer‐based adaptive neural control of uncertain MIMO nonlinear systems with unknown control direction

This paper investigates adaptive neural network output feedback control for a class of uncertain multi‐input multi‐output (MIMO) nonlinear systems with an unknown sign of control gain matrix. Because the system states are not required to be available for measurement, an observer is designed to estimate the system states. In order to deal with the unknown sign of control gain matrix, the Nussbaum‐type function is utilized. By using neural network, we approximated the unknown nonlinear functions and perfectly avoided the controller singularity problem. The stability of the closed‐loop system is analyzed by using Lyapunov method. Theoretical results are illustrated through a simulation example. Copyright © 2012 John Wiley & Sons, Ltd.     

Composite adaptive disturbance observer‐based control for a class of nonlinear systems with multisource disturbance

Antidisturbance control and estimation problem are introduced for a class of nonlinear system subject to multisource disturbances. The uncertain multisource disturbances consist of not only a single harmonic or constant disturbance but also another unexpected nonlinear signal described as a nonlinear function. The composite adaptive disturbance observers are constructed separately from the controller design to estimate the disturbance with partial known information. By integrating disturbance observer‐based controller with robust adaptive control, a novel type of composite adaptive disturbance observer‐based control scheme is presented for a class of nonlinear system with multisource disturbances. Simulations for a flight control system are given to demonstrate the effectiveness of the results compared with the previous schemes. Copyright © 2012 John Wiley & Sons, Ltd.     

非线性系统模糊间接自适应控制的后推设计

采用模糊神经网络作为非线性逼近器，针对一类一阶非线性多入多出系统，提出了一种具有扰动抑制的鲁棒自适应控制方法，给出了高阶多入多出系统具有扰动抑制的自适应后推(backstepping)设计方法。在鲁棒项合理简化的情况下，给出了系统Lyapunov意义下的稳定性证明，简略分析了各设计参数的物理意义及其对系统性能的影响。理论分析和仿真实验均显示，本方法可以保证系统的全局渐近稳定性，且若选取恰当的设计参数可保证系统对输入信号的跟踪达到任意精度；由于鲁棒项的引入可使系统的设计更具灵活性。     

Passivity‐based control for stabilization,regulation and tracking purposes of a class of nonlinear systems

In this paper, a new passivity‐based control (PBC) scheme based on state feedback is proposed in order to solve tracking, regulation and stabilization problems for a class of multi‐input multi‐output (MIMO) nonlinear systems expressed in the normal form, with time‐invariant parameters and locally bounded reference weakly minimum phase. For the proposed control scheme two new different state feedbacks, one non‐adaptive for the case when the system parameters are assumed to be known and the other adaptive for the case of unknown parameters, are developed. For the adaptive case it is assumed that the unknown parameters appear linearly in the equations. Analysis of the transient behaviour of the proposed control schemes is presented through the simulation of two examples. Copyright © 2006 John Wiley & Sons, Ltd.