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永磁直线伺服系统非线性自适应鲁棒控制器设计 总被引:1,自引:0,他引:1
对永磁直线伺服系统提出非线性自适应鲁棒控制器的设计方法。在永磁直线伺服系统非线性数学模型的基础上,为实现对速度和电流的准确跟踪,建立了误差系统的动态模型。将跟踪和干扰抑制归结为非线性自适应鲁棒控制器设计问题,通过构造存储函数得到包含电阻辨识算法的自适应鲁棒控制器的定理,证明定理给出的控制器能满足干扰抑制和系统的渐进稳定。仿真结果表明,用该方法设计的系统能很好的抑制扰动和跟踪给定,满足对高性能永磁直线伺服系统控制的要求。 相似文献
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为了解决永磁同步电机(PMSM)位置伺服系统中存在的内部参数摄动、负载扰动以及外界不确定性干扰等问题,设计了基于非线性干扰观测器(NDO)的自适应反演滑模控制器。通过NDO对系统存在的扰动进行观测,并将观测结果引入到自适应反演滑模控制器进行补偿。针对引入NDO后的系统,设计自适应反演滑模控制器,对滑模控制器中的切换增益利用自适应律进行调节,削弱系统抖振,提高系统的抗干扰能力和鲁棒性。仿真结果表明,与传统反演滑模控制相比,基于NDO的自适应反演滑模控制器对系统中存在的扰动具有更好的抗干扰能力,该控制器可削弱系统的抖振,从而提高了PMSM位置伺服系统的跟踪精度。 相似文献
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设计了一种基于等价输入干扰估计器的新型自抗扰控制系统,用于永磁同步电动机的速度控制。该系统运用跟踪微分器和非线性状态误差反馈控制器产生控制量,并引入等价输入干扰估计器对系统未知干扰作估计补偿,针对直接反馈线性化后的PMSM模型进行速度控制。仿真结果表明该控制器能够有效估计并抑制系统未知干扰,系统响应快,稳态精度高。 相似文献
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步进电动机的非线性自适应控制 总被引:1,自引:0,他引:1
本文研究进步电动机非线性自适应位置控制器的设计问题。采用非线性自适应反馈线性技术,设计了步进电动机的非线性自适应控制控制方案。该控制方案包括一个淅进跟踪负载力矩和绕组电阻实际值的非线性辨识算法,当辨识参数收敛到参数的实际值,该控制器就能实现步进电动机的高精度位置控制。仿真研究表明:所得闭环系统对电动机运行参数的变化和负载干扰具有良好的自适应性,不仅调节精度高,而且动态响应快速,无超调。 相似文献
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风电机组控制系统中PI控制器较多,需要辨识各PI控制器的参数。针对数字PI控制器,基于可辨识性理论,直接应用PI控制器不同状态的输入/输出数据,分析PI控制器参数的可辨识性,得到了其参数可唯一辨识的结论,并据此设计了PI参数辨识的具体算法。在此基础上,根据电机转速控制实验装置实测的数据,运用可辨识性分析步骤中的参数辨识算法,辨识得到高精确度的PI参数。在施加脉冲群干扰试验和振荡波干扰试验条件下,算法也能准确地辨识PI控制器参数,具有良好的鲁棒性,验证了理论分析的正确性和辨识方法的可行性。 相似文献
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双馈感应发电机(DFIG)的变流控制器模型是整个机组模型中的关键部分。变流控制器的参数众多且内外环比例—积分(PI)控制器之间存在级联,常规辨识方法或遇到参数可辨识性问题,或工程实现难度较大。文中提出一种以"分步辨识、交互迭代"为特点,基于二次侧量测信号扰动的控制器参数辨识方法。该方法分别在变流控制器中各PI控制器输入端所用的量测信号上施加扰动,从而突出某个PI控制器在特定量测信号扰动下的作用,并将该PI控制器的可测量控制目标作为观测变量,进而重点辨识其参数。对于存在级联的两个PI控制器,先对后一级PI控制器所用量测信号施加扰动,同时屏蔽前一级PI控制器所用量测信号的变化,从而可实现两个级联PI控制器参数的解耦辨识。该方法可以使变流控制器中每个PI控制器的两个参数在特定的量测信号扰动下被单独辨识,有效保证了参数的可辨识性;而对于全部待辨识参数,可通过多轮交互迭代辨识进一步提高整体辨识精度。 相似文献
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Hao Wang Lina Yao 《International Journal of Adaptive Control and Signal Processing》2019,33(9):1395-1406
In this paper, a new fault diagnosis and fault‐tolerant control method based on the model equivalent transformation is proposed for the stochastic distribution time‐delayed control system, in which the random delay between the controller and the actuator and the external disturbance is considered. The system is modeled by using a linear B‐spline to approximate the probability density function (PDF) of system output. The original system is transformed into an equivalent system without random delay based on the Laplace transformation method. Then, the equivalent system that is converted to the augmentation system with a new state variable is introduced. The observer is designed to estimate the fault information based on the augmentation system. Observer gain matrices and controller parameters are obtained by solving the linear matrix inequality. The PI control algorithm is used to make the PDF of the system output track the desired distribution. Finally, the validity of the proposed method is verified by computer simulation results. 相似文献
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Min Ding Jinhua She Ryuichi Yokoyama Min Wu Weihua Cao 《IEEJ Transactions on Electrical and Electronic Engineering》2015,10(1):36-43
This study employed the equivalent‐input‐disturbance (EID) approach to devise a two‐loop power‐flow control system that controls the output current of an inverter so as to regulate the flow of active and reactive power between a distributed generation unit and a utility grid. It actively eliminates disturbances that degrade the power quality of a microgrid. The pq theory and an all‐pass filter are employed to generate an instantaneous reference current for the control system based on the prescribed active and reactive power of a utility grid terminal. The inner loop consists of a disturbance compensator and a state observer. The disturbance compensator uses information acquired from the state observer to estimate disturbances, such as drops and harmonics in the grid voltage, and compensates for them by incorporating the equivalent input disturbance into the control law. The outer loop consists of a resonance‐based internal model and a state‐feedback controller, which enables the output current of inverter to track the instantaneous reference current. The small‐gain theorem ensures the stability of the system. The system improves the power quality and guarantees that the flow of active and reactive power from the grid and inverter has low harmonic distortion. Simulations demonstrated the effectiveness of the system. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. 相似文献
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Lijuan Li Xingyu Chen Shipin Yang 《International Journal of Adaptive Control and Signal Processing》2021,35(4):459-483
For an industrial control system, controller parameters are important factors that affect the control system performance. This article introduces a controller parameter performance assessment method based on disturbance characteristic variation for a dynamic matrix control system. Assuming that the process model is accurate and the setpoint is constant, disturbance characteristic variation without adjusting controller parameters leads to the degradation of system performance. Hence, the Markov parameters of a disturbance model, which inflect the variation of disturbance characteristics, are used to assess the controller parameter performance. These Markov parameters can be obtained from closed-loop data using the subspace identification method. The differences between the Markov parameters in an actual running state and those in a well-regulated state are used to design the assessing index of controller parameters. The simulation results in the Wood–Berry model and TE process show the validity of the proposed index. 相似文献
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为了实现无人机视轴稳定系统的准确测量与跟踪,设计了经典PID和模糊控制为基础的视轴稳定控制器。在实际工程中PID参数整定过程存在大量不确定性,为了实现PID参数的在线整定,将模糊控制算法与经典PID控制相结合,构造了参数自整定模糊PID控制器,实现了对PID控制器的修正。在MATLAB中的Fuzzy Toolbox和Simulink中,将PID和参数自整定模糊PID进行对比,参数自整定模糊PID控制器在无扰动和10 Hz的正弦扰动的阶跃响应曲线表明,模糊PID相对于模糊控制和PID控制有更短的响应时间和更小的隔离度;在输入为1~10 Hz的系统正弦响应曲线,模糊PID误差最小,控制效果最好。由此可得参数自整定模糊PID在视轴稳定系统中有良好的鲁棒性和控制性能。 相似文献
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基于CMAC的双馈水轮发电机系统控制策略研究 总被引:3,自引:2,他引:3
针对可调速双馈水轮发电机系统的不确定性、非线性和参数时变的特点,提出了一种采用小脑模型(CMAC)神经网络的自适应控制策略。该控制策略以系统动态误差和给定信号量作为CMAC的激励信号,并与自适应神经网络控制器相结合构成系统的复合控制。该文对双馈水轮发电机系统的稳态调节和暂态特性进行了数字仿真研究,并与常规的PID控制进行比较。结果表明,基于CMAC的自适应控制策略对系统模型结构和参数变化、负荷扰动都具有很好的适应性和鲁棒性,控制品质优良,是一种适于在线学习控制的双馈水轮发电机系统控制方法。 相似文献
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A. Patete K. Furuta M. Tomizuka 《International Journal of Adaptive Control and Signal Processing》2008,22(8):795-810
The overall stability of a self‐tuning controller for discrete‐time systems is proved by using the Lyapunov function in this paper, for minimum and a class of non‐minimum phase systems. The self‐tuning controller utilizes a recursive estimate algorithm for the controller parameters based on the generalized minimum variance criterion. Previously, the stability had been proved in the case of minimum phase systems. A new type of self‐tuning controller for the discrete‐time system with delay in control input is also studied which is named the generalized minimum variance criterion‐β equivalent control, and its stability is proved. The simulation is done to evaluate the performance of the proposed self‐tuning controller. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献