基于内模PID鲁棒控制的电阻炉炉温控制系统

针对电阻炉温度被控对象的纯滞后特性，设计了内模PID鲁棒控制器。结果表明，内模PID鲁棒控制器具有良好的抗干扰性和鲁棒性，且参数整定简单，可有效改善系统的控制效果。     

电厂热工智能控制系统的研究

火电厂的主汽温是大惯性、大滞后的对象,并且动态特性随机组符合变化而变化,运行过程中扰动多.采用模型参考自适应控制的思想,将模糊控制方法和内模控制方法结合在一起,提出了一种模型参考模糊自适应内模控制方法.此方法综合了模糊控制,内模控制和自适应控制的优点,增强了系统的鲁棒性,针对电厂热工过程系统的仿真研究结果证明了此方法的有效性.     

鲁棒二自由度PID控制

针对工业过程控制对象,将内模控制与二自由度PID控制有机结合,提出一种鲁棒二自由度PID控制方法,可以有效抑制参数变化对系统的影响,使系统同时获得良好的目标值跟踪特性、干扰抑制特性和鲁棒性.理论分析和仿真结果表明了这一方法的有效性.     

变论域模糊自整定PID内模控制在主汽温控制系统中的应用研究

火电厂主汽温控制系统具有大惯性、大延迟和时变等特性,采用常规PID串级控制方法难以获得满意的控制效果。通过引入1／1pade级数逼近纯滞后环节,将内模控制转换为常规PID控制器的参数的整定,运用变论域模糊控制原理来整定PID参数,从而实现了变论域模糊自整定PID内模控制。它充分综合了变论域模糊控制、内模控制、PID控制的优点。通过对锅炉过热蒸汽温度控制系统的仿真研究表明,变论域模糊自整定PID内模控制的控制效果优于常规的PID串级控制,它能适应对象参数的变化,具有较强的鲁棒性和自适应能力,控制品质好。     

锂电池叠片机隔膜纠偏神经近似内模及迭代学习复合控制

为了解决叠片过程中隔膜对齐度较差的问题,采用神经近似内模和迭代学习控制相结合的方法设计控制器来改进隔膜的纠偏效果,提出一种神经网络近似内模及迭代学习复合控制的隔膜纠偏控制算法。首先针对影响隔膜对齐度的复杂特性导致难以用物理数学模型去描述纠偏过程的问题,采用神经网络的优秀的非线性逼近能力建立纠偏系统的神经网络模型。其次为了提升系统的鲁棒性以及避免系统模型的非仿射非线性特性,采用一种神经近似内模对纠偏系统进行控制,仿真表明神经近似内模对纠偏系统能取得较好的控制效果,但是对周期性扰动的抑制能力有限。然而在锂电池叠片过程中,速度和张力的规律性变化会对隔膜偏移误差产生周期性的干扰。最后将迭代学习控制引入到神经近似内模控制中以应对纠偏系统的周期性扰动,仿真表明引入迭代学习控制后,纠偏系统的周期性扰动得到有效地抑制。试验结果表明所提出的纠偏控制算法可以有效地提升锂电池叠片机放卷系统的隔膜对齐度。     

电动静液压主动悬架的内模-Smith时滞补偿控制

提出一种内模-Smith时滞补偿控制方法进行电动静液压主动悬架的时滞控制。对电动静液压作动器(Electro-Hydrostatic Actuator,EHA)进行了响应特性试验,采用一维线性插值方法对试验数据进行了模型拟合,并得到了含纯时滞的作动器简化模型。针对作动器的惯性响应设计了内模控制器,利用一阶泰勒表达式转化成了PID控制器形式;将作动器的纯时滞视为理想主动力的时滞,设计了Smith时滞补偿控制器。搭建了EHA主动悬架的内模-Smith时滞补偿控制仿真模型,并进行了仿真分析。结果表明,内模-Smith时滞补偿控制能使作动器输出的主动力在时间上得到较好的控制,明显改善了主动悬架的动态性能。     

基于频域分析的预测控制鲁棒性设计

从分析预测控制的内模机理出发，把系统稳定鲁棒性和品质鲁棒性要求作为内模控制器设计的两个约束条件，利用控制理论中频域分析的方法把离散控制系统的控制器设计转化到频域进行分析，推导出满足系统稳定鲁棒性和品质鲁棒性条件的内模控制器，从而得出预测控制鲁棒性设计的条件，使控制系统能较好的抑制外部扰动所产生的影响。仿真实验结果表明该设计比传统的CHR和Cohen-Coon整定算法有更优异的控制效果。     

永磁同步风力发电机的神经网络自适应内模控制

为了提高永磁同步风力发电机的调速性能,结合自适应内模控制,将神经网络方法用于永磁同步风力发电机调速控制系统,设计了神经网络自适应速度控制器。基于MATLAB的仿真结果证明,神经网络自适应内模控制系统有很强的自适应能力和抗负载扰动能力,控制系统具有良好的静、动态特性。     

基于内模的光纤陀螺温控系统设计

本文针对光纤陀螺对温度敏感这一特性,在充分分析光纤陀螺物理特性基础上,分析了温度对陀螺噪声、陀螺光源的影响,温度的变化将导致光线环中不同区段上光纤的折射率不同,这种不同将最终导致光纤陀螺的零点随温度的变化而发生漂移;随后建立了相应的温度误差模型;通过最小二乘拟合,建立了较为准确的控制对象模型,采用内模控制方法对温控系统进行了设计,其设计原理简单、跟踪调节性能好、鲁棒性强、参数整定直观明了,能消除不可测干扰的影响;最后通过系统仿真,对分别用内模控制和常规PID控制设计的温控系统进行了比较,通过比较分析,验证了内模控制对于本系统所具有的优越性,研究成果对设计高精度温度控制系统有着重要的参考价值。     

考虑延迟的线控转向二自由度内模控制

针对线控转向系统中由于信号传输、机械间隙和摩擦等因素引起的响应延迟问题，设计了二自由度内模控制策略以提高转角跟踪精度。将延迟模型与线控转向系统模型相结合，构建新的名义模型，为避免引入非最小相位项，采用全极点近似方法将延迟环节线性化，求解跟踪控制器和抗干扰控制器。与名义模型不含延迟环节的二自由度内模控制以及经典PID控制相比较，通过MATLAB/Simulink仿真给出了延迟量对三种方法跟踪性能的影响。比较了延迟量对采用全极点近似、Taylor近似和Padé近似的二自由度内模控制跟踪性能的影响。经线控转向台架试验验证，采用全极点近似的二自由度内模控制跟踪精度较高，对延迟的适应性较好。     

基于阶跃响应的反向响应过程的预测函数控制

通过分析被控过程产生反向响应的内在机理,基于过程阶跃响应系数利用预测函数控制算法实现反向响应过程的控制。将系统控制结构归结为内模控制结构,并在此基础上给出控制系统的鲁棒稳定性证明。该方法的优点是所得控制器结构简单、参数易于调节,且所给方法也适用于其他非最小相位系统的控制。实验结果证实该方法有很强的抗干扰能力和较好鲁棒性。     

基于扰动观测器的内模控制在工业过程中的应用研究

介绍了一种工业生产过程中的复合控制方法.该方法结合了内模控制算法和改进的扰动观测器算法,解决了工业生产过程中因扰动导致常规PID控制效果欠佳的问题.理论分析和仿真实验表明,该方法控制效果明显优于常规PID控制,并能有效抑制各种扰动.     

精密内圆磨削过程的灰色系统模型研究与质量控制系统设计

预报补偿与控制技术是提高精密内圆磨削质量的有效途径。在分析轴承内圈内圆磨削质量的基础上，指出精密内圆磨削过程可视为一典型的灰色系统，灰色系统ＧＭ（１，１）模型将有助于进一步认识内圆磨削过程的本质。建模仿真结果表明，ＧＭ（１，１）模型可以较好地描述工件磨削尺寸误差序列的趋势项，基于此，就可以对内圆磨削过程实施预报补偿控制。设计了旨在提高轴承内圈内圆磨削质量和效率的控制系统。     

时滞系统的内模控制设计及仿真

在被控对象与模型失配情况下,Smith预估控制往往难以达到满意的效果。针对具有此种情况的纯滞后工业过程,提出了一种内模控制设计方法;通过仿真结果表明,内模控制能克服被控对象增益和时间常数变化对控制性能的影响,有较强的鲁棒性和抗干扰能力。     

Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle

In this paper, the nonminimum phase problem of a flexible hypersonic vehicle is investigated. The main challenge of nonminimum phase is the prevention of dynamic inversion methods to nonlinear control design. To solve this problem, we make research on the relationship between nonminimum phase and backstepping control, finding that a stable nonlinear controller can be obtained by changing the control loop on the basis of backstepping control. By extending the control loop to cover the internal dynamics in it, the internal states are directly controlled by the inputs and simultaneously serve as virtual control for the external states, making it possible to guarantee output tracking as well as internal stability. Then, based on the extended control loop, a simplified control-oriented model is developed to enable the applicability of adaptive backstepping method. It simplifies the design process and releases some limitations caused by direct use of the no simplified control-oriented model. Next, under proper assumptions, asymptotic stability is proved for constant commands, while bounded stability is proved for varying commands. The proposed method is compared with approximate backstepping control and dynamic surface control and is shown to have superior tracking accuracy as well as robustness from the simulation results. This paper may also provide a beneficial guidance for control design of other complex systems.     

带积分作用的模糊内模时滞控制器

将Smith预估器和内模控制结构结合起来，使用模糊控制器为主控制器，并用积分环节来消除系统所存在的稳态误差，理论分析可以证明，该结构就是内模控制器，无需滤波环节就可以得到良好的鲁棒性，而模糊控制器本身的非线性和鲁棒性也可以改善系统的动态性能和鲁棒性，经仿真研究发现，只要合理调整模糊比例因子和积分因子，该方法可以在一定的模型失配情况下得到比常规IMC更好的控制品质，且无稳态误差。     

A Conceptual Approach to Integrate Design and Control for the Epoxy Dispensing Process

Performance improvement of manufacturing systems in the semiconductor industry involves interdisciplinary expertise, such as physical modeling, mechanical design, electrical control, and even material science. Integration of these different disciplines is a challenging problem in the semiconductor industry. The paper presents a conceptual approach to integrate design and control methodology for complex processes with specific application to an epoxy-dispensing control system – a critical equipment in the semiconductor packaging process. This methodology includes three hierarchical levels: process design (system-level and component-level), multivariable control and the statistics-based supervision. This paper deals with conceptual design at system-level by integrating an approximate model with an axiomatic approach, and briefly introduces approaches at other levels. In the conceptual design at system level, the primitive model of the system is sufficient to show some basic properties of the process, by which the axiomatic design can be easily integrated to evaluate the system design and suggest an optimal system configuration with invariant properties to internal variations. Under minimal internal variation, the multivariable control that is intended to suppress external variations can be approximately constructed by a set of independent controllers. Statistics-based supervision will provide suitable setpoints for the multivariable control so as to maintain good performance in the dynamic environment.     

Vehicle active steering control research based on two-DOF robust internal model control

Because of vehicle’s external disturbances and model uncertainties, robust control algorithms have obtained popularity in vehicle stability control. The robust control usually gives up performance in order to guarantee the robustness of the control algorithm, therefore an improved robust internal model control(IMC) algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness. The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties. In order to separate the design process of model tracking from the robustness design process, the improved 2 degree of freedom(DOF) robust internal model controller structure is given from the standard Youla parameterization. Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm, on the basis of a nonlinear vehicle simulation model with a magic tyre model. Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance, which can enhance the vehicle stability and handling, regardless of variations of the vehicle model parameters and the external crosswind interferences. Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.     

基于SVM的内模控制算法在船舶航向中的应用

基于SVM的内模控制,采用SVM回归理论建立系统的内部模型和设计逆模控制器。首先简要介绍了SVMR的原理,然后将其应用于内摸控制问题.并建立了SVMR模型。其次,在控制过程可逆的条件下设计了SVMR控制器。最后将该控制方法用于具有大时滞性、非线性和不确定性的船舶航向控制中,仿真结果表明了该方法的合理性和有效性。     

Internal model control structure using adaptive inverse control strategy

In this paper, we propose a new adaptive internal model control scheme based on adaptive finite impulse response filters. This scheme provides the same design procedure for both minimum and nonminimum phase plants. The plants under consideration may contain time delay. The tracking objective is accomplished for both invertible and noninvertible stable plants. The internal model of the plant and its inverse are estimated by recursive least-squares and least-mean-squares algorithms, respectively. The closed loop is designed such that the system from the reference input to the plant output can be approximately represented by a pure delay. The effect of the process zeros on the output is compensated by using adaptive finite impulse response filters. This avoids the cancellation of noncancellable zeros of the plant and forces the plant output to track the reference input with a delay. The stability of the closed loop for both minimum and nonminimum phase systems is guaranteed. Computer simulation and laboratory scale experimental results are included in the paper to demonstrate the effectiveness of the proposed method.