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本文针对一大批工程实际中经常遇到的非线性系统,为设计低阶控制器,提出了非线性系统的低阶变参数特征模型的原理和方法,论证了所建特征模型与实际对象的等价性。文章介绍了如何根据非线性特征模型设计控制器的基本原则与步骤,文章通过某真空环境温度控制系统的仿真,进一步阐明了这种非线性系统特征建模及其控制的方法,最后给出了利用特征模型进行自适应控制的仿真与实际工程应用的结果。 相似文献
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郭丙君 《自动化与仪器仪表》1999,(2):25-29,38
概述了线件系统的最佳控制设计中存在的问题,根据控制系统的基本性能要求,引入了一类非线性输入控制器,针对二阶系统及高阶系统和非最小相位系统,讨论并设计出这种控制器的参数,最后讨论了该控制器的适应性问题。 相似文献
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模糊滑模变结构控制在AUV纵倾控制中的应用 总被引:1,自引:0,他引:1
无人水下机器人(AUV)在潜浮运动过程中,纵倾角的控制对其在垂直面的运动状态起着关键的作用.尽管目前研究的控制方法对纵倾角有较好的控制效果,但是由于AUV不确定的非线性特性和模型参数,其控制性能并不理想.根据AUV垂直面的非线性模型,在特定的工作点对非线性模型进行了线性化,得到AUV垂直面纵倾运动的数学模型.设计了基于模糊控制理论的模糊滑模变结构控制器调整滑模控制的控制增益,并在海流干扰下用该控制器成功地对AUV进行了纵倾控制.仿真结果验证了该控制方法对运动模型不确定的AUV具有很好的控制性能,在外界干扰下,既保证了控制系统的快速性和鲁棒性,又能够有效地削弱抖振. 相似文献
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对于具有非线性、大时滞、不确定性等特性的难以用精确数学模型描述的多变量复杂系统,靠传统控制理论难以获得理想的控制效果。基于模糊神经网络控制技术不依赖于被控对象精确的数学模型,且能根据被控对象参数的变化自适应调节控制规则和隶属函数参数的特性,进行了采用模糊神经网络控制器实现其控制的应用研究。采用典型的前向型模糊神经网络模型,给出了具有学习功能的多值模糊神经网络控制系统的一种设计方法。仿真实验证明,该系统能够获得较理想的控制效果。 相似文献
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一种基于Matlab的参数自调整模糊控制器的设计方法 总被引:1,自引:0,他引:1
本文介绍了一种在MATLAB的模糊控制工具箱中,通过编写S函数实现对量化因子和比例因子的在线自动调整来设计模糊控制器,从而有效地实现参数自调整模糊控制器的设计方法。为了验证参数自调整模糊控制器的优越性,分别进行了空调温度控制系统的PID控制、常规模糊控制和参数自调整模糊控制的仿真研究。结果表明,参数自调整模糊控制器较之常规的模糊控制器,在被控对象特性变化或较大扰动的情况下,控制系统能保持较好的性能,是一种较理想的控制方法,具有广阔的发展前景。 相似文献
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模糊-PID控制器在空调温度控制中的应用 总被引:1,自引:7,他引:1
该文首先利用计算机仿真软件中的优化工具箱对常规PID控制器中的比例、积分和微分参数进行优化,并且针对中央空调温度控制系统非线性、大滞后的特点,设计了在规则上可调整的模糊控制器,该模糊控制器通过α因子自调整和Ku的自寻优,达到适应和跟踪系统参数变化的目的;而后采用模糊逻辑工具箱和MATLAB函数相结合,方便地实现空调温度控制系统的计算机仿真。仿真结果表明,这种控制方式控制效果优于常规PID控制,有效地改善了系统的动态性能、稳态精度和鲁棒性。 相似文献
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In order to design a nonlinear controller for small-scale autonomous helicopters, the dynamic characteristics
of a model helicopter are investigated, and an integrated nonlinear model of a small-scale helicopter for hovering
control is presented. It is proved that the nonlinear system of the small-scale helicopter can be transformed to a linear
system using the dynamic feedback linearization technique. Finally, simulations are carried out to validate the nonlinear
controller. 相似文献
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蚁群算法滚动优化的LS-SVM预测控制研究 总被引:1,自引:0,他引:1
针对非线性过程预测控制的模型预测和滚动优化问题,提出一种蚁群算法滚动优化的最小二乘支持向量机(LS-SVM)新型预测控制器,该控制器以建模简单、精度高的LS-SVM作为预测模型,蚁群算法作为滚动优化策略,避免了滚动优化中复杂的梯度计算.仿真研究表明,该控制器具有良好的非线性控制效果. 相似文献
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Experiments dealing with the heating of living tissue have resulted in four completely different temperature response characteristics as a result of the application of four different constant power levels. The four response characteristics can be classified as overdamped, critically damped, underdamped, and undamped oscillations. A particular nonlinear, time-delay dynamic equation has previously been shown to exhibit the same type of temperature response characteristics as those in the experiments. Herein, a control strategy is applied to the nonlinear, time-delay equation to inhibit the oscillatory behavior. A proportional plus integral (PI) controller with antiwindup, that is restricted to be nonnegative, is shown to be an effective controller in eliminating the oscillatory responses. This effectiveness is shown by analyzing and explaining the robustness properties of this controller as applied to this nonlinear, time-delay system.This work was supported by National Cancer Institute Grant CA 36428. An earlier version of this article appears in the proceedings of the31st IEEE Conference on Decision and Control. 相似文献
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基于多模型和SVM逆系统单元机组解耦控制 总被引:2,自引:0,他引:2
火力单元机组协调控制系统是一个多变量、强耦合的控制系统,具有非线性、耦合和延迟等特性,其性能直接影响单元机组运行的安全性和经济性.为了有效解决火力单元机组协调控制系统的耦合特性和动态非线性,设计了基于多模型和支持向量机(SVM)逆系统的解耦控制方法,并进行了相应实验研究.针对一个300 MW单元机组的试验仿真模型,得到单元机组在5个典型工作点的线性化模型,然后对每个线性化模型分别设计SVM逆模型及其动态PID控制器,进而用模型线性组合成多模型全局控制系统.通过加权多项式选取合成的多模型控制方法,可以解决负荷大范围变化引起的非线性问题;支持向量机与逆系统的结合能很好地解决非线性系统的强耦合问题.仿真研究证明了这种控制算法设计的有效性和优越性. 相似文献
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《Control Engineering Practice》2000,8(8):937-947
This paper presents the application of a nonlinear controller, using a predictive control strategy, to the distributed collector field of a solar power plant at the Plataforma Solar de Almerı́a (Spain). The design procedure of the controller uses the mathematical input–output model of the plant to find a controller output, using a search strategy that minimizes the cost function for a given prediction horizon. From the basic physical relations that are valid for the heating process of the oil inside the piping different nonlinear models have been deduced for this plant. The parameters of these models are estimated on-line in order to compensate for time-varying effects and modelling errors. The controller has been used in connection with these models to form an adaptive control system and has been applied to the plant. The results of experiments that were carried out in 1998 are presented. 相似文献
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In this paper, a model-based control and state reconstruction of an underground coal gasification (UCG) process is elaborated. In order to deploy model-based control strategies, a sophisticated model of the UCG process based on partial differential equations is approximated with a nonlinear control-oriented model that adequately preserves the fundamental dynamic characteristics of the process. A robust dynamic integral sliding mode control (DISMC) is designed based on the control-oriented model to track the desired heating value, which is one of the key indicators for evaluating the performance of an UCG process. Unknown states required for the model-based control are reconstructed using a gain-scheduled modified Utkin observer (GSMUO). In order to assess the robustness of the nonlinear control and estimation techniques, the water influx phenomenon is considered as an input disturbance. Moreover, the underlying UCG plant model is subjected to parametric variations as well as measurement noise. In order to guarantee the stability of the overall system, the boundedness of the internal dynamics is also proved. To make a fair comparison, the performance of the proposed controller is compared with an integral sliding mode control (ISMC) and a classical proportional-integral (PI) controller. Simulation results highlight the effectiveness of the proposed control scheme in terms of minimum control energy and improved tracking error. Moreover, the simulation study shows that the combination of DISMC and GSMUO exhibit robustness against an input disturbance, parametric uncertainties and measurement noise. 相似文献
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研究船用柴油机控制优化问题,柴油机调速要求快、稳、准。针对船用柴油机调速系统的时变、非线性及外界干扰等特点,传统PID调速稳定时间长,控制效果不佳。为提高喷油量达到控制准确度,改善调速系统性能,提出了一种柴油机自适应遗传非线性PID调速控制策略。采用Matlab对柴油机调速系统模型进行辨识并验证其准确性。利用非线性PID控制实现各参数增益的实时调整,提高了抗干扰能力,通过自适应遗传算法对系统的动态偏差进行监控,优化非线性PID控制器参数,减少了超调量,提高控制精度。仿真结果表明,采用自适应遗传非线性PID控制器稳定时间更短,鲁棒性强,控制精度更高,优化了柴油机调速系统性能。 相似文献