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非线性系统预测控制的多模型方法 总被引:46,自引:1,他引:46
本文在非线性系统的线性化多模型基础上,引入多模型参考轨迹逼近期望轨迹,提出了一
种非线性系统预控制的多模型方法.仿真结果表明,这种方法是有效的. 相似文献
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非线性系统的微分几保控制理论的形成和发展给非线性控制的研究带来了一系列理论上的突破和成果,本文综了近年来微分几何理论在非线性系统解耦控制和线性化方面的应用状况。 相似文献
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关于建模与自适应控制的一体化途径 总被引:23,自引:1,他引:23
在文献自适应辨识预报和控制-多层递阶途经中,我们提出了非线性系统动态线性化
的概念.这种动态线性化仅仅是形式上的,而不是真的线性化.但研究发现,在这种线性化过程
中,包含了一种新的系统辨识思想,那就是在线实时建模一实时反馈控制校正的思想.这种辨识
把建模与反馈控制结合成为一体,突破了参数自适应的框架.实现了控制系统的结构自适应性,
并且避免了建立数学模型这一繁锁的步骤.本文就是对这种系统建模与控制一体化的途径进行
介绍. 相似文献
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蒸发过程的非线性控制仿真研究 总被引:1,自引:0,他引:1
为了研究蒸发过程的非线性控制,对六效逆流蒸发系统的稳态工作点附近建立了动态模型,并将模型转化为仿射非线性系统的形式。接下来应用MIMO的GLC结构对这个非线性系统进行了输入输出线性化,对线性化后的系统应用PI控制律进行控制,并与常规的多回路PID控制做了对比。仿真结果表明,应用输入输出线性化控制策略消除了回路之间的耦合,能够更好地跟踪系统的设定值,并达到了节能降耗的目的。 相似文献
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针对液压马达伺服控制系统由于系统强非线性引起的精确控制困难的问题,提出了基于线性化和滑模控制算法的自适应鲁棒积分滑模控制器.在不改变系统模型的前提下,应用线性化将系统模型中的部分非线性项进行线性化处理,降低了系统的强非线性,并结合自适应算法进行线性化误差补偿.同时,针对跟踪精度不足等问题,引入积分滑模控制算法进行鲁棒控... 相似文献
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基于Lie理论的倒立摆系统的控制算法研究 总被引:1,自引:1,他引:1
该文通过能量反馈和最优控制相结合的方法实现倒立摆系统的自摆起和稳定控制。在摆起阶段采用能量反馈方法实现快速摆起,而在平衡稳定控制阶段,采用一种非线性系统微分几何方法一李理论,对倒立摆系统进行近似线性化,此种线性化方法使模型更多包含原系统主要的非线性部分,更能逼近实际系统,针对采用李理论得到的近似线性化模型,对倒立摆系统进行最优稳定控制设计。仿真和实时控制试验结果表明,文中提出的李理论近似模型线性化方法对于控制器设计结果是有效的,而且采用的能量反馈和最优控制相结合的联合控制策略能够成功实现倒立摆系统的自摆起和稳定控制过程。 相似文献
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For representing the input—output behaviour of a robot manipulator by a linear time-invariant model, four direct linearization schemes are: (i) state linearization, (ii) linearization based on an identification method, (iii) linearization based on neglecting velocity-dependent and gravity terms and (iv) linearization based on neglecting the velocity-dependent term only (rate linearization). In order to make an appropriate choice of linear model for the development of real-time control, these schemes are extensively studied in this paper. It is shown that the rate linearization method leads to a satisfactory tradeoff between computation, accuracy, and stability. In the case of high velocity motions, a combination of state linearization and rate linearization is proposed. 相似文献
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Cascaded feedback linearization and its application to stabilization of nonholonomic systems 总被引:1,自引:0,他引:1
In this paper, a new cascaded feedback linearization problem is formulated and a set of conditions on the cascaded feedback linearizability are established for a class of two-input affine nonlinear systems. The proposed cascaded feedback linearization method enlarges the classes of nonlinear systems which can be dealt with using the feedback linearization technique. In particular, the proposed design can be applied to address the feedback stabilization problem for a few classes of nonlinear systems which have uncontrollable linearization and do not satisfy the standard feedback linearization conditions. As an illustrative application, the proposed cascade feedback linearization concept is used to solve the feedback stabilization problem of nonholonomic systems within the framework of continuously differentiable state feedback control. Simulation results are provided to illustrate the proposed method. 相似文献
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In this paper a new nonlinear feedback control law for continuous stirred tank reactors, obtained by exact Input/Output (I/O) linearization and Sontag's input‐to‐state stability feedback control redesign methods, is studied. By the new feedback control law, a significant attenuation of the disturbance effect is guaranteed, with evident improvement with respect to control laws obtained by the exact I/O linearization method. The performed simulations validate the theoretical results. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
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基于反馈线性化的TCSC滑模控制 总被引:1,自引:0,他引:1
针对含可控串联补偿(Thyristor Controlled Series Compensation,TCSC)的电力系统非线性强及易受外部扰动的特点,应用反馈线性化方法和滑模变结构控制理论,设计了提高系统稳定性的可控串联补偿滑模控制器。通过引入反馈控制变量,基于状态反馈线性化理论实现了对非线性模型的精确线性化。采用极点配置方法设计滑模切换函数,从理论上保证发电机转子方程具有期望的极点。为了减小抖振采用指数趋近律和准滑动模态方法求取滑模控制律,使得设计的可控串联补偿非线性控制律形式简洁,鲁棒性好。为了验证该控制策略的有效性,在Matlab/Simulink环境下建立了基于反馈线性化的可控串联补偿滑模控制系统仿真模型,进行了仿真研究。仿真结果表明,与传统的控制方式相比,设计的控制器能有效地阻尼系统振荡,增强系统的暂态稳定性。 相似文献
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Qiang Gan Harris C.J. 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》1999,29(6):802-817
Model-based methods for the state estimation and control of linear systems have been well developed and widely applied. In practice, the underlying systems are often unknown and nonlinear. Therefore, data based model identification and associated linearization techniques are very important. Local linearization and feedback linearization have drawn considerable attention in recent years. In this paper, linearization techniques using neural networks are reviewed, together with theoretical difficulties associated with the application of feedback linearization. A recurrent neurofuzzy network with an analysis of variance (ANOVA) decomposition structure and its learning algorithm are proposed for linearizing unknown discrete-time nonlinear dynamic systems. It can be viewed as a method for approximate feedback linearization, as such it enlarges the class of nonlinear systems that can be feedback linearized using neural networks. Applications of this new method to state estimation are investigated with realistic simulation examples, which shows that the new method has useful practical properties such as model parametric parsimony and learning convergence, and is effective in dealing with complex unknown nonlinear systems. 相似文献
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G. A. Leonov 《Automation and Remote Control》2009,70(5):800-810
The development of numerical methods, computational engineering, and the applied theory of bifurcations made it possible to consider the application and verification of the harmonic linearization procedure from new positions. The joint application of the harmonic linearization procedure, the classical method of a small parameter, and numerical methods enables calculating the periodic modes of automatic control systems by the multistage procedure, where at the first stage the method of harmonic linearization is used. 相似文献