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本文给出了加权多步预测控制(WLPC)[1]的递推自适应算法,该算法将每个采样时刻
WLPC算法中计算量很大的极点配置方程求解问题化为一步递推的算法,大大减少了在线计
算量,从而使WLPC成为一种实际可行的算法,本文还证明了其闭环稳定性. 相似文献
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递推广义预测自校正控制器 总被引:21,自引:1,他引:21
本文给出了广义预测自校正控制器的递推算法,用递推平方根法代替最小二乘法估计参
数,改善了计算精度,比牛津大学克拉克等人的算法节省了计算时间.仿真实验表明,该控制
器对系统时延与阶次有很好的鲁棒性,性能优于PID调节器、广义最小方差自校正器与极点
配置自校正器,有较强的抑制干扰能力. 相似文献
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基于ARMAX模型自适应预测函数控制 总被引:10,自引:0,他引:10
本文提出了基于ARMAX模型的自适应预测函数控制,该算法的特点是占用内存少,计算
速度快,并具有较强的鲁棒性.ARMAX模型参数是通过带遗忘因子的递推最小二乘算法在线辨
识得到.仿真结果表明,该控制算法比PID控制具有更好的控制品质. 相似文献
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参数化模型预测空间实现及递推预测算法 总被引:4,自引:0,他引:4
本文给出线性时不变离散系统的参数化模型的预测空间实现的表达式,利用该表达式将传统的参数化模型预测算法化为状态空间递推形式,可大大减小参数化模型预测的在线计算量。为工程上实现自适应参数化模型预测控制带来很大方便。 相似文献
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从算法的实用性出发,对Clark等提出的广义预测控制算法(GPC)进行了改进,通过直接递推控制量参数,得到了更为简洁和易于在计算机上实现的算法。仿真表明,该算法对复杂系统有较强的鲁棒性。 相似文献
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In this paper, an extension of the modified generalized predictive control (GPC) algorithm and a tuning strategy is presented. To take the plant dynamics such as under damped behavior and the effect of zeros into account, extension to the second order plus dead time (SOPDT) of the first order plus dead time (FOPDT) modified GPC method is proposed. It is shown that this method is computationally undemanding. Also, implementation is more straightforward than conventional GPC algorithms. Moreover, the proposed tuning strategy enables a fast implementation of the GPC with regard to nominal stability and desired performance. The simplicity of this strategy and its wide applicability makes it readily accessible to practitioners for utilization. Multiple simulation results are provided to show the effectiveness of the proposed algorithm. 相似文献
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Computationally efficient and numerically robust algorithms for stabilising predictive control are derived. In particular, a static programming (SP) algorithm which takes advantage of the structure in stable GPC and a new dynamic programming (DP) approach are developed and contrasted. Both overcome the numerical difficulties and significantly improve the computational efficiency of some earlier predictive control algorithms with guaranteed stability and moreover it is demonstrated that DP is the more efficient. 相似文献
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基于状态空间模型广义预测控制的并行算法 总被引:5,自引:1,他引:4
本文首先基于脉动阵列经,提出了一种实时参数辨识的并行算法,然后推导出基于状态空间模型广义预测控制的两种新算法,这两种算法都可以通过阵列结构并行实现。 相似文献
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S. Iplikci 《国际强度与非线性控制杂志
》2006,16(17):843-862
》2006,16(17):843-862
In this study, we propose a novel control methodology that introduces the use of support vector machines (SVMs) in the generalized predictive control (GPC) scheme. The SVM regression algorithms have extensively been used for modelling nonlinear systems due to their assurance of global solution, which is achieved by transforming the regression problem into a convex optimization problem in dual space, and also their higher generalization potential. These key features of the SVM structures lead us to the idea of employing a SVM model of an unknown plant within the GPC context. In particular, the SVM model can be employed to obtain gradient information and also it can predict future trajectory of the plant output, which are needed in the cost function minimization block. Simulations have confirmed that proposed SVM‐based GPC scheme can provide a noticeably high control performance, in other words, an unknown nonlinear plant controlled by SVM‐based GPC can accurately track the reference inputs with different shapes. Moreover, the proposed SVM‐based GPC scheme maintains its control performance under noisy conditions. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
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Fast algorithms for generalized predictive control (GPC) are derived by adopting an approach whereby dynamic programming and a polynomial formulation are jointly exploited. They consist of a set of coupled linear polynomial recursions by which the dynamic output feedback GPC law is recursively computed wwith only O(Nn) computations for an n-th order plant and N-steps prediction horizon. 相似文献
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采用遗传算法训练对角递归神经网络预测控制器 总被引:2,自引:0,他引:2
本文提出了一种基于广义预测控制的神经网络预测控制方案.预测控制器由对角递归
神经网络预测控制器和前向神经网络静态补偿器组成.两种神经网络均采用遗传算法进行训
练.仿真实验表明,对于带纯时延的非线性被控对象,采用遗传算法设计的对角递归神经网
络预测控制器具有令人满意的控制性能. 相似文献
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一种广义预测控制的快速算法 总被引:3,自引:0,他引:3
针对传统广义预测控制算法的计算量大这一缺陷 ,通过对未来的控制序列的离线近似计算 ,而只精确求解当前时刻要实施的控制量 ,提出了一种广义预测控制的快速算法。该算法简单 ,不必求解Diophantine方程和逆矩阵 ,大大减小了在线计算量。仿真结果表明 ,该算法具有良好的控制性能 ,而且对控制作用具有较强的约束能力 相似文献
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预测控制算法的内模结构及其统一格式 总被引:14,自引:1,他引:13
本文应用内模控制(IMC)原理,研究了现有各类预测控制算法IMC、MAC、DMC、GPC、GPP的控制器方程,闭环系统输入输出和误差方程,归纳出它们的统一算式,为理解各类预测控制算法的内在联系及进一步研究提供了方便. 相似文献
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针对多变量有约束过程,将一种约束输入的广义预测控制新算法(CPCLC)推广到任意维输入任意维输出(ADLADO)线性系统中,该算法简单,不必解Diophantine方向,而且在求逆矩陈时,与传统的广义预测控制相比,极大地减少了计算器,仿真结果进一步证实了算法的有效性。 相似文献