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研究了智能桁架结构最优振动控制和作动器的优化配置问题。首先采用有限元方法,根据Hamilton原理推导了智能桁架结构的机电耦合动力学方程,根据线性二次型最优控制理论,推导了结构振动控制的数学模型,通过最小化性能泛函,求解黎卡提矩阵代数方程确定了最优控制输入。然后通过对最优控制性能指标函数的修正,得到了与初始状态无关的性能指标,以修正的性能指标为目标函数,应用模拟退火算法对作动器位置进行了优化配置。最后给出了空间智能桁架结构振动控制算例验证建模过程和算法。算例结果表明,通过最优振动控制可以使结构振动快速衰减,达到振动抑制的效果,而且通过模拟退火算法可以确定最佳的作动器布置方式。 相似文献
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讨论了柔性结构振动的混合H2/H∞最优控制问题,结构振动控制器的鲁棒稳定性转化为H∞最优控制问题,以及振动控制的最优二次性能转化为H2最优控制问题,并提出了利用遗传算法求解了H2/H∞的方法,通过结构振动主动控制的计算机仿真,表明用遗传优化算法解H2/H∞最优控制是有效的。仿真结果还表明,H2和H∞性能指标是相互矛盾的。本方法能有效地处理H2和H∞性能指标的折衷问题,以得到闭环系统的鲁棒稳定性和良 相似文献
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结构振动的H_2/H_∞混合最优控制 总被引:3,自引:0,他引:3
讨论了柔性结构振动的混合H2/H∞最优控制问题、结构振动控制器的鲁棒稳定性转化为H∞最优控制问题,以及振动控制的最优二次性能转化为H2最优控制问题,并提出了利用遗传算法求解H2/H∞的方法。通过结构振动主动控制的计算机仿真,表明用遗传优化算法解H2/H∞最优控制是有效的。仿真结果还表明,H2和H∞性能指标是相互矛盾的,本方法能有效地处理H2和H∞性能指标的折衷问题,以得到闭环系统的鲁棒稳定性和良好的时域性能。 相似文献
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研究带有两个动量飞轮的刚体航天器姿态控制问题。在系统角动量为零的情况下,系统的控制问题可转化为无漂移系统的非完整运动规划问题。利用最优控制方法和样条逼近技术提出求解带有2个动量飞轮航天器姿态的运动规划控制的粒子群优化算法。运动规划的最优控制是光滑的,且初值和终值均为零,可以方便地通过伺服电机实现飞轮的控制。数值仿真表明:该方法对航天器姿态运动规划控制是有效的。 相似文献
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在磁流变智能结构的减震控制中,结构的位移控制和加速度控制是其减震控制的两个重要控制目标,这就使得磁流变智能结构的减震控制成为了一多目标优化控制。为此,本文采用微粒群优化控制算法同时对磁流变智能结构的位移和加速度进行了最优控制分析,实现了磁流变智能结构多目标的优化减震控制。并对一每层各安装一个磁流变阻尼器的五层钢结构分别采用微粒群优化控制算法、ON控制算法和OFF控制算法进行了实例对比分析,结果表明:采用微粒群优化控制可显著地减小结构的位移反应,同时也可一定程度地减小结构的加速度反应。 相似文献
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Abstract This paper focuses on the development of a solver for solving optimal control problems. A developed numerical optimal control module integrated with the Sequential Quadratic Programming method is introduced. An optimal control problem solver based on the proposed method is implemented to solve optimal control problems efficiently in engineering applications. In addition, a systematic procedure for solving optimal control problems by using the optimal control problem solver is also proposed. A time‐optimal benchmark problem presented in the literature is used to illustrate for the capability and facility of solving optimal control problems. The numerical results demonstrate the proposed method and the procedure suggested in this paper are helpful to engineers in solving optimal control problems in a systematic and efficient manner. 相似文献
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基于随机平均的非线性随机最优控制 总被引:1,自引:0,他引:1
首先建立非线性随机系统的最优控制问题,并介绍通过随机平均法导出平均系统、再由随机动态规划原理确定控制律的平均系统的非线性随机最优控制方法。然后,对于非线性随机系统的动态规划方程,提出应用随机平均法简化该方程、从而得到最优平均控制律的方法,并证明该最优平均控制律等价于平均系统的最优控制律。最后用一个例子说明方法及等价性,并指出在一定条件下,最优平均控制律将是动态规划方程的精确解。 相似文献
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拉索作动器已被引入结构振动控制中,但作动器具有单边饱和的非线性特点,因此,拉索控制难以直接采用要求控制无约束的LQG对结构振动进行控制律设计。针对拉索的单边饱和特点,提出了一种用分段性能指标代替原有的二次型性能指标的最优控制方法。将拉索的单边饱和特性考虑在内并以合适的抑制速度对结构振动进行控制。并证明了直接用LQG方法对结构振动进行控制律设计,通过拉索控制器取单边和饱和之后作用于结构也是一种最优控制。同时证明了加观测器的最优控制系统对结构振动控制是稳定的。对一悬臂梁振动进行数值仿真控制,结果验证了该最优控制率的可行性。 相似文献
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本文以配置两对光致伸缩驱动器的简支板为控制对象,提出了最优控制与模糊控制相结合的最优模糊主动控制算法。考虑到光致伸缩驱动器的非线性驱动特性,首先由最优控制获得光电层合简支板多模态振动的期望控制量, 再通过模糊控制器使光致伸缩驱动器光致应变逼近该控制量, 从而实现对简支板的多模态振动控制。在最优模糊控制器设计过程中,模糊控制的设计与最优控制设计是相互独立的。仿真结果表明, 最优模糊控制能够有效实现光电层合简支板的多模态振动抑制,控制效果明显优于直接最优状态反馈控制。 相似文献
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It is well known that the optimal control of a linear quadratic model is characterized by the solution of a Riccati differential equation. In many cases, the corresponding Riccati differential equation cannot be solved exactly such that the optimal feedback control may be a complex time-oriented function. In this article, a parametric optimal control problem of an uncertain linear quadratic model under an optimistic value criterion is considered for simplifying the expression of optimal control. Based on the equation of optimality for the uncertain optimal control problem, an approximation method is presented to solve it. As an application, a two-spool turbofan engine optimal control problem is given to show the utility of the proposed model and the efficiency of the presented approximation method. 相似文献
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The control of probabilistic Boolean networks as a model of genetic regulatory networks is formulated as an optimal stochastic control problem and has been solved using dynamic programming; however, the proposed methods fail when the number of genes in the network goes beyond a small number. There are two dimensionality problems. First, the complexity of optimal stochastic control exponentially increases with the number of genes. Second, the complexity of estimating the probability distributions specifying the model increases exponentially with the number of genes. We propose an approximate stochastic control method based on reinforcement learning that mitigates the curses of dimensionality and provides polynomial time complexity. Using a simulator, the proposed method eliminates the complexity of estimating the probability distributions and, because the method is a model-free method, it eliminates the impediment of model estimation. The method can be applied on networks for which dynamic programming cannot be used owing to computational limitations. Experimental results demonstrate that the performance of the method is close to optimal stochastic control. 相似文献
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Mehmet Bakioglu Unal Aldemir 《International journal for numerical methods in engineering》2001,50(12):2601-2616
Exact optimal classical closed–open‐loop control is not achievable for the buildings under seismic excitations since it requires the whole knowledge of earthquake in the control interval. In this study, a new numerical algorithm for the sub‐optimal solution of the optimal closed–open‐loop control is proposed based on the prediction of near‐future earthquake excitation using the Taylor series method and the Kalman filtering technique. It is shown numerically that how the solution is related to the predicted earthquake acceleration values. Simulation results show that the proposed numerical algorithm are better than the closed‐loop control and the instantaneous optimal control and proposed numerical solution will approach the exact optimal solution if the more distant future values of the earthquake excitation can be predicted more precisely. Effectiveness of the Kalman filtering technique is also confirmed by comparing the predicted and the observed time history of NS component of the 1940 El Centro earthquake. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
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Conservation of generalized momentum maps in mechanical optimal control problems with symmetry 下载免费PDF全文
Peter Betsch Christian Becker 《International journal for numerical methods in engineering》2017,111(2):144-175
In this paper, a structure‐preserving direct method for the optimal control of mechanical systems is developed. The new method accommodates a large class of one‐step integrators for the underlying state equations. The state equations under consideration govern the motion of affine Hamiltonian control systems. If the optimal control problem has symmetry, associated generalized momentum maps are conserved along an optimal path. This is in accordance with an extension of Noether's theorem to the realm of optimal control problems. In the present work, we focus on optimal control problems with rotational symmetries. The newly proposed direct approach is capable of exactly conserving generalized momentum maps associated with rotational symmetries of the optimal control problem. This is true for a variety of one‐step integrators used for the discretization of the state equations. Examples are the one‐step theta method, a partitioned variant of the theta method, and energy‐momentum (EM) consistent integrators. Numerical investigations confirm the theoretical findings. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献