共查询到18条相似文献，搜索用时 390 毫秒
1.
提出了一种具有地震抑制功能的结构抗震主动控制算法。其特点是设计一组状态反馈控制律，使得闭环结构系统在具有希望极点的同时，还能够减小结构地震输人的影响。首先，在特征结构配置参数化方法的基础上，将该控制问题转化为一个含有约束条件的优化问题；其次，给出了求解该问题的算法及实施步骤，该方法直接基于结构系统原始矩阵，不涉及系统的增广或变换，便于工程应用；最后，对地震作用下三层剪切型Benchmark结构模型进行了仿真分析，结果表明本文所提具有地震干扰抑制功能算法的有效性。 相似文献
2.
基于参数灵敏度最小的鲁棒主动控制方法 总被引：5，自引：2，他引：5
本文建立了带有参数摄动的结构状态空间模型。在此基础上，提出了基于参数灵敏度最小的鲁棒极点配置的主动控制算法，通过使闭环系统的特征值对系统参数变化不敏感来提高结构控制系统对参数摄动的鲁棒性。最后对一个单自由度结构地震作用下的控制仿真计算，证实了这种控制方法的有效性和较强的鲁棒性。 相似文献
3.
结构动力灵敏度分析中的几个问题 总被引：3，自引：0，他引：3
结构动力灵敏度分析是进行抗震结构优化设计和考虑参数不确定性进行动力可靠性分析的基本步骤。本文就结构动力分析中几个常用的计算过程进行灵敏度分析研究,给出了Choleskey分解矩阵及其它常用数学变换的灵敏度计算表达,分析了振型灵敏度的传递作用,指出对于一般的剪切型结构可以不考虑振型及振型参与系数的灵敏度,从而使问题大为简化。本文还讨论了结构动力反应与各基本参数的灵敏度之间的关系,提出了直接通过结构地震反应得到灵敏度谱的设想。作者认为,通过大量的统计分析可以得到工程上实用的地震反应灵敏度谱。 相似文献
4.
龙复兴 《地震工程与工程振动》1994,14(1):24-29
本文讨论结构控制系统的极点配置问题，文中用典型变换将闭环系统解耦，从而把与待配置极点对应的振型分离出来逐一分别研究，文中直接建立了状态反馈增益矩阵和输出反馈增益矩阵的显式表达式，无需迭代，计算简单，应用方便。 相似文献
5.
基于状态反馈的结构鲁棒控制 总被引：8，自引：0，他引：8
本文采用基于状态反馈的鲁棒控制方法解决地震作用下结构控制问题，首先将结构的运动方程转化为状态方程，利用鲁棒控制方法设计了系统的状态反馈控制律；通过引入控制力权重系数，合理地平衡了控制效果与控制力的关系；对于地震作用下的三层框架模型。仿真验证了该控制方法的有效性，并讨论了各种参数对控制效果的影响。 相似文献
6.
地震作用下参数不确定系统的变结构控制 总被引：5，自引：2，他引：3
本文对结构参数具有有确定性的变结构控制系统设计方法进行了研究。首先采用摄动方法给出了结构参数具有确定性的控制系统的运动方程,证明了基于层间剪切模型的参数不确定受控系统与其标称系统具有相同的滑动模态,从而解决了系统切换函数的确定问题,并利用到达条件推导了控制律的表示式。算例分析结果表明,本文的控制方法能有效地减小结构的地震响应,对于结构系统建模存在误差或系统本身存在学确定性的情况,控制效果仍十分显著 相似文献
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工程结构地震破坏概率矩阵分析 总被引：3，自引：0，他引：3
本文提出了一种计算工程结构地震坡坏概率矩阵的方法，建立了地震地面运动模型和结构分析模型，对结构进行了随机地震反应分析，并获得了结构随机分应的统计量，进而采用双参数的结构破坏模型，给出了教育处结构地震破坏概率的表达式，利用此方法计算了一座按8度要求设计的钢筋混凝土框架型，给出了计算结构地震坡坏概率的表达式，利用此方法计算了一座按8度要求的钢筋混凝土框架结构的地震破坏概率矩阵，本文提出了方法可以在确定抗震设防标准和进行震害预测时采用。 相似文献
9.
考虑参数不确定性的结构抗震鲁棒H∞控制 总被引：1，自引：0，他引：1
基于线性矩阵不等式方法,本文给出了一种新的考虑参数不确定性的鲁棒H∞控制器设计方法,并用于建筑结构的抗震控制。假定结构不确定参数是范数有界的,通过有界实引理,把考虑参数不确定性的鲁棒H∞控制器设计化为具有线性矩阵不等式约束的凸优化问题,进而可以应用内点法等凸优化技术进行求解。以6层建筑结构在Kobe地震动输入和突加Kanai—Tajimi过滤白噪声随机地震激励下的抗震控制为例,进行了数值仿真。数值结果表明,鲁棒H∞控制器具有很强的鲁棒性,无论结构刚度和阻尼是否存在变异,均能实现很好的控制效果。 相似文献
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11.
F. A. El-Awar J. W. Labadie T. B. M. J. Ouarda 《Stochastic Environmental Research and Risk Assessment (SERRA)》1998,12(4):247-266
: As with all dynamic programming formulations, differential dynamic programming (DDP) successfully exploits the sequential
decision structure of multi-reservoir optimization problems, overcomes difficulties with the nonconvexity of energy production
functions for hydropower systems, and provides optimal feedback release policies. DDP is particularly well suited to optimizing
large-scale multi-reservoir systems due to its relative insensitivity to state-space dimensionality. This advantage of DDP
encourages expansion of the state vector to include additional multi-lag hydrologic information and/or future inflow forecasts
in developing optimal reservoir release policies. Unfortunately, attempts at extending DDP to the stochastic case have not
been entirely successful. A modified stochastic DDP algorithm is presented which overcomes difficulties in previous formulations.
Application of the algorithm to a four-reservoir hydropower system demonstrates its capabilities as an efficient approach
to solving stochastic multi-reservoir optimization problems. The algorithm is also applied to a single reservoir problem with
inclusion of multi-lag hydrologic information in the state vector. Results provide evidence of significant benefits in direct
inclusion of expanded hydrologic state information in optimal feedback release policies. 相似文献
12.
F. A. El-Awar J. W. Labadie T. B. M. J. Ouarda 《Stochastic Hydrology and Hydraulics》1998,12(4):247-266
: As with all dynamic programming formulations, differential dynamic programming (DDP) successfully exploits the sequential
decision structure of multi-reservoir optimization problems, overcomes difficulties with the nonconvexity of energy production
functions for hydropower systems, and provides optimal feedback release policies. DDP is particularly well suited to optimizing
large-scale multi-reservoir systems due to its relative insensitivity to state-space dimensionality. This advantage of DDP
encourages expansion of the state vector to include additional multi-lag hydrologic information and/or future inflow forecasts
in developing optimal reservoir release policies. Unfortunately, attempts at extending DDP to the stochastic case have not
been entirely successful. A modified stochastic DDP algorithm is presented which overcomes difficulties in previous formulations.
Application of the algorithm to a four-reservoir hydropower system demonstrates its capabilities as an efficient approach
to solving stochastic multi-reservoir optimization problems. The algorithm is also applied to a single reservoir problem with
inclusion of multi-lag hydrologic information in the state vector. Results provide evidence of significant benefits in direct
inclusion of expanded hydrologic state information in optimal feedback release policies. 相似文献
13.
The paper deals with gray box identification of flexible structures and active vibration suppression from a robust control perspective. First, the linearized mathematical model of an N‐storey flexible structure is presented. Next, the generalized mathematical model is particularized for the investigated three‐storey flexible structure. The considered flexible structure is identified based on black box and gray box identification methods and the model's parametric uncertainties are deduced. Furthermore, control constraints are presented for the design problem, in case of velocity as well as acceleration feedback, from a robust control perspective. Finally, the effectiveness of the control system is tested through experiments, when the input disturbance is assumed to be a sinusoidal one as well as a historical earthquake record (1940 El Centro record). Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
14.
It is well known that the classical optimal control method requires all the state variables of the controlled system to be measurable and available for control feedback. However, for a high‐order or complex system some state variables are possibly unmeasurable in practice. In addition, the control cost will be higher if more sensors are used, because it is expensive to install sensors. On the other hand, when using the optimal control method with full‐state feedback, some state variables in control feedback have only a small effect on control performance. Neglecting these state variables does not affect the control performance greatly. Good control effectiveness can be obtained by using only the state variables that have a big effect on the control performance. So the questions become how to determine those state variables which have a big effect on the control performance? and how to design the optimal controller using only the determined state variables? The discrete sub‐optimal control method with partial‐state feedback is investigated in this paper. Firstly, the continuous control system and performance index are both transformed into discrete forms. Then the state variables, which have a big effect on the control performance, are determined using the second‐order sensitivity which is the second‐order derivative of the performance index with respect to control gain. The sub‐optimal controller is finally designed using only the determined state variables. Numerical examples are worked out to demonstrate the application of the proposed control algorithm. It is shown that the relative importance of each state variable can be indicated clearly by the second‐order sensitivity. The sub‐optimal control method presented is effective in reducing maximum responses of the structure. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
15.
A reliability‐based output feedback control methodology is presented for controlling the dynamic response of systems that are represented by linear state‐space models. The design criterion is based on a robust failure probability for the system. This criterion provides robustness for the controlled system by considering a probability distribution over a set of possible system models with a stochastic model of the excitation so that robust performance is expected. The control command signal can be calculated using incomplete response measurements at previous time steps without requiring state estimation. Examples of robust structural control using an active mass driver on a shear building model and on a benchmark structure are presented to illustrate the proposed method. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
16.
The integrated optimum problem of structures subjected to strong earthquakes and wind excitations, optimizing the number of actuators, the configuration of actuators and the control algorithms simultaneously, is studied. Two control algorithms, optimal control and acceleration feedback control, are used as the control algorithms. A multi‐level optimization model is proposed with respect to the solution procedure of the optimum problem. The characteristics of the model are analysed, and the formulation of each suboptimization problem at each level is presented. To solve the multi‐level optimization problem, a multi‐level genetic algorithm (MLGA) is proposed. The proposed model and MLGA are used to solve two multi‐level optimization problems in which the optimization of the number of actuators, the positions of actuators and the control algorithm are considered in different levels. In problem 1, an example structure is excited by strong wind, and in problem 2, an example structure is subjected to strong earthquake excitation. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
17.
Impact of sensor measurement error on sensor positioning in water quality monitoring networks 总被引：1，自引：1，他引：0
This paper studies the impact of sensor measurement error on designing a water quality monitoring network for a river system, and shows that robust sensor locations can be obtained when an optimization algorithm is combined with a statistical process control (SPC) method. Specifically, we develop a possible probabilistic model of sensor measurement error and the measurement error model is embedded into a simulation model of a river system. An optimization algorithm is used to find the optimal sensor locations that minimize the expected time until a spill detection in the presence of a constraint on the probability of detecting a spill. The experimental results show that the optimal sensor locations are highly sensitive to the variability of measurement error and false alarm rates are often unacceptably high. An SPC method is useful in finding thresholds that guarantee a false alarm rate no more than a pre-specified target level, and an optimization algorithm combined with the thresholds finds a robust sensor network. 相似文献
18.
Time-delay causes unsynchronized application of the control forces which may not only degrade the performance of the control system but also even induce instability to the dynamic system. Time-delay control algorithm is developed in this paper to solve this practical problem. The control system is first formulated in discrete-time form. In the presence of time-delay, the motion equation of the discrete-time control system remains a difference equation which can be transformed into first-order difference equation by augmenting the state variables. Optimal time-delay control algorithm is derived based on the augmented system. The time-delay control forces are simply generated from the time-delay states multiplied by the constant feedback gain. Numerical simulation is illustrated to verify the feasibility of the proposed control algorithm. Since time-delay effect is incorporated in the mathematical model for the structural control system throughout the derivation of the proposed algorithm, system performance and dynamic stability are guaranteed. 相似文献