遗传算法在结构振动主动控制中的应用研究

基于遗传算法，对简支梁振动主动控制的传感器/作动器位置优化问题，提出了一种以结构总储能量小为优化目标的数学模型，并编制了遗传算法软件包Ga205对此模型进行优化计算，结果表明，较之穷举法，用遗传算法解决感器/作动器进行位置优化问题是高效的，同时也是全局收敛的。     

Genetic approach to optimal topology/controller design of adaptive structures

Integrated optimization of structural topology and control system is considered. The problem is formulated as mixed discrete-continuous multi-objective programming with a linear quadratic regulator cost index, and measures of robustness and controllability as objectives. The Genetic Algorithm (GA), a guided random search technique, is adopted for the problem-solving. A member elimination strategy that allows deleted members to be recovered is suggested in the search procedure. As verification for the proposed method, optimum layout and actuator placement for a 45-bar truss is illustrated. Numerical results indicate that the genetic algorithm can converge to optimum solutions by searching only a minor fraction of the solution space. Discussions on the algorithm are presented. © 1998 John Wiley & Sons, Ltd.     

Integrated structure and control design of actively controlled structures using substructure decomposition

This paper presents a substructuring based approach to the combined structure and control system design problem for flexible space structures. The proposed approach involves decomposing the structure to be controlled into a number of substructures. The substructure information obtained through finite element analysis is synthesized to reconstruct a reduced order model for the entire structure. Two approaches for controller design based on linear quadratic regulator (LQR) theory are proposed. The first approach involves designing a controller for the entire structure obtained by assembling individual substructures. For the second approach, the global controller is obtained by assembling all subcontrollers designed at the substructure level. The integrated control/structure design problem is solved iteratively until a minimum weight design is achieved. A numerical example which compares the results obtained from both the methods with those obtained by directly synthesizing a global controller for the entire structure is presented. The results indicate that both methods proposed herein provide good agreement with the results obtained by analyzing the structure in its entirety.     

A hybrid fuzzy/genetic algorithm for the design of offshore oil production risers

This work presents the development and implementation of a synthesis and optimization procedure based on genetic algorithms (GA). A modified version of the basic GA, consisting in a hybrid fuzzy–GA, is considered. The performance of the optimization procedure is improved by employing linguistic knowledge and uncertainties inherent of human thinking. This eases the definition of the penalty and global objective functions that would be required in a standard GA procedure, which is not a simple task since it involves subjective assumptions. The application of the proposed procedure is focused on the design of steel catenary risers (SCRs) for floating oil production units at deep and ultra‐deep waters. The application of this procedure is illustrated first by a small academic example, and then by a case study involving the design of lazy‐wave configurations of SCRs. Copyright © 2005 John Wiley & Sons, Ltd.     

结构主动控制的一体化多目标优化研究

基于Pareto多目标遗传算法提出了结构主动控制系统的一体化多目标优化设计方法,对作动器位置与主动控制器进行同步优化设计.外界激励采用平稳过滤白噪声来模拟,在状态空间下通过求解Lyapunov方程,得到结构响应和主动控制力的均方值.主动控制器采用LQG控制算法来进行设计.以结构位移和加速度均方值最大值与相应无控响应均方值的最大值之比,以及所需控制力均方值之和作为多目标同步优化的目标函数.优化过程还考虑了结构与激励参数对优化结果的影响.最后以某6层平面框架有限元模型为例进行了计算机仿真分析,结果表明所提出的主动控制系统多目标一体化优化方法简单,高效,实用,具有较好的普适性.     

Topology optimization of double- and triple-layer grids using a hybrid methodology

In this article, a hybrid methodology combining evolutionary structural optimization (ESO) and gravitational particle swarm (GPS) methods is proposed for topology optimization of double- and triple-layer grids. In the present methodology, which is called the ESO-GPS method, the size optimization of double- and triple-layer grids is first performed by ESO. Then, the outcomes of the ESO are used to improve the GPS through four modifications. Structural weight is minimized against constraints on the displacements of nodes, internal stresses and element slenderness ratio. The GPS is used to investigate the optimum topology of large-scale skeletal structures with discrete variables whose agents update their respective positions by the particle swarm optimization velocity and the acceleration of the gravitational search algorithm. The numerical results show that the proposed algorithm, the ESO-GPS, performs better than the GPS and the other methods presented in the literature.     

Topology and sizing optimization of discrete structures using a cooperative coevolutionary genetic algorithm with independent ground structures

This article proposes a method called the cooperative coevolutionary genetic algorithm with independent ground structures (CCGA-IGS) for the simultaneous topology and sizing optimization of discrete structures. An IGS strategy is proposed to enhance the flexibility of the optimization by offering two separate design spaces and to improve the efficiency of the algorithm by reducing the search space. The CCGA is introduced to divide a complex problem into two smaller subspaces: the topological and sizing variables are assigned into two subpopulations which evolve in isolation but collaborate in fitness evaluations. Five different methods were implemented on 2D and 3D numeric examples to test the performance of the algorithms. The results demonstrate that the performance of the algorithms is improved in terms of accuracy and convergence speed with the IGS strategy, and the CCGA converges faster than the traditional GA without loss of accuracy.     

Modeling of hybrid vibration control for multilayer structures using solid-shell finite elements

A self-control method of vibrations is presented in this paper. This method combines the passive damping capabilities afforded by viscoelastic materials with the active control properties associated with piezoelectric materials. Active control is introduced, using the piezoelectric properties, in order to improve the reduction in vibration amplitudes that can be obtained by viscoelastic passive damping alone. To this end, a filter has been mounted between the sensors and the actuators. The resulting nonlinear problem is discretized using the recently developed solid-shell finite element SHB20E, due to the advantages it offers in terms of accuracy and efficiency as compared to standard finite elements with the same geometry and kinematics. In order to solve the discretized problem, a resolution method using DIAMANT approach is developed. A set of selective and representative numerical tests are performed on multilayer plates to demonstrate the interest of the proposed damping model.     

Design space optimization using a numerical design continuation method

A generalized optimization problem in which design space is also a design to be found is defined and a numerical implementation method is proposed. In conventional optimization, only a portion of structural parameters is designated as design variables while the remaining set of other parameters related to the design space are often taken for granted. A design space is specified by the number of design variables, and the layout or configuration. To solve this type of design space problems, a simple initial design space is selected and gradually improved while the usual design variables are being optimized. To make the design space evolve into a better one, one may increase the number of design variables, but, in this transition, there are discontinuities in the objective and constraint functions. Accordingly, the sensitivity analysis methods based on continuity will not apply to this discontinuous stage. To overcome the difficulties, a numerical continuation scheme is proposed based on a new concept of a pivot phase design space. Two new categories of structural optimization problems are formulated and concrete examples shown. Copyright © 2001 John Wiley & Sons, Ltd.     

Analysis,design and optimization of structures using force method and genetic algorithm

In the first part of this paper, the energy formulation of the force method is presented and analysis is performed using genetic algorithm. Two simple examples are provided to show the accuracy of the approach. In the second part, an efficient method is developed for designing structures with prescribed stress ratios for its members. The genetic algorithm performed very well and designs with specified stress ratios were achieved with a good convergence rate. A unit value of c_i for all the members of a structure corresponds to the well known fully stressed design. In the third part, minimum weight design is formulated by the additional conditions being imposed on the design process. Again, genetic algorithm showed to be a powerful means for optimization. Copyright © 2005 John Wiley & Sons, Ltd.     

A geometry projection method for the topology optimization of curved plate structures with placement bounds

Single‐curvature plates are commonly encountered in mechanical and civil structures. In this paper, we introduce a topology optimization method for the stiffness‐based design of structures made of curved plates with fixed thickness. The geometry of each curved plate is analytically and explicitly represented by its location, orientation, dimension, and curvature radius, and therefore, our method renders designs that are distinctly made of curved plates. To perform the primal and sensitivity analyses, we use the geometry projection method, which smoothly maps the analytical geometry of the curved plates onto a continuous density field defined over a fixed uniform finite element grid. A size variable is ascribed to each plate and penalized in the spirit of solid isotropic material with penalization, which allows the optimizer to remove a plate from the design. We also introduce in our method a constraint that ensures that no portion of a plate lies outside the design envelope. This prevents designs that would otherwise require cuts to the plates that may be very difficult to manufacture. We present numerical examples to demonstrate the validity and applicability of the proposed method.     

泡沫填充夹芯墙多胞结构的耐撞性多目标优化设计

泡沫填充管由于其优秀的能量吸收性能引起越来越多的关注。根据对丝瓜结构的研究,提出一种与丝瓜横截面类似的泡沫填充夹芯墙多胞结构。基于非线性有限元软件LS-DYNA,建立此种泡沫填充夹芯墙多胞结构的轴压分析有限元模型。基于多项式代理模型,采用多目标粒子群优化算法对不同截面形状的多胞结构进行了优化设计。根据优化结果对不同结构的选择给出指导性意见,使结构在满足峰值力限制的情况下拥有最好的吸能特性。本文提出的新型结构在车辆工程及航空航天等领域具有很好的应用前景。     

Investigating the optimal passive and active vibration controls of adjacent buildings based on performance indices using genetic algorithms

This study proposes the optimal passive and active damper parameters for achieving the best results in seismic response mitigation of coupled buildings connected to each other by dampers. The optimization to minimize the H₂ and H_∞ norms in the performance indices is carried out by genetic algorithms (GAs). The final passive and active damper parameters are checked for adjacent buildings connected to each other under El Centro NS 1940 and Kobe NS 1995 excitations. Using real coded GA in H_∞ norm, the optimal controller gain is obtained by different combinations of the measurement as the feedback for designing the control force between the buildings. The proposed method is more effective than other metaheuristic methods and more feasible, although the control force increased. The results in the active control system show that the response of adjacent buildings is reduced in an efficient manner.     

输出时滞控制系统稳定性分析及控制器设计

考虑滤波器时滞对受控系统的影响,研究受控输出时滞系统的稳定性能。根据稳定性切换理论,确定多自由度受控系统的稳定时滞区域。经过分析获得受控系统脉冲响应衰减时间接近最短时的时滞量,在此基础上采用时滞引入法和滤波器设计法进行控制器设计。结合悬臂梁模型进行数值分析,结果表明:根据时滞系统稳定性分析设计的控制器能够使受控系统脉冲响应衰减速度提高80%以上,有效改善系统的控制效果和稳定性能。     

Reducing dimensionality in topology optimization using adaptive design variable fields

Topology optimization methodologies typically use the same discretization for the design variable and analysis meshes. Analysis accuracy and expense are thus directly tied to design dimensionality and optimization expense. This paper proposes leveraging properties of the Heaviside projection method (HPM) to separate the design variable field from the analysis mesh in continuum topology optimization. HPM projects independent design variables onto element space over a prescribed length scale. A single design variable therefore influences several elements, creating a redundancy within the design that can be exploited to reduce the number of independent design variables without significantly restricting the design space. The algorithm begins with sparse design variable fields and adapts these fields as the optimization progresses. The technique is demonstrated on minimum compliance (maximum stiffness) problems solved using continuous optimization and genetic algorithms. For the former, the proposed algorithm typically identifies solutions having objective functions within 1% of those found using full design variable fields. Computational savings are minor to moderate for the minimum compliance formulation with a single constraint, and are substantial for formulations having many local constraints. When using genetic algorithms, solutions are consistently obtained on mesh resolutions that were previously considered intractable. Copyright © 2009 John Wiley & Sons, Ltd.     

A new hybrid reliability-based design optimization method under random and interval uncertainties

This article proposes a new method for hybrid reliability-based design optimization under random and interval uncertainties (HRBDO-RI). In this method, Monte Carlo simulation (MCS) is employed to estimate the upper bound of failure probability, and stochastic sensitivity analysis (SSA) is extended to calculate the sensitivity information of failure probability in HRBDO-RI. Due to a large number of samples involved in MCS and SSA, Kriging metamodels are constructed to substitute true constraints. To avoid unnecessary computational cost on Kriging metamodel construction, a new screening criterion based on the coefficient of variation of failure probability is developed to judge active constraints in HRBDO-RI. Then a projection-outline-based active learning Kriging is achieved by sequentially select update points around the projection outlines on the limit-state surfaces of active constraints. Furthermore, the prediction uncertainty of Kriging metamodel is quantified and considered in the termination of Kriging update. Several examples, including a piezoelectric energy harvester design, are presented to test the accuracy and efficiency of the proposed method for HRBDO-RI.     

Engineering optimization using a real-parameter genetic-algorithm-based hybrid method

A hybrid optimization algorithm which combines the respective merits of the genetic algorithm and the simulated annealing algorithm is proposed. The proposed algorithm incorporates adaptive mechanisms designed to adjust the probabilities of the cross-over and mutation operators such that its hill-climbing ability towards the optimum solution is improved. The algorithm is used to optimize the weight of four planar or space truss structures and the results are compared with those obtained using other well-known optimization schemes. The evaluation trials investigate the performance of the algorithm in optimizing over discrete sizing variables only and over both discrete sizing variables and continuous configuration variables. The results show that the proposed algorithm consistently outperforms the other optimization methods in terms of its weight-saving capabilities. It is also shown that the global searching ability and convergence speed of the proposed algorithm are significantly improved by the inclusion of adaptive mechanisms to adjust the values of the genetic operators. Hence the hybrid algorithm provides an efficient and robust technique for solving engineering design optimization problems.     

采用改进遗传算法的结构主动控制器优化布置

用改进遗传算法研究了主动控制机构在建筑结构上的优化布置问题，先利用瞬时最优方法确定目标函数，在进行遗传操作时，为避免因采用普通遗传算法中的交叉和基本变异操作而产生违反约束条件的个体，提出了一种改进的交叉方法，即利用识别码进行判断交叉，并采用了双基因座变异，以满足约束条件，数值算例和结果表明了本文所提方法行之有效，优化速度较快。     

Global shared-layer blending method for stacking sequence optimization design and blending of composite structures

A global shared-layer blending (GSLB) method is proposed for obtaining manufacturable stacking sequence of composite structures with blending and design rules. The method combines the traditional SLB technique with an evaluation algorithm of spatial variation of panels, where the manufacturability of laminates is enhanced by identifying and minimizing the ply-drops, and controlling the laminate transition drop boundaries. In addition, a blended design scheme is also proposed, which is achieved by using the stacking sequence table technique. A composite wing structure is selected to validate the efficiency and accuracy of the proposed method. Results show that the GSLB method can be used for generating more manufacturable designs of large-scale composite structure with multiple engineering constraints.     

Post‐buckling optimization of composite structures using Koiter's method

Thin‐walled structures, when compressed, are prone to buckling. To fully utilize the capabilities of such structures, the post‐buckling response should be considered and optimized in the design process. This work presents a novel method for gradient‐based design optimization of the post‐buckling performance of structures. The post‐buckling analysis is based on Koiter's asymptotic method. To perform gradient‐based optimization, the design sensitivities of the Koiter factors are derived, and new design optimization formulations based on the Koiter factors are presented. The proposed optimization formulations are demonstrated on a composite square plate and a curved panel where the post‐buckling stability is optimized. Copyright © 2016 John Wiley & Sons, Ltd.