基于非概率模型的结构稳健可靠性设计方法

 基于非概率可靠性理论,将稳健设计和稳健可靠性的思想和方法用于结构设计,提出了结构的稳健可靠性设计方法。把结构设计归结为满足可靠性要求的多目标优化。其中,以非概率可靠性指标为约束,以极小化结构重量 (或造价)和极大化对不确定因素的稳健性为目标。目的在于使结构在满足可靠性要求的前提下,其重量 (或造价)和对不确定因素的稳健性达到协调最优。在不确定参量的已知数据很少的情况下,本方法为结构的可靠性设计提供了一种可能的选择。数值算例说明了文中方法的应用。     

基于容限控制策略的结构振动鲁棒控制器设计

本文研究了一种直接满足控制性能要求的结构振动鲁棒控制的常增益反馈优化设计方法,提出了基于容限性能指标的控制设计准则,依据特征结构配置思想构造了反馈控制增益的优化设计程式,并辅以算例给出具体计算中的一些考虑。     

A novel method for importance measure analysis in the presence of epistemic and aleatory uncertainties

For structural systems with both epistemic and aleatory uncertainties, research on quantifying the contribution of the epistemic and aleatory uncertainties to the failure probability of the systems is conducted. Based on the method of separating epistemic and aleatory uncertainties in a variable, the core idea of the research is firstly to establish a novel deterministic transition model for auxiliary variables, distribution parameters, random variables, failure probability, then to propose the improved importance sampling(IS) to solve the transition model. Furthermore,the distribution parameters and auxiliary variables are sampled simultaneously and independently;therefore, the inefficient sampling procedure with an ‘‘inner-loop' for epistemic uncertainty and an‘‘outer-loop' for aleatory uncertainty in traditional methods is avoided. Since the proposed method combines the fast convergence of the proper estimates and searches failure samples in the interesting regions with high efficiency, the proposed method is more efficient than traditional methods for the variance-based failure probability sensitivity measures in the presence of epistemic and aleatory uncertainties. Two numerical examples and one engineering example are introduced for demonstrating the efficiency and precision of the proposed method for structural systems with both epistemic and aleatory uncertainties.     

带有广义不确定性的导弹非线性控制系统设计

 在导弹系统存在广义不确定性情况下,提出了一种基于反演设计技术和RBF神经网络的导弹非线性自适应控制系统设计方法。设计过程中将不确定性对系统的影响合成为一项,然后应用RBF神经网络消除了其对系统的影响,有效地解决了控制系数矩阵未知时控制器设计问题,同时放松了现有文献中对控制系数矩阵不确定性的要求。应用Lypunov稳定性定理推导出神经网络权重矩阵的自适应调节律,并证明了闭环系统的所有信号均有界且指数收敛至系统原点的一个邻域。最后给出的BTT导弹非线性六自由度数字仿真结果验证了该算法的有效性。     

Reliability design optimization of composite structures based on PSO together with FEA

The present work aims to develop a method for reliability-based optimum design of composite structures. A procedure combining particle swarm optimization (PSO) and finite element analysis (FEA) has been proposed. Numerical examples for the reliability design optimization (RDO) of a laminate and a composite cylindrical shell are worked out to demonstrate the effectiveness of the method. Then a design for composite pressure vessels is studied. The advantages and necessity of RDO over the conventional equi-strength design are addressed. Examples show that the proposed method has good stability and is efficient in dealing with the probabilistic optimal design of composite structures. It may serve as an effective tool to optimize other complicated structures with uncertainties.     

智能结构不确定参数系统振动控制及其摄动分析

 结构建模中通常考虑不确定性等因素以确保系统及其控制系统具有良好的鲁棒性,由于参数不确定性引起的系统参数的变化将导致系统性能退化,甚至影响系统内部稳定性,所以不确定性概念在工程结构的分析与设计中起到重要的作用。研究了具有不确定参数系统鲁棒性理论,提出了抑制系统振动的控制规律;基于矩阵摄动法讨论了不确定参数对智能结构系统的影响,并利用不确定性凸模型理论分析了智能结构具有不确定参数系统稳定性的问题,提出了分析含不确定参数系统鲁棒性的方法。算例说明该方法的有效性。     

卫星姿态控制的一种鲁棒控制方法

针对含有不确定性的Delta算子离散系统,研究了其鲁棒控制问题。鲁棒控制律的存在条件及设计由线性矩阵不等式描述,便于求解。将所得结果应用于卫星姿态控制系统的设计,以解决对模型进行线性化处理时产生的误差。针对所得控制律进行了仿真研究,结果证明了方法的有效性。     

Robust dissipative compensators for flexible spacecraft control

The problem of controller design for flexible spacecraft is addressed. Model-based compensators, which rely on the knowledge of the system parameters to tune the state estimator, are first considered, and are shown to have high sensitivity to parameter uncertainties. Three types of dissipative controllers, which use collocated actuators and sensors, are next considered. These controllers guarantee stability in the presence of unmodeled elastic modes and parameter uncertainties. A procedure is given for designing an optimal dissipative dynamic compensator, which can provide better performance while still retaining robust stability     

Robust guidance for electro-optical missiles

A robust guidance law is presented which renders zero miss distance (ZMD) against deterministically or randomly maneuvering targets for all missile parametric uncertainties. Since the resulting guidance controller is a phase-lead network, it is mainly suitable for systems characterized by moderate glint levels such as electro-optical missiles. The structured uncertainties in missile dynamics are modeled by interval transfer functions. It is first shown that for the nominal case, when the total missile transfer function is positive real, ZMD can be obtained. When uncertainties are considered, the problem becomes design of a guidance controller which renders a family of transfer functions positive real. A new algorithm for the design of such controllers is proposed. An example illustrating a typical design procedure for a nonlinear real-life missile model is given, showing the simplicity and effectiveness of the proposed robust guidance. The main conclusion of this work is that the newly developed guidance law performs well against highly maneuvering targets and may be a suitable alternative to optimal guidance laws in low-glint systems.     

Attitude tracking control for variable structure near space vehicles based on switched nonlinear systems

An adaptive robust attitude tracking control law based on switched nonlinear systems is presented for a variable structure near space vehicle (VSNSV) in the presence of uncertainties and disturbances. The adaptive fuzzy systems are employed for approximating unknown functions in the flight dynamic model and their parameters are updated online. To improve the flight robust performance, robust controllers with adaptive gains are designed to compensate for the approximation errors and thus they have less design conservation. Moreover, a systematic procedure is developed for the synthesis of adaptive fuzzy dynamic surface control (DSC) approach. According to the common Lyapunov function theory, it is proved that all signals of the closed-loop system are uniformly ultimately bounded by the continuous controller. The simulation results demonstrate the effectiveness and robustness of the proposed control scheme.     

正交多项式在不确定转子动态响应计算中的应用及对比分析

为研究航空发动机转子系统中的区间不确定性对系统动态响应的影响,提出利用正交多项式求解不确定转子响应的非嵌入式区间分析法,克服了传统概率方法需要参数先验概率分布的苛刻要求。用有限元法建立了悬臂转子的确定性运动方程,阐述了Chebyshev和Legendre两种正交多项式建立响应代理模型的原理和计算步骤。通过与Monte Carlo抽样对比,验证方法的可行性和精度。对照Monte Carlo方法500样本的计算结果,两种多项式区间法计算结果都具有较高精度,误差均小于1%,而计算时间则分别为Monte Carlo法的2.5%和5.4%,Chebyshev多项式方法具有更高的计算效率。分析了不同不确定参数在不同不确定水平下,系统的响应范围。研究表明,正交多项式区间分析法可高精度高效率地计算转子系统区间响应范围,不确定性对该转子系统动力特性影响很大,多源不确定性传播可引起转子系统大幅振动。      

具结构式不确定性系统的鲁棒镇定

考虑一类与摄动参数呈多项式函数关系的不确定性模型 ,这类模型反应了预知部分不确定性信息的物理意义。给出了含这类不确定性系统鲁棒稳定的充分条件和最大稳定域估计方法。在区间系统情形 ,该条件退化为已有结果 ,这间接表明文中条件的保守性有限。进一步得到了状态和输出反馈鲁棒镇定控制器的设计方法 ,及文中方法意义下具有最大稳定域的镇定控制器设计算法。最后 ,给出了一个飞控系统鲁棒镇定控制器设计的例子 ,说明文中方法的可行性。     

基于自适应反演的导弹滑模控制

阐述了在导弹系统存在不确定性情况下,基于自适应反演控制技术和模糊神经网络理论,提出了一种导弹滑模控制系统设计方法。设计过程中将不确定性对系统的影响合成为一项,然后应用模糊神经逼近器来逼近系统的不确定项;考虑了已知信息,利用自适应模糊神经控制理论和滑模控制设计了控制器,应用Lypunov稳定性理论保证了闭环系统的稳定性,并推导出模糊神经逼近器各参数的自适应调节律。     

过失速机动飞机的鲁棒非线性控制律设计

 采用非线性动态逆和结构奇异值综合方法设计了过失速飞行条件下飞控系统控制律,解决了飞控设计中面临的非线性和鲁棒性问题。应用非线性动态逆的目的就是对过失速机动飞行条件下高度非线性的飞机动力学进行线化;从而围绕线性的快逆回路应用结构奇异值综合方法设计相应的鲁棒控制器,以提供对驾驶员指令的鲁棒跟踪。所设计的飞控系统将达到期望的飞行品质,确保系统对过失速机动飞行过程中因非定常气动力效应引起的系统参数摄动鲁棒性良好。高逼真度、非线性的仿真验证了这一点。     

基于泰勒展开法的转子系统动力特性区间分析方法

对转子系统动力特性运用一种非概率-区间分析方法进行分析.基于区间数学和1阶泰勒展开理论的区间分析方法将非确定参数支承刚度和连接结构刚度视为区间向量,运用泰勒展开法建立了转子系统固有频率的公式.区间分析方法降低了传统的概率分析方法对不确定参数信息的过分要求,为解决含有非确定参数的转子系统动力特性问题提供了一个途径.应用区间泰勒展开法和概率方法对数值算例进行了分析,并比较了结果.当参数非确定性小于20%时,计算得到的转子系统固有频率区间上下界与真实值区间上下界误差小于2.2%.建立了转子系统动力特性试验装置,试验结果验证了方法的有效性.      

复合材料层合板屈曲载荷计算的区间分析算法

提出了求解具有不确定性复合材料层合板屈曲载荷的一种处理方法———区间分析法。区间分析法是基于区间数学和泰勒展开的一种处理不确定性的方法。区间分析法不需要知道不确定变量的概率统计特性,只要较少的材料物理特性信息,即不确定变量的上界和下界,加上较简单的计算就可以得出结构响应的变化区间。在样本比较小,概率统计特性不明显,从而通常的概率统计方法不能有效应用时,区间分析仍然有效。文中针对四边简支的特殊正交层合板以及反对称角铺设层合板的屈曲载荷,用概率算法和区间算法分别进行了计算与比较。     

Aeroelastic two-level optimization for preliminary design of wing structures considering robust constraints

An aeroelastic two-level optimization methodology for preliminary design of wing struc- tures is presented, in which the parameters for structural layout and sizes are taken as design vari- ables in the first-level optimization, and robust constraints in conjunction with conventional aeroelastic constraints are considered in the second-level optimization. A low-order panel method is used for aerodynamic analysis in the first-level optimization, and a high-order panel method is employed in the second-level optimization. It is concluded that the design of the abovementioned structural parameters of a wing can be improved using the present method with high efficiency. An improvement is seen in aeroelastic performance of the wing obtained with the present method when compared to the initial wing. Since these optimized structures are obtained after consideration of aerodynamic and structural uncertainties, they are well suited to encounter these uncertainties when they occur in reality.     

高超声速飞行器飞行动力学特性不确定分析

 高超声速飞行器分析模型存在较大不确定性,其给出的动力学特性与真实值之间存在偏差,因此研究飞行动力学特性分析结果的可信度水平对控制系统设计具有重要意义。针对典型的乘波体构型高超声速飞行器,在建立气动/结构/推进相互耦合的动力学模型基础上,利用非概率区间来描述模型中的不确定参数,并将复特征根不确定范围求解问题转化为频率和阻尼比两个实数的不确定区间分别求解,给出了动力学模态特征根、频率及阻尼比的不确定边界。分别采用直接蒙特卡罗(DMC)模拟方法、基于泰勒展开的区间分析方法(TIAM)和基于多项式逼近的区间分析方法(CIAM)对高超声速飞行器飞行动力学不确定性进行了研究。结果表明:CIAM计算时间适中,且给出的边界更为准确、安全,适合在控制系统设计和验证过程中使用。     

Adaptive vector field based accurate homing control of aerial delivery systems

This paper investigates the homing control problem of a flexible aerial delivery system with external wind, at-mospheric turbulence, and aerodynamic uncertainties. An accurate homing control strategy is presented, consisting of a trajectory generation algorithm and a lateral tracking controller. A high-altitude trajectory generation is de-veloped with system characteristics explicitly considered to generate the desired trajectory for the aerial delivery control system design. It significantly compensates for the altitude deviation of the existing multiphase theory based trajectory generation methodologies. A novel adaptive vector field control law is then designed to accom-plish the lateral tracking maneuvers. The key feature of the proposed method is that the complete lateral closed-loop control, including position and heading angle loops, is achieved in the presence of disturbances and dynamic uncertainties. The homing control with high landing accuracy is therefore achieved. Simulation and hardware-in-loop testing results are finally presented to validate the proposed method’s effectiveness compared to a conventional homing control scheme.     

Constrained adaptive neural network control of an MIMO aeroelastic system with input nonlinearities

A constrained adaptive neural network control scheme is proposed for a multi-input and multi-output (MIMO) aeroelastic system in the presence of wind gust, system uncertainties, and input nonlinearities consisting of input saturation and dead-zone. In regard to the input nonlinear-ities, the right inverse function block of the dead-zone is added before the input nonlinearities, which simplifies the input nonlinearities into an equivalent input saturation. To deal with the equiv-alent input saturation, an auxiliary error system is designed to compensate for the impact of the input saturation. Meanwhile, uncertainties in pitch stiffness, plunge stiffness, and pitch damping are all considered, and radial basis function neural networks (RBFNNs) are applied to approximate the system uncertainties. In combination with the designed auxiliary error system and the backstep-ping control technique, a constrained adaptive neural network controller is designed, and it is pro-ven that all the signals in the closed-loop system are semi-globally uniformly bounded via the Lyapunov stability analysis method. Finally, extensive digital simulation results demonstrate the effectiveness of the proposed control scheme towards flutter suppression in spite of the integrated effects of wind gust, system uncertainties, and input nonlinearities.