基于逆系统方法的多输入多输出非高斯驱动信号生成

多输入多输出(MIMO)振动环境试验是振动试验的新方法,该方法比传统的单输入单输出(SISO)方法更真实地模拟了结构在实际工作下的振动环境。传统随机振动试验的频域方法所模拟的是平稳高斯信号,但是实际振动环境往往是超高斯的,且超高斯激励和高斯激励对结构的损害差异很大,因此对MIMO超高斯振动环境试验的研究十分重要。驱动信号的产生是振动环境试验的关键。提出一种基于逆系统的MIMO超高斯驱动信号生成方法。首先,根据给定的响应参考功率谱密度(PSD)和参考峭度值采用相位调节法生成参考响应超高斯伪随机信号;其次,利用逆系统方法生成超高斯伪随机驱动信号;最后,对伪随机驱动信号进行时域随机化处理得到超高斯真随机驱动信号。对一根两输入两输出的悬臂梁模型进行了仿真验证,结果表明,采用本文方法所得到的驱动信号加载在梁上后,其输出响应谱与给定参考谱之间的误差完全满足工程中常用的±3 dB的要求,而且峭度也与给定的参考值十分接近,证实了所提方法的有效性。     

MIMO窄带加宽带非高斯随机振动试验

提出了一种用于多输入多输出窄带加宽带非高斯随机振动试验方法。首先，详细分析了随机相位与非高斯随机信号偏度和峭度的关系，提出了一种可用于快速生成具有指定偏度和峭度的迭代相位调节法。其次，根据控制通道之间的耦合关系，利用各通道之间随机相位的不相关特性，实现了多通道非高斯随机信号生成的解耦。然后，将生成的非高斯随机信号作为参考输出响应，采用时域逆系统方法生成驱动信号，并利用控制算法分别对响应信号的功率谱、偏度和峭度进行控制。最后，通过三轴向振动台试验验证了本文提出的多输入多输出窄带加宽带非高斯随机振动试验方法的可行性。结果表明，控制点上加速度的功率谱被控制在了±3 dB的容差限内，满足预设的容差要求。同时，时域响应信号的峭度和偏度也满足给定的参考要求。     

颤振抑制中的测量点和压电驱动器的分布

对于一个具有分布式压电驱动器的模型，设计了单输入／单输出（SISO），单输入／多输出（SIMO），多输入／多输出（MIMO）颤振主动抑制控制律，并进行了风洞试验验证。在此基础上，研究了测量点和压电驱动器的分布。     

利用FIR滤波器生成随机振动试验驱动信号的新方法

 阐述了一种利用有限冲击响应(FIR) 滤波器生成随机振动试验驱动信号的新方法。该方法通过设计一个FIR 滤波器对白噪声序列进行滤波,使滤波器输出序列的功率谱密度满足试验驱动信号的要求。在随机振动试验控制中,将FIR 滤波器和试验的受控对象组成增广系统,这将有助于简化对控制系统的分析和设计。     

多输入多输出随机振动试验变参数PID控制

 对多输入多输出(MIMO)随机振动试验控制的基本过程进行了系统分析。定义了一种新的在对数坐标下的控制误差表达式,然后在控制算法中引入了新的比例-积分-微分(PID)控制策略,并给出了PID参数随误差变化的规律。以悬臂梁为控制对象,完成了两输入两输出随机振动试验。结果表明：变参数PID控制方法能在保证快速均衡的基础上,有效地减小功率谱和参考谱之间的相对误差以及加速度总均方根值的控制误差,提高随机振动试验的控制精度。     

MIMO系统稳定裕度的几个定义

在介绍了单输入单输出（SISO）系统稳定裕度的基础上，重点讨论了多输入多输出（MIMO）系统的稳定裕度，给出了MIMO系统稳定裕度的几种定义并分析了各种定义的优劣，最后指出了MIMO系统需要进一步研究的问题。     

MIMO雷达DOA估计阵列设计

 多输入多输出（MIMO）雷达的关键技术之一是天线阵列的设计。由于MIMO雷达同时增加了收发两端的相位中心,使得系统具有更高的空间分辨率和更多的自由度。论文从接收信号模型出发,对MIMO雷达发射正交信号的等效阵列进行了讨论,以波达方向估计为目标提出了一种MIMO雷达天线阵的设计方法,通过抛物线理论得出了收发组合的唯一性和合理性,然后通过分析各种收发组合给出了发射阵元的最佳间隔设置。推导了几种情景下的MIMO收发阵列最佳设计解析解,最后进行了仿真实验。仿真结果验证了算法的有效性。     

多自由度非高斯随机振动控制

在振动试验台上进行多自由度(MDOF)随机振动激励时,传统的控制方法生成的驱动信号及试验台的响应信号都是高斯信号。但真实的振动干扰信号多是超高斯的;而相比于高斯激励,亚高斯激励可降低驱动信号的最大幅值。为实现多自由度亚高斯和超高斯振动控制,提出一种多自由度非高斯随机振动控制方法,该方法采用系统辨识解决系统耦合问题,而后通过选择特殊的相位生成非高斯伪随机驱动信号,再经过时域随机化得到真随机非高斯驱动信号。基于Hexapod平台的多自由度微振动试验台的亚高斯和超高斯实验表明,在试验台的响应功率谱(PSD)满足工程中常用的±3dB精度的同时,亚高斯驱动信号的最大幅值相比于高斯驱动信号的最大幅值降低了20%以上;超高斯响应信号的峭度与参考峭度的误差在0.2之内。实验结果验证了所提方法的有效性。     

MIMO雷达中一种降维MUSIC的相干角度估计算法

研究单快拍下双基地多输入多输出（Multiple—InputMultiple-Output,MIMO）雷达中相干信源的离开角（Directionofdeparture,DOD）与到达角（directionofarrival,DOA）联合估计问题。利用单快拍下双基地MIMO雷达的接收信号构造一组Toeplitz矩阵,利用这组ToepIitz矩阵重构一个信号矩阵,提出一种基于降维多重信号分类（ReducedDimensionMultipleSignalClassification,RD-MUSIC）的DOD与DOA联合估计算法。提出的算法能够有效估计相干信源以及非相干信源的角度,实现角度的自动配对,并且角度估计性能远优于FBSS—ESPRIT算法以及ESPRIT-like算法。仿真结果验证了算法的有效性。     

MIMO雷达的信号处理方法研究

在对多输入多输出（MIMO）雷达原理分析的基础上,研究了MIMO雷达的信号处理方法,并给出了两种信号处理实现方法。理论分析和公式推导表明,这两种信号处理实现方法具有相同的输出结果,计算机仿真结果也表明了结论的正确性。另外还对这两种实现方法的运算量进行了分析和比较。     

Control method for multi-input multi-output non-Gaussian random vibration test with cross spectra consideration

A control method for Multi-Input Multi-Output(MIMO) non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified references composed of auto spectral densities, cross spectral densities and kurtoses on the test article in the laboratory. It is found that the cross spectral densities will bring intractable coupling problems and induce difficulty for the control of the multioutput kurtoses. Hence, a sequential phase modification method is put forward to solve the coupling problems in multi-input multi-output non-Gaussian random vibration test. To achieve the specified responses, an improved zero memory nonlinear transformation is utilized first to modify the Fourier phases of the signals with sequential phase modification method to obtain one frame reference response signals which satisfy the reference spectra and reference kurtoses. Then, an inverse system method is used in frequency domain to obtain the continuous stationary drive signals. At the same time, the matrix power control algorithm is utilized to control the spectra and kurtoses of the response signals further. At the end of the paper, a simulation example with a cantilever beam and a vibration shaker test are implemented and the results support the proposed method very well.     

基于遗传算法的多振动台随机振动控制方法

 针对多振动台随机振动控制问题中求解补偿矩阵的广义逆算法,提出利用遗传算法对补偿矩阵的初值进行优化,解决了该类非线性、大范围极值求解问题。双振动台随机振动控制的仿真实验研究表明:将基于遗传算法的广义逆求解补偿矩阵方法引入随机振动控制过程,在同等精度条件下,计算时间大为缩短并改善了控制中共振峰处的奇异性,使广义逆算法在多振动台随机振动控制中的在线应用成为可能。     

Implementation of nondeterministic pulsewidth modulation forinverter drives

A single-phase power factor preregulator to improve the power quality in the input side of an ac/dc/ac converter and a random pulsewidth modulation (PWM) to reduce the emitted noise energy and the mechanical vibration for an induction motor drive is proposed. The hysteresis current control (HCC) technique for a voltage source switching mode rectifier (SMR) is adopted. A control scheme is presented such that the line current is driven to follow the reference current which is derived from the dc bus voltage regulator and the output power estimator. A random pulse position technique for a three-phase voltage source inverter system to reduce the noise energy and resonant vibration from ac machine drive is described. By randomly varying the instantaneous pulse position in each switching frequency, the frequency distribution of harmonics is spread in a wide frequency range which results in reduction of torque pulsations in the ac motor drive systems. To investigate the proposed control scheme, experimental tests based on a laboratory prototype were implemented to show the nearly unity power factor at the SMR and reduce the noise energy concentrated at the specific tones     

Quantitative speed control for SRM drive using fuzzy adapted inverse model

Quantitative and robust speed control for a switched reluctance motor (SRM) drive is considered to be rather difficult and challenging owing to its highly nonlinear dynamic behavior. A speed control scheme having two-degree-of-freedom (2DOF) structure is developed here to improve the speed dynamic response of an SRM drive. In the proposed control scheme, the feedback controller is quantitatively designed to meet the desired regulation control requirements first. Then a reference model and a command feedforward controller based on an inverse plant model are employed to yield the desired tracking response at nominal case. As the variations of system parameters and operating conditions occur, the prescribed control specifications may not be satisfied any more. To improve this, the inverse model is adaptively tuned by a fuzzy control scheme so that the model-following tracking error is significantly reduced. In addition, a simple disturbance cancellation robust controller is added to improve the tracking and regulation control performances further.     

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.     

Matrix Power Control Algorithm for Multi-input Multi-output Random Vibration Test

 Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output (MIMO) random vibration test. During the control process with the difference control algorithm (DCA), a lower triangular matrix is derived from Cholesky decomposition of a reference spectrum matrix. The diagonal elements of the lower triangular matrix (DELTM) may become negative. These negative values have no meaning in physical significance and can cause divergence of auto-power spectrum control. A proportional root mean square control algorithm (PRMSCA) provides another method to avoid the divergence caused by negative values of DELTM, but PRMSCA cannot control the cross-power spectrum. A new control algorithm named matrix power control algorithm (MPCA) is proposed in the paper. MPCA can guarantee that DELTM is always positive in the auto-power spectrum control. MPCA can also control the cross-power spectrum. After these three control algorithms are analyzed, three-input three-output random vibration control tests are implemented on a three-axis vibration shaker. The results show the validity of the proposed MPCA.     

导弹块对角控制器的组合设计法

利用小脑关节模型控制器 ( CMAC)神经网络辨识了导弹控制系统的几个重要空气动力参数,证明了估计误差、权误差有界,然后用解析逆解设计方法、模糊神经网络变结构控制方法设计了块对角控制器。仿真结果显示了该算法的有效性。     

高阶柔性结构系统振动控制中加权函数的选择

 总结了混合灵敏度H_∞控制算法中加权函数阵的选择方法,提出了一种新的选择加权函数矩阵的思想。以某悬臂梁为研究对象,将混合灵敏度H_∞控制方法应用在高阶柔性结构的振动主动控制问题中,完成了两输入两输出结构振动控制的控制器设计和算法仿真。结果表明,通过本方法选择加权函数矩阵,可在满足鲁棒稳定性的前提下,使外部干扰得到有效抑制,减振效果良好。