集总干扰下六旋翼飞行器的轨迹跟踪控制

针对复杂集总干扰下六旋翼飞行器轨迹跟踪控制问题,给出了混合积分反步法控制与线性自抗扰控制的控制算法. 首先,通过牛顿-欧拉方程建立六旋翼飞行器的非线性动力学模型,并剖析系统输入输出的数学关系. 其次,根据六旋翼飞行器动力学模型的特点,将其分为位置与姿态两个控制环. 位置环采用积分反步法控制理论设计控制器,通过引入积分项来提高系统的抗干扰能力,消除轨迹跟踪的静态误差;姿态环采用线性自抗扰控制技术设计控制器,通过线性扩张观测器估计和补偿集总干扰影响,提高系统的鲁棒性. 最后,通过2组仿真算例和1组飞行试验验证了本文所提飞行控制算法的有效性. 研究结果表明:该控制算法对集总干扰有较好的抑制作用,能够使六旋翼飞行器既快又稳地跟踪上参考轨迹,具有一定的工程应用价值.      

自抗扰控制在推力矢量飞机大迎角机动中的应用

为实现推力矢量飞机的大迎角机动控制,提出一种基于自抗扰控制的三通道解耦控制策略.以第三代战机F16公开数据为基础,添加推力矢量模型,利用双发推力矢量喷管组合偏转产生大迎角机动的期望三轴力矩.在纵向、横向和航向通道分别独立设计自抗扰控制器,将系统中未建模动态、不确定性以及通道间的强耦合视作总扰动进行估计并补偿,并在纵向和航向通道引入角速度阻尼反馈项,使原始飞行器开环动力学闭环近似为一个广义对象,降低了自抗扰控制器的设计阶次.选取眼镜蛇机动和赫伯斯特机动两种典型的过失速机动动作进行控制策略验证,数值仿真结果表明,所设计的三通道独立自抗扰控制器能够消除通道间的强耦合,完成推力矢量飞机的大迎角机动控制.蒙特卡罗仿真测试表明,所提控制策略具有较强的鲁棒性.      

复用等储备负荷法在热连轧粗轧负荷分配中的应用

 基于带钢热连轧粗轧区的特点,提出了复用等储备负荷法。该方法运用多层迭代算法进行粗轧机组负荷分配,外层对总轧制道次进行递增迭代,内层通过交替迭代确定带钢厚度和宽度轧制方向的综合负荷函数值,逐步优化平 立辊轧制规程。基于该方法设计了带钢热连轧粗轧过程设定系统软件,并结合实例进行了分析。分析结果表明该方法的适应性和灵活性很强,可适用于实时粗轧轧制过程中的设定计算。     

基于超图的非规则应用局部性优化

针对非规则循环应用中存在的一次迭代访问多个间接数组的问题,给出了超图数组的形式化描述,提出了三种基于超图的数据重排算法,即基于超图的非重复编码数据重排算法、基于超图的回溯搜索数据重排算法和基于超图的先划分再回溯数据重排算法,以及两种基于超图的迭代重排算法,即基于超图的非重复编码迭代重排算法和基于超图的回溯搜索迭代重排算法.通过对典型的非规则应用实例——流体力学问题进行实验,表明单独的重排算法提高程序执行速度约25.4%.在最好的数据重排与迭代重排的组合算法下,一级和二级高速缓存的平均命中率分别增加到91.7%和96.5%.      

Biological implications of a 3 A structure of dimeric antithrombin

BACKGROUND: Antithrombin, a member of the serpin family of inhibitors, controls coagulation in human plasma by forming complexes with thrombin and other coagulation proteases in a process greatly accelerated by heparin. The structures of several serpins have been determined but not in their active conformations. We have determined the structure of intact antithrombin in order to study its mechanism of activation, particularly with respect to heparin, and the dysfunctions of this mechanism that predispose individuals to thrombotic disease. RESULTS: The crystal structure of a dimer of one active and one inactive molecule of antithrombin has been determined at 3 A. The first molecule has its reactive-centre loop in a predicted active conformation compatible with initial entry of two residues into the main beta-sheet of the molecule. The inactive molecule has a totally incorporated loop as in latent plasminogen activator inhibitor-1. The two molecules are linked by the reactive loop of the active molecule which has replaced a strand from another beta-sheet in the latent molecule. CONCLUSION: The structure, together with identified mutations affecting its heparin affinity, allows the placement of the heparin-binding site on the molecule. The conformation of the two forms of antithrombin demonstrates the extraordinary mobility of the reactive loop in the serpins and provides insights into the folding of the loop required for inhibitory activity together with the potential modification of this by heparin. The mechanism of dimerization is relevant to the polymerization that is observed in diseases associated with variant serpins.     

Simulation of Highly Skewed Non-Gaussian Stochastic Processes

In this paper, a simulation methodology is proposed to generate sample functions of a stationary, non-Gaussian stochastic process with prescribed spectral density function and prescribed marginal probability distribution. The proposed methodology is a modified version of the Yamazaki and Shinozuka iterative algorithm that has certain difficulties matching the prescribed marginal probability distribution. Although these difficulties are usually sufficiently small when simulating non-Gaussian stochastic processes with slightly skewed marginal probability distributions, they become more pronounced for highly skewed probability distributions (especially at the tails of such distributions). Two major modifications are introduced in the original Yamazaki and Shinozuka iterative algorithm to ensure a practically perfect match of the prescribed marginal probability distribution regardless of the skewness of the distribution considered. First, since the underlying “Gaussian” stochastic process from which the desired non-Gaussian process is obtained as a translation process becomes non-Gaussian after the first iteration, the empirical (non-Gaussian) marginal probability distribution of the underlying stochastic process is calculated at each iteration. This empirical non-Gaussian distribution is then used instead of the Gaussian to perform the nonlinear mapping of the underlying stochastic process to the desired non-Gaussian process. This modification ensures that at the end of the iterative scheme every generated non-Gaussian sample function will have the exact prescribed non-Gaussian marginal probability distribution. Second, before the start of the iterative scheme, a procedure named “spectral preconditioning” is carried out to check the compatibility between the prescribed spectral density function and prescribed marginal probability distribution. If these two quantities are found to be incompatible, then the spectral density function can be slightly modified to make it compatible with the prescribed marginal probability distribution. Finally, numerical examples (including a stochastic process with a highly skewed marginal probability distribution) are provided to demonstrate the capabilities of the proposed algorithm.     

双闭环直流调速系统优选设计

根据自动控制原理和内模控制原理,针对双闭环直流调速系统的速度调节器进行设计,通过比较选取最优设计方法,最优设计的调节人有ＰＩＤ结构,但只有一个可调参数,而且这一被调参数与系统的性能直接相关。理论分析和仿真结果表明,该调节器使系统获得优良的动态和静态性能,设计简单,参数调整方便。     

Active Control of Structures in Nonlinear Response

The need to account for geometric and material nonlinearities in the active control of highly flexible, large, space structures is emphasized herein. The performance index of the control problem is minimized subject to equations of state and costate using a variable metric algorithm. Unlike the conventional techniques for active control, the present algorithm is able to exploit the sparsity and symmetry of the mass and stiffness matrices of the finite element models of structures. The algorithm thus has the potential of being able to control moderately large‐scale, finite element models of highly flexible, large, space structures in a cost‐effective manner. The proposed algorithm is validated in suppressing the nonlinear vibrations of an impulsively loaded, highly flexible beam, and the need for inclusion of nonlinearities is demonstrated.     

Parallel Algorithms for Integrated Structural/Control Optimization

Optimization of combined structural and control systems is a complex problem requiring an inordinate amount of computer‐processing time, especially the solution of the eigenvalue problem of a general unsymmetric square real matrix with complex eigenvalues and eigenvectors, which is frequently used in such problem. The few algorithms presented in the literature thus far have been applied to small structures with a few members and controllers only. Parallel processing on new‐generation multiprocessor computers provides an opportunity to solve large‐scale problems. In this paper, the integrated structural and control optimization problem is formulated by including constraints on displacements, stresses, and closed‐loop eigenvalues and the corresponding damping factors. Then, parallel algorithms are presented for integrated optimization of structures on shared‐memory multiprocessors such as the Cray YMP 8/864 supercomputer. In particular, parallel algorithms are presented for the solution of complex eigenvalue problems encountered in structural control problems using the method of matrix iteration for dominant eigenvalue(s). The solution is divided into two parts. The first part is the iteration for dominant eigenvalue(s) and the corresponding eigenvector(s) and the second part is the reduction of the matrix to obtain the smaller eigenvalue(s) and the corresponding eigenvector(s).     

串级极点配置自校正控制

根据串级过程的特点，提出了用两种极点配置自校正控制算法分别实现主、付控制器、构成自校正串极控制系统，并给出数字仿真结果．     

模糊神经网络自组织控制算法在罩式加热炉温控系统上的应用

罩式炉在工作过程中,需要控制好炉台的温度,达到生产需要的温度及变化要求。为了实现温度控制的要求,整个系统采用双闭环的控制方式,外环为温度环,内环为电流环。其中加入模糊神经网络自组织控制算法,使系统更具有精确性。模糊控制器以温度及温度变化作为输入变量,以脉冲宽度调节作为输出变量。从而通过可控硅开关的通断来改变回路中的电流,以达到控制电阻丝的发热量,调节炉膛内的温度变化。整个过程中,模糊神经网络自组织控制与可控硅开关起着重要的作用,着重研究基于模糊控制的罩式加热炉可控硅控制的实现问题。     

A model of the quaternary structure of enolases, based on structural and evolutionary analysis of the octameric enolase from Bacillus subtilis

Purified enolase from Bacillus subtilis has a native mass of approximately 370 kDa. Since B. subtilis enolase was found to have a subunit mass of 46.58 kDa, the quaternary structure of B. subtilis is octameric. The pl for B. subtilis enolase is 6.1, the pH optimum (pHo) for activity is 8.1-8.2, and the Km for 2-PGA is approximately 0.67 mM. Using the dimeric Calpha structure of yeast dimeric enolase as a guide, these dimers were arranged as a tetramer of dimers to simulate the electron microscopy image processing obtained for the octameric enolase purified from Thermotoga maritima. This arrangement allowed identification of helix J of one dimer (residues 86-96) and the loop between helix L and strand 1 (HL-S1 loop) of another dimer as possible subunit interaction regions. Alignment of available enolase amino acid sequences revealed that in 16 there are two tandem glycines at the C-terminal end of helix L and the HL-S1 loop is truncated by 4-6 residues relative to the yeast polypeptide, two structural features absent in enolases known to be dimers. From these arrangements and alignments it is proposed that the GG tandem at the C-terminal end of helix L and truncation of the HL-S1 loop may play a critical role in octamer formation of enolases. Interestingly, the sequence features associated with dimeric quaternary structure are found in three phylogenetically disparate groups, suggesting that the ancestral enolase was an octamer and that the dimeric structure has arisen independently multiple times through evolutionary history.     

Adaptive Control Strategy for Dynamic Substructuring Tests

Real-time dynamic substructuring, or hybrid testing, is a technique that enables experimental testing of critical elements of a complete structure. The structure in question is decomposed into at least two parts: the critical element, which is physically tested, and the remainder of the structure, which is modeled numerically. For accurate replication of the system to be emulated, the two parts must interact, via a controller to compensate for the actuator dynamics, in real-time, and with minimal errors at their interfaces. During development, the adaptive minimal controller synthesis (MCS) algorithm controller has previously been implemented for substructuring of a one-degree-of-freedom mass-spring-damper system. The potential advantage that MCS has over a traditional linear controller is its lack of reliance on detailed knowledge of the experimental specimen dynamics. This paper presents the MCSmd control strategy, an improved MCS-based strategy for substructure testing, using a modified demand (md) signal. Experimental and simulation studies of the MCSmd controller applied to a two-degree-of-freedom mass spring damper system are presented along with an analysis of the transient gain behavior.     

Damping of Vibration by Actively Controlled Initial Distortions

A concept for the artificial damping of free vibration by means of actively controlled initial distortions imposed on the structure is presented. Two formulations for active control are presented: The first simulates the natural damping properties of structures, while the second uses a more sophisticated modal strategy of control (but with a faster damping process). The general idea of damping by actively forced distortions is explained and followed by a simple example for a one‐degree‐of‐freedom system. Then, the simulation of natural damping (which is a particular case of active control) and the possibility of accelerating the damping process by the modal optimal strategy are discussed and demonstrated with some examples for a two‐degree‐of‐freedom system. Finally, the vibration control of a four‐degree‐of‐freedom system is presented to demonstrate the efficiency of the proposed method. The method of active damping is described for truss structures, but it can be easily generalized to include frame structures as well.     

Semiactive Neurocontrol for Seismic Response Reduction Using Smart Damping Strategy

A new semiactive control strategy that combines a neurocontrol system with a smart damper is proposed to reduce seismic responses of structures. In the proposed semiactive control system, the improved neurocontroller, which was developed by employing a training algorithm based on a cost function and a sensitivity evaluation algorithm to replace an emulator neural network, produces the desired active control force, and then a bang-bang-type controller clips the control forces that cannot be achieved by a smart damper (e.g., a variable orifice damper, controllable fluid damper, etc.). Therefore, the proposed semiactive control strategy is fail-safe in that the bounded-input, bounded-output stability of the controlled structure is guaranteed. Numerical simulation results show that the proposed semiactive control system that employs a neural network-based control algorithm is quite effective in reducing seismic responses.     

Vibration Control of Wind-Excited Tall Buildings Using Sliding Mode Fuzzy Control

A sliding mode fuzzy control (SMFC) is proposed to design a controller for the third-generation benchmark problem on wind-excited buildings. A distinctive feature in vibration control of large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure; however, they cannot be precisely measured, especially for the case of wind excitations. Since the structural accelerations are measured only at a limited number of locations without the measurement of the wind forces, the structure of the conventional control may have the feedback loop only. The general structure of the SMFC, proposed herein, is composed of a compensation part and a convergent part. The compensation part prevents the system from diverging, and the convergent part directs the system to the sliding surface. The compensation part uses not only the structural response measurement but also the disturbance measurement, so the SMFC has a feedback loop and a feedforward loop. To realize the virtual feedforward loop for the wind-induced vibration control, a disturbance estimation filter is introduced. The structure of the filter is constructed based on an autoregressive model for the stochastic wind force. This filter estimates the wind force at each time instance based on the measured structural responses and the stochastic information of the wind force. For verification of the proposed algorithm, numerical simulation is carried out on the benchmark problem for wind-excited buildings. The results indicate that the present control algorithm is efficient for reducing the wind-induced vibration.     

Model Predictive Control of Structures under Earthquakes using Acceleration Feedback

This paper presents a general formulation of the model predictive control (MPC) scheme with special reference to acceleration feedback in structural control under earthquakes. The MPC scheme is based on a prediction model of the system response to obtain the control action by minimizing an objective function. Optimization objectives include minimization of the difference between the predicted and desired response trajectories, and of the control effort subject to certain constraints. The effectiveness of MPC has been demonstrated to be equivalent to the optimal control. In this study, the prediction model is formulated using a feedback loop containing acceleration measurements from various locations in the structure. The state observer utilizes the Kalman-Bucy filter to estimate the states of the system from the acceleration feedback. Examples of single-story and three-story buildings equipped with control devices are used to demonstrate the effectiveness of the MPC scheme based on acceleration feedback. Both buildings are analyzed using an active tendon control device and an active mass damper (AMD). A two-story building with an AMD is used to experimentally validate the numerical control scheme. The results demonstrate the effectiveness of the MPC scheme using acceleration feedback. The acceleration feedback framework developed in this paper should serve as a building block for future extensions of MPC in capturing and benefiting from the attractive features of MPC, i.e., computational expediency, real-time applications, intrinsic compensation for time delays, and treatment of constraints, for implementation in civil structures.     

MIMO控制系统性能评价与监测的理论研究

控制系统性能评价与监测可以提高工业过程的性能 ,目前这个领域的研究越来越受到控制工程师们的重视。这篇论文介绍了一种MIMO控制系统性能评价与监测的新方法 ,这种新方法是基于控制系统的输出和过滤数据的FCOR(FilteringandsubsequentCorrelation)算法。FCOR算法包括估计MIMO控制系统的延迟时间也即交互矩阵 ;和以最小方差作为基准估计MIMO控制系统的性能。     

Multiobjective Optimal Fuzzy Logic Control System for Response Control of Wind-Excited Tall Buildings

Performance of the structure includes both the safety as well as comfort level for the user. The safety of the structure mainly depends on the displacement response, while the comfort level of occupants depends on the acceleration response. In this paper, an approach for multiobjective optimal design of a fuzzy logic controller (FLC)-driven active tuned mass damper (ATMD) has been proposed. The evaluation criteria for both the acceleration and displacement responses have been used as the two objective functions for this multiobjective optimization problem. As a multiobjective optimization approach provides a set of Pareto-optimal solutions, the user is allowed to select an appropriate design for the specific performance requirement. The effectiveness and performance of the proposed FLC-driven ATMD has been investigated for the third-generation benchmark problem for the response control of wind-excited tall buildings. A multiobjective optimization version of the genetic algorithm has been used for obtaining the FLC and ATMD design parameters, as this approach is more effective in handling a discontinuous and nonconvex domain. Performance of the proposed control system has been found to be better than the sample controller given in the benchmark problem. The proposed controller is less sensitive than the sample controller for the variation in the stiffness of the structure.     

Optimal Stabilization of Column Buckling

Linear buckling of column structures is an important design constraint in many structures, particularly where weight is a primary concern. Active strengthening is the application of feedback control to increase the critical buckling load of the structure. An important feature of this control problem is that the structure is inherently unstable when the axial load surpasses the critical buckling load. This research presents a design method for creating optimal buckling control systems using state or static output feedback. The primary feature of this method is the ability to select the designed closed loop, actively strengthened, critical buckling load. The stability of the resulting controllers is determined using Lyapunov methods. Simulation and experimental demonstration of this algorithm is performed using a column employing piezoelectric actuators, and MEMS-based strain sensors. The optimal buckling controllers developed are able to increase the critical buckling load by a factor of 2.9. The closed loop system is able to support lower axial loads indefinitely (>30 min).