A fuzzy adaptive learning control network with on-line structure and parameter learning

This paper addresses a general connectionist model, called Fuzzy Adaptive Learning Control Network (FALCON), for the realization of a fuzzy logic control system. An on-line supervised structure/parameter learning algorithm is proposed for constructing the FALCON dynamically. It combines the backpropagation learning scheme for parameter learning and the fuzzy ART algorithm for structure learning. The supervised learning algorithm has some important features. First of all, it partitions the input state space and output control space using irregular fuzzy hyperboxes according to the distribution of training data. In many existing fuzzy or neural fuzzy control systems, the input and output spaces are always partitioned into "grids". As the number of input/output variables increase, the number of partitioned grids will grow combinatorially. To avoid the problem of combinatorial growing of partitioned grids in some complex systems, the proposed learning algorithm partitions the input/output spaces in a flexible way based on the distribution of training data. Second, the proposed learning algorithm can create and train the FALCON in a highly autonomous way. In its initial form, there is no membership function, fuzzy partition, and fuzzy logic rule. They are created and begin to grow as the first training pattern arrives. The users thus need not give it any a priori knowledge or even any initial information on these. In some real-time applications, exact training data may be expensive or even impossible to obtain. To solve this problem, a Reinforcement Fuzzy Adaptive Learning Control Network (RFALCON) is further proposed. The proposed RFALCON is constructed by integrating two FALCONs, one FALCON as a critic network, and the other as an action network. By combining temporal difference techniques, stochastic exploration, and a proposed on-line supervised structure/parameter learning algorithm, a reinforcement structure/parameter learning algorithm is proposed, which can construct a RFALCON dynamically through a reward/penalty signal. The ball and beam balancing system is presented to illustrate the performance and applicability of the proposed models and learning algorithms.     

Algorithm for Generating Samples of Homogeneous Gaussian Fields

A new algorithm is developed for generating samples of stationary Gaussian random fields. The algorithm is based on a model derived from the spectral representation theorem for weakly stationary random fields. The model consists of a superposition of a random number of waves with random amplitude and frequency, can match the second moment properties of any target random field, and becomes Gaussian as the intensity of two independent Poisson processes, defining the number of waves and their frequencies, increases indefinitely. In contrast to the current Monte Carlo simulation algorithms, the proposed algorithm: (1) does not produce periodic samples; and (2) does not require the discretization of the frequency domain. The proposed Monte Carlo algorithm is applied to generate samples of a stationary Gaussian field defined on 2.     

一种模糊认知图分类器构造方法

提出了一种新的模糊认知图分类器模型构造方法,它包括构建流程、激活函数、推理规则和学习方法等核心构件.模型利用提出的动态交叉变异算子自适应遗传进化过程,实现种群间自动调节和自动适应.仿真实验表明:本文提出的模型增强了局部随机搜索能力,加强了算法的全局收敛能力,与其他经典分类方法相比,不但性能较好,而且具有较强的抗噪能力,从而具有更强的鲁棒性.      

Deterministic Control of Column under Horizontal-Vertical Excitation

A control methodology is presented for a column, modeled as a single-degree-of-freedom system subjected to simultaneous horizontal and vertical support motion. It is assumed that the support motions are uncertain, time varying, and norm bounded, and that the column itself has no uncertainties associated with it. The control signal is based on Lyapunov theory and noise-free state feedback measurements. The states of the resulting closed-loop system (namely displacement and velocity) are uniformly and ultimately bounded within a neighborhood of the zero state. To illustrate the features of the proposed controller, examples of nonhysteretic and hysteretic columns subjected to combined horizontal and vertical nonstationary seismic excitation are considered. Numerical results for the uncontrolled and controlled responses are obtained and analyzed. Several issues involved in the controller design are examined, and results illustrating the control performance and effectiveness are presented and discussed.     

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.     

Monte–Carlo Based Method for Predicting Extreme Value Statistics of Uncertain Structures

In the present paper, a simple method is proposed for predicting the extreme response of uncertain structures subjected to stochastic excitation. Many of the currently used approaches to extreme response predictions are based on the asymptotic generalized extreme value distribution, whose parameters are estimated from the observed data. However, in most practical situations, it is not easy to ascertain whether the given response time series contain data above a high level that are truly asymptotic, and hence the obtained parameter values by the adopted estimation methods, which points to the appropriate extreme value distribution, may become inconsequential. In this paper, the extreme value statistics are predicted taking advantage of the regularity of the tail region of the mean upcrossing rate function. This method is instrumental in handling combined uncertainties associated with nonergodic processes (system uncertainties) as well as ergodic ones (stochastic loading). For the specific applications considered, it can be assumed that the considered time series has an extreme value distribution that has the Gumbel distribution as its asymptotic limit. The present method is numerically illustrated through applications to a beam with spatially varying random properties and wind turbines subjected to stochastic loading.     

Semiactive Control Strategies for MR Dampers: Comparative Study

This paper presents the results of a study to evaluate the performance of a number of recently proposed semiactive control algorithms for use with multiple magnetorheological (MR) dampers. Various control algorithms used in recent semiactive control studies are considered including the Lyapunov controller, decentralized bang-bang controller, modulated homogeneous friction algorithm, and a clipped optimal controller. Each algorithm is formulated for use with the MR damper. Additionally, each algorithm uses measurements of the absolute acceleration and device displacements for determining the control action to ensure that the algorithms could be implemented on a physical structure. The performance of the algorithms is compared through a numerical example, and the advantages of each algorithm are discussed. The numerical example considers a six-story structure controlled with MR dampers on the lower two floors. In simulation, an El Centro earthquake is used to excite the system, and the reduction in the drifts, accelerations, and relative displacements throughout the structure is examined.     

Development of Direct Integration Algorithms for Structural Dynamics Using Discrete Control Theory

In structural dynamics, integration algorithms are often used to obtain the solution of temporally discretized equations of motion at selected time steps. Various time integration algorithms have been developed in the time domain using different methods. In order for an integration algorithm to be reliable it must be stable and accurate. A discrete transfer function is used to study the properties of integration algorithms. A pole mapping rule from control theory in conjunction with a discrete transfer function is used to develop new integration algorithms for obtaining solutions to structural dynamics problems. A new explicit integration algorithm, called the CR (Chen and Ricles) algorithm, is subsequently developed based on the proposed method. The properties of the algorithm are investigated and compared with other well established algorithms such as the Newmark family of integration algorithms. By assigning proper stable poles to the discrete transfer function the newly developed CR explicit algorithm is unconditionally stable and has the same accuracy as the Newmark method with constant acceleration. In addition, the CR algorithm is based on expressions for displacement and velocity that are both explicit in form, making it an appealing integration algorithm for solving structural dynamics problems.     

Element Level System Identification with Unknown Input with Rayleigh Damping

A novel system identification procedure is proposed for nondestructive damage evaluation of structures. It is a finite element-based time-domain linear system identification technique capable of identifying structures at the element level. The unique features of the algorithm are that it can identify a structure without using any input excitation information and it can consider both viscous and Rayleigh-type proportional damping in the dynamic models. The consideration of proportional damping introduces a source of nonlinearity in the otherwise linear dynamic algorithm. However, it will also reduce the total number of damping coefficients to be identified, reducing the size of the problem. The Taylor series approximation is used to transform a nonlinear set of equations to a linear set of equations. The proposed algorithm, denoted as the modified iterative least square with unknown input algorithm, is verified with several examples considering various types of structures including shear-type building, truss, and beams. The algorithm accurately identified the stiffness of structures at the element level for both viscous (linear) and proportional (nonlinear) damping cases. It is capable of identifying a structure even with noise-contaminated response information. An example shows how the algorithm could be used in detecting the exact location of a defect in a defective element. The algorithm is being developed further and is expected to provide an economical, simple, efficient, and robust system identification technique that can be used as a nondestructive defect detection procedure in the near future.     

Protein folding: optimized sequences obtained by simulated breeding in a minimalist model

For a minimalist model of protein folding, which we introduced recently, we investigate various methods to obtain folding sequences. A detailed study of random sequences shows that, for this model, such sequences usually do not fold to their ground states during simulations. Straight-forward techniques for the construction of folding sequences, based solely on the target structure, fail. We describe in detail an optimization algorithm, based on genetic algorithms, for the "simulated breeding" of folding sequences in this model. We find that, for any target structure studied, there is not only a single folding sequence but a patch of sequences in sequence space that fold to this structure. In addition, we show that, much as in real proteins, nonhomologous sequences may fold to the same target structure.     

基于双维度搜索的地下自主铲运机最优转弯轨迹规划

提出了一种基于双维度搜索的实时轨迹规划方法,用来解决自主地下铲运机转弯轨迹规划问题。该方法是一种结合采样思想和最优化算法的复合轨迹规划方法,包含三个主要步骤:基于双维度搜索策略的优化模型参数生成,基于二次规划的轨迹计算,以及基于约束检查的最优轨迹确定。该方法新颖之处在于提出的基于转弯区域行驶时间和里程的双维度搜索策略,以及基于平稳目标的轨迹最优化模型,可根据弯道区域入口速度和位置,快速生成纵横向都有最优性保证的最优轨迹。该方法结构简单、易于实施,可通过关键参数的调整满足控制器对轨迹生成速度的实时性要求。基于该轨迹规划方法的特点,使其不仅适用于实时轨迹规划,还可为未来智慧矿山的智能管控与优化调度提供底层约束。多组算例验证了该方法的有效性和优越性。      

球磨机制粉系统的线性自抗扰控制

球磨机制粉系统具有大惯性、大时滞和强耦合等特点,很难建立精确的数学模型.本文分析了球磨机制粉系统的动态特性,并为其设计分散线性自抗扰控制方案.该方案综合分散控制和线性自抗扰控制器的优点,结构简单,不依赖于对象精确模型,可以对被控对象中存在的耦合、干扰和不确定性等进行估计并补偿.根据实际现场要求,对球磨机制粉系统进行设定值跟踪实验、输入扰动实验和性能鲁棒性实验,并比较所设计方案与PID方案的控制性能.结果表明,分散线性自抗扰控制具有更强的解耦能力和抗干扰能力,且性能鲁棒性更优.      

Application of Mix Optimization Scheduling Approach for Steelmaking-Continuous Casting Process Based on Actual Steelmaking Industry

The models, algorithms and implementation results of a computerized scheduling system were introduced for the steelmaking-continuous casting process (SCCP) of a steel plant in China. The scheduling of SCCP in this plant required that each cast plan should be processed on time, the charges in the same cast should be processed continuously on the same caster, and the waiting time of the charges which are in front of each caster cannot exceed the given threshold. At the same time, the processing time of charges cannot be conflicted mutually in the same converters or refining furnaces. Based on the research background, a hybrid optimal scheduling approach and its application were discussed. Aiming at the main equipment scheduling, an optimal scheduling method was proposed which consisted of equipment assignment algorithm based on dynamic program (DP) technique and conflict elimination algorithm based on linear program (LP) technique. The approach guarantees that the charges are continuously processed on the same caster. Meanwhile, the requirement for high temperature ladle can also be satisfied due to the ladle matching function. Numerical results demonstrate solution quality, computational efficiency, and values of the models and algorithm.     

基于变量选择的尖点突变模型的两步构建方法

突变是工程实践过程中广泛存在的现象.当系统的状态发生跳跃性变化时,基于微积分的传统数学建模方法精度较低,人工神经网络等机器学习算法无法对突变现象作出合理的解释.基于突变理论的尖点突变模型可以用来解释系统状态的不连续变化,然而在输入变量维度较大的情况下,传统的尖点突变模型复杂度高且精度较差.为了解决这一问题,提出了一种基于变量选择的尖点突变模型的两步构建方法.第一步,利用多模型集成重要变量选择算法(MEIVS)量化待选变量的重要性并提取重要变量;第二步,基于极大似然法(MLE)利用所提取的重要变量构建尖点突变模型.仿真结果表明,在具有突变特征的数据集上,通过MEIVS降维后的尖点突变模型在评价指标上优于线性模型、Logistic模型和通过其他方法降维的尖点突变模型,并且可以用来解释研究对象的不连续变化.     

On the efficacy of linear system analysis of renal autoregulation in rats

In order to assess the linearity of the mechanisms subserving renal blood flow autoregulation, broad-band arterial pressure fluctuations at three different power levels were induced experimentally and the resulting renal blood flow responses were recorded. Linear system analysis methods were applied in both the time and frequency domain. In the frequency domain, spectral estimates employing FFT, autoregressive moving average (ARMA) and moving average (MA) methods were used; only the MA model showed two vascular control mechanisms active at 0.02-0.05 Hz and 0.1-0.18 Hz consistent with previous experimental findings [Holstein-Rathlou et al., Amer. J. Physiol., vol. 258, 1990.]. In the time domain, impulse response functions obtained from the MA model indicated likewise the presence of these two vascular control mechanisms, but the ARMA model failed to show any vascular control mechanism at 0.02-0.05 Hz. The residuals (i.e., model prediction errors) of the MA model were smaller than the ARMA model for all levels of arterial pressure forcings. The observed low coherence values and the significant model residuals in the 0.02-0.05 Hz frequency range suggest that the tubuloglomerular feedback (TGF) active in this frequency range is a nonlinear vascular control mechanism. In addition, experimental results suggest that the operation of the TGF mechanism is more evident at low/moderate pressure fluctuations and becomes overwhelmed when the arterial pressure forcing is too high.     

Timoshenko Beam with Tuned Mass Dampers to Moving Loads

The structural analysis of a Timoshenko beam system with tuned mass dampers (TMDs) under moving-load excitation is presented. A proposed simplified two-degrees-of freedom system based on the first mode of the Timoshenko beam is employed for the design of TMDs. The dynamic characteristics of a Timoshenko beam, such as the structural-resonant and phase-resonant velocities, and the effectiveness of a TMD for vibrational control are especially emphasized. A practical example of an elevated railway subjected to the Japanese Shinkansen (SKS) high-speed bullet train is included.     

Adaptive Predictive Functional Control for Networked Control Systems with Random Delays

Nowadays, more and more field devices are connected to the central controller through a serial communication network such as fieldbus or industrial Ethernet.Some of these serial communication networks like controller area network (CAN) or industrial Ethernet will introduce random transfer delays into the networked control systcms (NCS), which causes control performance degradation and even system instability.To address this problem, the adaptive predictive functional control algorithm is derived by applying the concept of predictive functional control to a discrete state space model with variable delay.The method of estimating the networkinduced delay is also proposed to facilitate the control algorithm implementing.Then, an NCS simulation research based on TrueTime simulator is carried out to validate the proposed control algorithm. The numerical simulations show that the proposed adaptive predictive functional control algorithm is effective for NCS with random delays.     

Extreme Value of Response to Nonstationary Excitation

An efficient method is presented for approximate computation of extreme value characteristics of the response of a linear structure subjected to nonstationary Gaussian excitation. The characteristics considered are the mean and standard deviation of the extreme value and fractile levels having specific probabilities of not being exceeded by the random process within a specified time interval. The approximate procedure can significantly facilitate the utilization of nonstationary models in engineering practice, since it avoids computational difficulties associated with direct application of extreme value theory. The method is based on the approximation of the cumulative distribution function (CDF) of the extreme value of a nonstationary process by the CDF of a corresponding “equivalent” stationary process. Approximate procedures are developed for both the Poisson and Vanmarcke approaches to the extreme value problem, and numerical results are obtained for an example problem. These results demonstrate that the simple approximate method agrees quite well with the direct application of extreme value theory, while avoiding the difficulties associated with solution of nonlinear equations containing complicated time integrals.     

Nonlinear Response of Double-Wall Cylindrical Shell Vibrations under Random Excitation

An analytical model is presented to predict the nonlinear response of a double-wall sandwich cylindrical shell system subjected to random excitation. Nonlinear spring-dashpot models are integrated into the system to characterize the behavior of the soft core. Donnell’s thin shell theory is used to develop the governing nonlinear equations of motion. A Monte Carlo simulation of stationary random processes, multimode Galerkin-type approach, and numerical integration procedures are used to develop linear and nonlinear response solutions of simply supported cylindrical shells. Numerical results include time domain response histories, root-mean-square values and response spectral densities. Parametric studies are performed to investigate the effects of nonlinearity, shell thickness, core stiffness, and thickness.