Energy-based control of a distributed solar collector field

Model-based control of the outlet temperature of a distributed solar collector field is studied. An energy-based controller is derived using internal energy as a controlled variable. The controller relies on a distributed parameter nonlinear plant model and includes feedforward from the solar irradiation and inlet temperature. Convergence of the closed loop is proved, and the method is experimentally verified to perform well on a pilot-scale solar power plant.     

Model-based temperature control of a diesel oxidation catalyst

The problem studied in this article is the control of a DOC (diesel oxidation catalyst) as used in aftertreatment systems of diesel vehicles. This system is inherently a distributed parameter system due to its elongated geometry where a gas stream is in contact with a spatially distributed catalyst. A first contribution is a model for the DOC system. It is obtained by successive simplifications justified either experimentally (from observations, estimates of orders of magnitude) or by an analysis of governing equations (through asymptotic developments and changes of variables). This model can reproduce the complex temperature response of DOC output to changes in input variables. In particular, the effects of gas velocity variations, inlet temperature and inlet hydrocarbons are well represented. A second contribution is a combination of algorithms (feedback, feedforward, and synchronization) designed to control the thermal phenomena in the DOC. Both contributions have been tested and validated experimentally. In conclusion, the outcomes are evaluated: using the approach presented in this article, it is possible to control, in conditions representative of vehicle driving conditions, the outlet temperature of the DOC within ±15 °C.     

Boundary control of a parallel-flow heat exchanger by input–output linearization

A design of the control of the internal fluid temperature at the outlet of a parallel-flow heat exchanger by manipulating the inlet external fluid temperature is proposed. The dynamic model of the heat exchanger is given by two partial differential equations that are used without spatial discretization to design the control law. Based on nonlinear control, a state-feedback law that ensures a desired performance of a measured output defined as the spatial weighted average temperature of the internal fluid is derived. Then, in order to control the outlet internal fluid temperature, a control strategy is proposed where an external controller is introduced to provide the set point of the considered measured output by taking as input the error between the outlet internal fluid temperature and its desired set point. As the designed control law is a state feedback of distributed nature, for practical application, a Kalman filter is used to reconstruct the entire state of the system from the measurements of the outlet fluids temperatures. The closed-loop system is shown to be exponentially stable. The validity of the proposed control design is examined in simulation by considering the tracking and perturbation rejection problems.     

Monitoring defects of ceramic tiles using fuzzy subtractive clustering-based system identification method

In this paper, a subtractive clustering fuzzy identification method and a Sugeno-type fuzzy inference system are used to monitor tile defects in tile manufacturing process. The models for the tile defects are identified by using the firing mechanical resistance, water absorption, shrinkage, tile thickness, dry mechanical resistance and tiles temperature as input data, and using the concavity defect and surface defects as the output data. The process of model building is carried out by using subtractive clustering in both the input and output spaces. A minimum error model is developed through exhaustive search of clustering parameters. The fuzzy model obtained is capable of predicting the tile defects for a given set of inputs as mentioned above. The fuzzy model is verified experimentally using different sets of inputs. This study intends to examine and deal with the experimental results obtained during various stages of ceramic tile production during 90-day period. It is believed, that the results obtained from the present study could be considered in other ceramic tiles industries, which experienced similar forms of defects.     

Two adaptive control structures of robot manipulators

This paper proposes two simple adaptive control schemes of robot manipulators. The first one is the state feedback control which consists of feedforward from the desired position trajectory, PD feedback from the actual trajectory, and an auxiliary input. The second one is the feedforward/feedback control which consists of a feedforward term from the desired position, velocity, and acceleration trajectory based on the inverse of robot dynamics. The feedforward, feedback, and auxiliary gains are adapted using simple equations derived from the decentralized adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a priori knowledge of the detail parameters of the manipulator or the payload. Simulation results are presented in support of the proposed schemes. The results demonstrate that both controllers perform well with bounded adaptive gains.     

Feedforward—feedback control of distributed parameter systems†

Regulatory control of distributed systems subjected to load disturbances is considered by using feedforward and state measure control configurations. Dynamic compensation of the feedforward signal is accomplished with a lead-lag function, the time constants of which are determined by means of a numerical search technique. Compensation of the state measure signal is provided by the distributed nature of the process itself. Exit temperature regulation of a tubular heat exchanger acted upon by velocity and inlet temperature disturbances is considered as an application for feedforward control. Considerably better performance is obtained with the addition of dynamic compensation to the feedforward signal. State measure control is applied to the exchanger for a feed temperature upset and the effects of sensor location on outlet performance are investigated. An optimal sensor location is determined which minimizes the integral-square error at the outlet.     

Adaptive UKF-based model predictive control of a Fresnel collector field

One of the ways to improve the efficiency of solar energy plants is by using advanced control and optimization algorithms. In particular, model predictive control strategies have been applied successfully in their control.The control objective of this kind of plant is to regulate the solar field outlet temperature around a desired set-point. Due to the highly nonlinear dynamics of these plants, a simple linear controller with fixed parameters is not able to cope with the changing dynamics and the multiple disturbance sources affecting the field.In this paper, an adaptative model predictive control strategy is designed for a Fresnel collector field belonging to the solar cooling plant installed at the Escuela Superior de Ingenieros in Sevilla. The controller changes the linear model used to predict the future evolution of the system with respect to the operating point.Since only the inlet and outlet temperatures of the heat transfer fluid are measurable, the intermediate temperatures have to be estimated. An unscented Kalman filter is used as a state estimator. It estimates metal-fluid temperature profiles and effective solar radiation.Simulation results are provided comparing the proposed strategy with a PID + feedforward series controller showing better performance. The controller is also compared to a gain scheduling generalized predictive controller (GS-GPC) which has previously been tested at the actual plant with a very good performance. The proposed strategy outperforms these two strategies.Furthermore, two real tests are presented. These tests show that the proposed controller achieves adequate set-point tracking in spite of strong disturbances.     

快速调节加热炉燃气量的控制系统

加热流体温度关系到加热炉的生产安全和能量的合理利用．采用出口温度控制加热炉燃气量,导致自动控制系统存在滞后性,造成出口温度大幅度变化．甚至加热管烧焦现象。提出利用加热介质入口参数辅助加热管出口温度控制加热炉燃气量．通过预估控制法计算燃气量,采用模糊控制技术评价出口温度,设计了一种新的快速调节加热炉燃气量的控制系统．进行了现场应用。结果表明,改造后加热炉的控制系统性能得到较好的改善．出口温度最大偏差减小4．28％,稳定时间提高12h．效率提高5．5％。     

Activatable tiles for compact robust programmable molecular assembly and other applications

Algorithmic DNA self-assembly is capable of forming complex patterns and shapes, that have been shown theoretically, and experimentally. Its experimental demonstrations, although improving over recent years, have been limited by significant assembly errors. Since 2003 there have been several designs of error-resilient tile sets but all of these existing error-resilient tile systems assumed directional growth of the tiling assembly. This is a very strong assumption because experiments show that tile self-assembly does not necessarily behave in such a fashion, since they may also grow in the reverse of the intended direction. The assumption of directional growth of the tiling assembly also underlies the growth model in theoretical assembly models such as the TAM. What is needed is a means for enforce this directionality constraint, which will allow us to reduce assembly errors. In this paper we describe a protection/deprotection strategy to strictly enforce the direction of tiling assembly growth so that the assembly process is robust against errors. Initially, we start with (1) a single “activated” tile with output pads that can bind with other tiles, along with (2) a set of “deactivated” tiles, meaning that the tile’s output pads are protected and cannot bind with other tiles. After other tiles bind to a “deactivated” tile’s input pads, the tile transitions to an active state and its output pads are exposed, allowing further growth. When these are activated in a desired order, we can enforce a directional assembly at the same scale as the original one. Such a system can be built with minimal modifications of existing DNA tile nanostructures. We propose a new type of tiles called activatable tiles and its role in compact proofreading. Activatable tiles can be thought of as a particular case of the more recent signal tile assembly model, where signals transmit binding/unbinding instructions across tiles on binding to one or more input sites. We describe abstract and kinetic models of activatable tile assembly and show that the error rate can be decreased significantly with respect to Winfree’s original kinetic tile assembly model without considerable decrease in assembly growth speed. We prove that an activatable tile set is an instance of a compact, error-resilient and self-healing tile-set. We describe a DNA design of activatable tiles and a mechanism of deprotection using DNA polymerization and strand displacement. We also perform detailed stepwise simulations using a DNA Tile simulator Xgrow, and show that the activatable tiles mechanism can reduce error rates in self assembly. We conclude with a brief discussion on some applications of activatable tiles beyond computational tiling, both as (1) a novel system for concentration of molecules, and (2) a catalyst in sequentially triggered chemical reactions.     

Mixed Logical Dynamical Nonlinear Model Predictive Controller for Large‐Scale Solar Fields

This paper presents a control algorithm for reducing heat losses caused by clouds in large solar fields. The formulation is based on a Mixed Logical Dynamical (MLD) representation of the solar field plus the application of a Practical Nonlinear Model Predictive Controller (PNMPC) for calculating the optimal control action. The main purpose of the controller is to deactivate fields with inlet temperature greater than outlet temperature and to manipulate the oil flow rate of the activated fields for tracking the reference of the outlet temperature. A simplified lumped parameters model is used for prediction and simulation of the solar fields.     

Cascade control of a distributed collector solar field

This paper reports experimental results on the cascade control of a distributed collector solar field. The control problem consists of keeping constant the field outlet oil temperature by acting on the circulating oil flow used for heat transfer. In the inner loop an adaptive model based predictive controller exploiting the information conveyed by accessible disturbances (radiation changes and inlet oil temperature) is used, while in the outer loop a PID is employed. The need for adaptive control arises from the time varying behaviour of the plant. Due to the generality of the methods employed, the experience reported is relevant to a wide class of industrial processes.     

Convergence rates of Markov chains for some self-assembly and non-saturated Ising models

Algorithms based on Markov chains are ubiquitous across scientific disciplines as they provide a method for extracting statistical information about large, complicated systems. For some self-assembly models, Markov chains can be used to predict both equilibrium and non-equilibrium dynamics. In fact, the efficiency of these self-assembly algorithms can be related to the rate at which simple chains converge to their stationary distribution. We give an overview of the theory of Markov chains and show how many natural chains, including some relevant in the context of self-assembly, undergo a phase transition as a parameter representing temperature is varied in the model. We illustrate this behavior for the non-saturated Ising model in which there are two types of tiles that prefer to be next to other tiles of the same type. Unlike the standard Ising model, we also allow empty spaces that are not occupied by either type of tile. We prove that for a local Markov chain that allows tiles to attach and detach from the lattice, the rate of convergence is fast at high temperature and slow at low temperature.     

基于MPI的大规模栅格影像并行瓦片化算法

当前主流GIS软件以及互联网地图应用在WebGIS（网络地理信息系统）解决方案中都广泛采用地图切片（又称瓦片）,切片处理服务是实现影像在WebGIS上快速无缝浏览的关键技术。针对目前传统算法以及商业GIS软件在大数据量栅格影像快速瓦片化方面的不足,提出一种名为ParaTile的高效栅格影像快速瓦片化方法,ParaTile基于MPI共享外存的并行技术,利用多进程对原始栅格影像进行数据划分,每个进程对其所划分的区域进行独立读写和计算,而后再按照TMS或者Google Tile定义的标准将瓦片进行编码输出。实验采用不同级别大小的遥感影像进行测试,结果表明ParaTile在面对不同规模的数据时,无论从速度还是算法稳定性上都较现有算法和工具具有显著优势,特别是当数据量越大时,这种优势愈加明显。     

模糊前馈-反馈控制在药品酯化过程控制的应用

针对制药生产过程控制中间歇式反应釜温度控制非线性和大滞后的特点，提出了模糊前馈—反馈控制的方法，并对模糊控制器的一般设计方法进行了研究，简化了模糊控制器的设计过程，实际控制结果表明本设计方案的可用性和有效性。     

A replication strategy for a distributed high-speed caching system based on spatiotemporal access patterns of geospatial data

Distributed high-speed caching uses replication strategies to improve the parallel service efficiency in data-intensive services in cloud-based environments. This paper proposes a replication strategy based on the access pattern of tile in order to optimize load balancing for large-scale user access in cloud-based WebGISs. First, this strategy considers the access bias and repeatability involved in tile access, to cache tiles with higher popularities, and obtains a higher cache hit rate under limited distributed caches. Second, on the basis of the uneven distribution and temporal local changes of tile access, it generates hot tile replicas with a seat allocation scheme to efficiently allocate the distributed cache. Finally, it balances the load for tile access requests based on the spatial correlation and spatial locality in tile access patterns to achieve fast data extraction. Experimental results indicate that the proposed strategy can be adopted to handle numerous WebGISs tile requests in a cloud-based environment.     

基于边界特征配准的墙地砖缺陷检测研究

该文结合radon变换和几何推理,研究了基于墙地砖边界的用于规则图案表面缺陷检测的图像配准方法。实验证明该算法简单快捷,能检测出墙地砖的一般常见缺陷。     

基于模糊神经网络大容量输油泵多变量控制

大容量输油泵系统是一个时变非线性复杂系统,生产要求对输油泵的流量、入口压力和出口压力进行协调控制.根据大容量输油泵系统实际控制要求,提出了基于模糊神经网络大容量输油泵多变量控制策略,设计了控制系统和模糊神经网络控制器的结构,给出了模糊神经网络控制器、模型辨识网络参数的修正算法.仿真结果表明该系统能根据流量、入口压力和出口压力给定值与实际值之间的偏差,在线修正控制器参数,实现对大容量输油泵流量、入口压力和出口压力的协调控制.     

基于模糊逻辑与遗传算法的燃料电池热管理方法研究

有效的质子交换膜燃料电池(Proton Exchange Membrane Fuel Cell,PEMFC)热管理是提升氢燃料电池汽车安全性、耐久性以及运行效率的关键因素之一.该文提出一种PEMFC电堆热管理控制方法,使电堆出入口温度保持在设定值.该方法以PEMFC热管理系统模型中电堆出入口温度的变化为依据,设计一种二...     

一种改进DCGANs网络的磁瓦缺陷图像生成方法研究

基于机器视觉的磁瓦表面缺陷检测研究对于改进磁瓦生产工艺、提升磁瓦生产效率有着重要意义.但在研究过程中,存在磁瓦含缺陷样本收集困难、不同缺陷样本数不均匀、缺陷类型单一等问题.本文提出一种使用高斯混合模型的深度卷积生成对抗网络(Gaussian Mixture Model Deep Convolution Generative Adversarial Networks,GMM-DCGANs)生成含缺陷磁瓦图像的方法.在深度卷积生成对抗网络的基础上,将生成图像的输入噪声潜在空间复杂化为高斯混合模型,从而提高图像生成网络对有限数量且具有类间及类内多样性训练样本的学习能力.实验结果表明,GMMDCGANs网络可以生成质量更好、缺陷类型更加丰富的磁瓦缺陷图像,并且生成的图像满足缺陷检测及分类的要求.