WSA制酸工艺主要过程控制系统设计与开发

WSA制酸工艺中熔盐系统温度控制直接影响到SO2→SO3的转化率和烟气净化效果。本文在简介了WSA制酸工艺、DeltaV系统之后重点描述了熔盐温度、烧嘴燃烧、风机控制与系统连锁等控制流程设计、策略与实现方法以及软件设计的情况。     

伴有初始负载摆角的桥式起重机能量防摆控制

桥式起重机是一种广泛应用的大型搬运设备,在实际工作过程中,台车运动时会产生伴有初始负载摆角的负载摆动,影响工作效率并带来安全隐患.针对这种情况,设定期望的台车误差轨迹和摆角误差轨迹,将桥式起重机动力学模型转换为误差跟踪动力学模型,提出一种基于能量分析方法的桥式起重机防摆控制策略.通过LaSalle不变性原理和Lyapunov方法对闭环系统的稳定性进行理论分析.仿真与实验结果表明,所提防摆控制方法的控制性能几乎不受初始负载摆角的影响,可以保证桥式起重机在无初始负载摆角和带有初始负载摆角的情况下都能取得良好的控制效果,能够驱动台车准确到达目标位置,有效抑制并快速消除负载摆角,同时对外部扰动具有很强的鲁棒性.     

Electro-mechanical Braking Method in Hybrid Electric Vehicles Based on Feedback Control Theory

In this paper, the hybrid electric vehicle braking process is researched, by using variables consists of HEV speed, motor speed, and state of charge established, fimctions of mechanical braking force, regenerative braking force and efficiency of energy recovery are constructed, and the control goal is to maximization the energy recovery efficiency. Under the feedback control strategy, with the constrain condition of braking strength and braking stability, combining experiments in ADVISOR, in different experiments of different working conditions, we can see that in UDDS Cycle, the regenerative braking efficiency is the best. What＇s more, compared with strategies in ADVISOR, strategy proposed in this paper is obviously better.     

面向交通能源融合的路侧单元传输控制优化策略

针对如何提高自供电路侧单元服务满足数量的问题,提出一种在自供电路侧单元平均能效约束下最大化满足车辆服务请求数量的传输控制策略.该策略按照待服务车辆权重次序以车辆位置和能量队列长度为系统状态作出传输控制决策.通过建立自供电路侧单元传输控制决策的马尔可夫链模型,对服务过程中平均完成请求数和平均能效进行分析,进而提出一个非线性优化问题并求解,获得最优传输控制策略及其调度参数.仿真结果表明,上述自供电路侧单元最优传输控制策略具有位置状态和能量状态的双门限结构,相比于贪婪策略和Q- learning方法分别在能效方面平均提升了20.55%与11.86%,在服务稳定性方面,相比于其他两种策略,停电概率与不服务概率分别平均下降了20.03%与15.14%,具有能效和稳定性上的优势.     

Predictive control of an activated sludge process: An application to the Viikinmäki wastewater treatment plant

In this work, we discuss the application of multivariable predictive control for the activated sludge process in a full-scale municipal wastewater treatment plant. Emphasis is given to the selection of a control configuration that contributes to minimising the economic costs while improving the removal efficiency of the nitrogen compounds. For this task, a simple dynamic matrix control algorithm is favoured for controlling the nitrogen concentrations at the end of the biological process. The behaviour of the activated sludge process is reproduced in a commercial simulator that acts as a real-time testing platform and that is also used for identifying the multivariable input–output models for the predictive controller. For demonstrating the effectiveness of the proposed approach, different control configurations are considered and compared against the aeration control strategies currently used at the plant. Based on the simulation results, this work shows the potentiality of the dynamic matrix control which is able to decrease the energy consumption costs and, at the same time, reduce the ammonia peaks and nitrate concentration in the effluent.     

MB40可编程控制器在车间空调自控系统中的应用

本文以某药厂的空调自动控制系统为例,介绍南瑞MB40可编程控制器在其系统上的应用.该控制系统基于HtMI、PLC、和变频器等自动化产品,实现了设备的技术升级与高效节能,体现出较高的性价比.本系统的实际运行显示:基于MB40开发的控制系统稳定可靠,操作直观简单,控制效率高,值得业界同行借鉴和推广.     

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.     

A general analysis and control framework for process systems with inventory recycling

In this work, we generalize our previous results concerning the impact of material recycling and energy recovery on plant dynamics and control. We define a generic class of integrated process systems, in which an extensive quantity that obeys conservation laws is recovered from the process output and recycled to the process feed; the operation of the system is assumed to be subject to time‐varying, measurable disturbances. We establish, in this general case, that integration is conducive to the emergence of a two‐time‐scale dynamic behavior and derive reduced‐order models for the dynamics in each time scale. Subsequently, we postulate a hierarchical control framework that exploits these dynamics results in the design of coordinated fast and slow feedback/feedforward controllers and formulate a stability result for the closed‐loop system. We demonstrate these concepts on a case study concerning an energy‐integrated process. Copyright © 2013 John Wiley & Sons, Ltd.     

Distributed economic MPC: Application to a nonlinear chemical process network

In the present work, we focus on the development and application of Lyapunov-based economic model predictive control (LEMPC) designs to a catalytic alkylation of benzene process network, which consists of four continuously stirred tank reactors and a flash separator. We initially propose a new economic measure for the entire process network which accounts for a broad set of economic considerations on the process operation including reaction conversion, separation quality and energy efficiency. Subsequently, steady-state process optimization is first carried out to locate an economically optimal (with respect to the proposed economic measure) operating steady-state. Then, a sequential distributed economic model predictive control design method, suitable for large-scale process networks, is proposed and its closed-loop stability properties are established. Using the proposed method, economic, distributed as well as centralized, model predictive control systems are designed and are implemented on the process to drive the closed-loop system state close to the economically optimal steady-state. Extensive simulations are carried out to demonstrate the application of the proposed economic MPC (EMPC) designs and compare them with a centralized Lyapunov-based model predictive control design, which uses a conventional, quadratic cost function that includes penalty on the deviation of the states and inputs from their economically optimal steady-state values, from computational time and closed-loop performance points of view.     

Non-centralised control strategies for energy-efficient and flexible manufacturing systems

The manufacturing industry is transforming towards smart, energy-efficient, and flexible manufacturing systems. In this regard, this work deals with the design of non-centralised control architectures to improve the energy efficiency of such systems and to promote their flexibility. Based on both the configuration of manufacturing systems and their coupling dynamics, these systems are divided into sub-systems, from which smaller control problems can be stated. Thus, control/management strategies can also be modularised to confer more flexibility to manufacturing systems. Then, by using suitable distributed optimisation techniques, and properly defining the consensus stages among the local controllers, the outputs from such controllers are optimally coordinated to minimise the total energy consumption of the whole system. The proposed control strategies are tested in simulation for a typical process line of automotive parts manufacturing industry, in which the main processing units are machine tools. Based on the obtained results, manufacturing systems and their control strategies could be suitably modularised using non-centralised control schemes, from which a closed-loop performance similar to its centralised counterpart can be achieved.     

一种引入Nelder-Mead算子的改进狼群搜索算法*

为了克服狼群搜索算法(WSA)存在的不足,提出一种新的混合优化算法,称之为引入Nelder-Mead算子的改进狼群搜索算法。该算法使每只狼在搜索中可利用群体信息和个体记忆来指导其搜索猎物,以提高算法的全局搜索能力;让每只狼在搜索中可使用Nelder-Mead方法,以弥补WSA算法在局部搜索能力上的不足。针对12个基准测试实例的实验结果表明, 该算法能够寻得更优的最优解,且鲁棒性更强。     

Visual word spatial arrangement for image retrieval and classification

We present word spatial arrangement (WSA), an approach to represent the spatial arrangement of visual words under the bag-of-visual-words model. It lies in a simple idea which encodes the relative position of visual words by splitting the image space into quadrants using each detected point as origin. WSA generates compact feature vectors and is flexible for being used for image retrieval and classification, for working with hard or soft assignment, requiring no pre/post processing for spatial verification. Experiments in the retrieval scenario show the superiority of WSA in relation to Spatial Pyramids. Experiments in the classification scenario show a reasonable compromise between those methods, with Spatial Pyramids generating larger feature vectors, while WSA provides adequate performance with much more compact features. As WSA encodes only the spatial information of visual words and not their frequency of occurrence, the results indicate the importance of such information for visual categorization.     

Energy efficiency and area spectral efficiency tradeoff for coexisting wireless body sensor networks共存无线体域网的能效和区域频效折中

The coexistence of wireless body sensor networks (WBSNs) is a very challenging problem, due to strong interference, which seriously affects energy consumption and spectral reuse. The energy efficiency and spectral efficiency are two key performance evaluation metrics for wireless communication networks. In this paper, the fundamental tradeoff between energy efficiency and area spectral efficiency of WBSNs is first investigated under the Poisson point process (PPP) model and Matern hard-core point process (HCPP) model using stochastic geometry. The circuit power consumption is taken into consideration in energy efficiency calculation. The tradeoff judgement coefficient is developed and is shown to serve as a promising complementary measure. In addition, this paper proposes a new nearest neighbour distance power control strategy to improve energy efficiency. We show that there exists an optimal transmit power highly dependant on the density of WBSNs and the nearest neighbour distance. Some important properties are also addressed in the analysis of coexisting WBSNs based on the IEEE 802.15.4 standard, such as the impact of intensity nodes distribution, optimal guard zone, and outage probability. Simulation results show that the proposed power control design can reduce the outage probability and enhance energy efficiency. Energy efficiency and area spectral efficiency of the HCPP model are better than those of the PPP model. In addition, the optimal density of WBSNs coexistence is obtained.     

电能量远程采集数据并发存取过程中Sybase数据库防死锁的设计

该文针对大型关系数据库Sybase在大量数据存取并发控制过程中经常发生死锁现象,严重影响应用程序的工作效率和稳定性的问题提出了一套解决方案,它包括:引入Delphi中的ActiveX控件(第三方控件):Fbook控件,替代Dbgrid控件来避免死锁现象;改变数据表的索引方式,减少超时机率;改变页锁为行锁,缩小锁定数据的范围;合理配置timeouts选项,正确授予和取消标准的用于本地服务器的超时代码;尽量减少子系统并发控制的数量,将大事务分解为若干个小事务进行处理。该方案已在某供电局电能量远程采集与分析系统中应用,效果较好。     

多能源电动汽车中的Fuzzy控制策略及仿真

多能源电动汽车的能量存储系统由锌空电池、镍氢电池和超大电容三种能量存储元件组成。锌空电池为负载提供基本能量。镍氢电池工作在中级能量区，并回收下坡和刹车过程中的能量。超大电容工作在尖峰负载区，为大加速度过程提供能量，在短时间内可以实现能量回收。该文在多能源电动汽车的模型基础上，针对能量管理系统(EMS)提出了一种模糊控制策略。EMS模糊控制策略的输入包括所需功率、镍氢电池的SOC和超大电容的SOC，模糊控制策略的输出包括三个能量存储元件的分配功率因子，每个输入和输出有不同的模糊量。仿真结果表明：模糊控制策略比简单查表控制策略在续驶里程、燃料经济性和效率等方面均有所改善。     

基于专家-模糊PID的冻结凿井智能流量控制研究

为有效提高煤矿冻结凿井效率,节省凿井能耗,本文设计了一种嵌入式专家-模糊PID流量控制系统,该系统结合了嵌入式系统高效、实时的控制性能和专家-模糊自适应控制的快、稳、准的控制效果,为煤矿冻结凿井流量智能控制提出了一种良好的解决方案。实验和仿真结果表明,在冻结凿井盐水流量控制中应用该控制器比单一的专家PID和模糊PID适应性更好、超调量更小、稳定速度更快,应用价值较高。     

Employing a Gaussian Particle Swarm Optimization method for tuning Multi Input Multi Output-fuzzy system as an integrated controller of a micro-grid with stability analysis

There are mainly two most essential problems in power networks, load frequency control and power flow management, which are grown recently because of growth in dimension/complication of grids. Present work suggests a controller based on fuzzy systems in which controller design is performed in a supervisory manner over a multiagent system aiming to control the frequency variation as well as generation cost minimization in the entire grid. The designing processes for low-frequency controller (LFC) and management are mostly performed separately, which results in the disruption of both outputs. This challenge is tackled in this paper by the integration of them in the designing process. Additionally, stability guarantee is in high importance in the power systems, which is neglected in most of the related works. The Gaussian particle swarm optimization (GPSO) algorithm is applied for determining the optimal values of the decision variables, which can also guarantee the stability of the system by adopting a chaotic map by Gaussian function to balance the seeking abilities of particles that promotes the computation effectiveness without affecting the efficiency of the fuzzy controller. Then, the stability situationof the fuzzy + GPSO method is derived that guarantees a suitable global exploration and rapid convergence, with no require to gradients.     

The parameterized level set method for structural topology optimization with shape sensitivity constraint factor

In recent years, the parameterized level set method (PLSM) has attracted widespread attention for its good stability, high efficiency and the smooth result of topology optimization compared with the conventional level set method. In the PLSM, the radial basis functions (RBFs) are often used to perform interpolation fitting for the conventional level set equation, thereby transforming the iteratively updating partial differential equation (PDE) into ordinary differential equations (ODEs). Hence, the RBFs play a key role in improving efficiency, accuracy and stability of the numerical computation in the PLSM for structural topology optimization, which can describe the structural topology and its change in the optimization process. In particular, the compactly supported radial basis function (CS-RBF) has been widely used in the PLSM for structural topology optimization because it enjoys considerable advantages. In this work, based on the CS-RBF, we propose a PLSM for structural topology optimization by adding the shape sensitivity constraint factor to control the step length in the iterations while updating the design variables with the method of moving asymptote (MMA). With the shape sensitivity constraint factor, the updating step length is changeable and controllable in the iterative process of MMA algorithm so as to increase the optimization speed. Therefore, the efficiency and stability of structural topology optimization can be improved by this method. The feasibility and effectiveness of this method are demonstrated by several typical numerical examples involving topology optimization of single-material and multi-material structures.

     

Stability analysis via the concept of Lyapunov exponents: a case study in optimal controlled biped standing

Balancing control is important for biped standing. In spite of large efforts, it is very difficult to design balancing control strategies satisfying three requirements simultaneously: maintaining postural stability, improving energy efficiency and satisfying the constraints between the biped feet and the ground. In this article, a proportional-derivative (PD) controller is proposed for a standing biped, which is simplified as a two-link inverted pendulum with one additional rigid foot-link. The genetic algorithm (GA) is used to search for the control gain meeting all three requirements. The stability analysis of such a deterministic biped control system is carried out using the concept of Lyapunov exponents (LEs), based on which, the system stability, where the disturbance comes from the initial states, and the structural stability, where the disturbance comes from the PD gains, are examined quantitively in terms of stability region. This article contributes to the biped balancing control, more significantly, the method shown in the studied case of biped provides a general framework of systematic stability analysis for certain deterministic nonlinear dynamical systems.     

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 1: Unconstrained optimization

This paper is the first one of the two papers entitled “Weighted Superposition Attraction (WSA)”, which is based on two basic mechanisms, “superposition” and “attracted movement of agents”, that are observable in many systems. Dividing this paper into two parts raised as a necessity because of their individually comprehensive contents. If we wanted to write these papers as a single paper we had to write more compact as distinct from its current versions because of the space requirements. So, writing them as a single paper would not be as effective as we desired.In many natural phenomena it is possible to compute superposition or weighted superposition of active fields like light sources, electric fields, sound sources, heat sources, etc.; the same may also be possible for social systems as well. An agent (particle, human, electron, etc.) may be supposed to move towards superposition if it is attractive to it. As systems status changes the superposition also changes; so it needs to be recomputed. This is the main idea behind the WSA algorithm, which mainly attempts to realize this superposition principle in combination with the attracted movement of agents as a search procedure for solving optimization problems in an effective manner. In this current part, the performance of the proposed WSA algorithm is tested on the well-known unconstrained continuous optimization functions, through a set of computational study. The comparison with some other search algorithms is performed in terms of solution quality and computational time. The experimental results clearly indicate the effectiveness of the WSA algorithm.