An intelligent EGWO-SCA-CS algorithm for PSS parameter tuning under system uncertainties

This paper proposes a novel hybrid technique called enhanced grey wolf optimization-sine cosine algorithm-cuckoo search (EGWO-SCA-CS) algorithm to improve the electrical power system stability. The proposed method comprises of a popular grey wolf optimization (GWO) in an enhanced and hybrid form. It embraces the well-balanced exploration and exploitation using the cuckoo search (CS) algorithm and enhanced search capability through the sine cosine algorithm (SCA) to elude the stuck to the local optima. The proposed technique is validated with the 23 benchmark functions and compared with state-of-the-art methods. The benchmark functions consist of unimodal, multimodal function from which the best suitability of the proposed technique can be identified. The robustness analysis also presented with the proposed method through boxplot, and a detailed statistical analysis is performed for a set of 30 individual runs. From the inferences gathered from the benchmark functions, the proposed technique is applied to the stability problem of a power system, which is heavily stressed with the nonlinear variation of the load and thereby operating conditions. The dynamics of power system components have been considered for the mathematical model of a multimachine system, and multiobjective function has been framed in tuning the optimal controller parameters. The effectiveness of the proposed algorithm has been assessed by considering two case studies, namely, (i) the optimal controller parameter tuning, and (ii) the coordination of oscillation damping devices in the power system stability enhancement. In the first case study, the power system stabilizer (PSS) is considered as a controller, and a self-clearing three-phase fault is considered as the system uncertainty. In contrast, static synchronous compensator (STATCOM) and PSS are considered as controllers to be coordinated, and perturbation in the system states as uncertainty in the second case study.     

烟气CO2捕集热能梯级利用节能工艺耦合优化

醇胺法捕集CO₂技术是一种较成熟的CO₂捕集技术，具有吸收速度快、脱除效果好等显著优点，但其操作费用高、解吸能耗大。本文以降低醇胺法捕集烟气中CO₂系统再生能耗为出发点，对常规醇胺法捕集CO₂工艺统进行了节能优化研究。在常规工艺流程基础上引入压缩式热泵节能技术，并利用Aspen Plus软件建立了基于压缩式热泵技术的CO₂捕集工艺流程模型。研究了压缩式热泵与机械蒸汽压缩回收（MVR）热泵、分流解吸、分布式换热、级间冷却4种节能工艺耦合，通过模拟计算与优化，结果说明了最佳节能工艺组合为“解吸塔压缩式热泵+贫液MVR热泵+分流解吸+级间冷却”耦合的CO₂捕集工艺流程，当解吸塔顶气体分流比为0.25∶0.75、冷富液分流比为0.05∶0.95、级间冷却器位于吸收塔17块塔板位置、吸收塔输入冷量为-3.0GJ/h时，系统再生能耗最低，为2.533 GJ/tCO₂，相比常规有机胺工艺（再生能耗4.204GJ/tCO₂）节能率39.748%。     

大方坯结晶器电磁搅拌器结构优化

为改善连铸结晶器内钢液的流动状况，采用有限元法和有限容积法研究了大方坯结晶器电磁搅拌器结构对连铸结晶器内电磁场、流场和温度场分布的影响。结果表明，新型结晶器电磁搅拌器在400 A、3 Hz时产生的电磁力比传统结晶器电磁搅拌器在500 A、3 Hz时产生的电磁力更加均匀，对结晶器内钢液的扰动更强，可提高结晶器内的传热效率，有助于初始凝固坯壳和等轴晶的形成，改善方坯质量。     

γ辐照加工用新型工作模体设计研究

本文研究设计了一种用于获取γ辐照装置辐射场和货物剂量场真实分布的新型工作模体。基于真实γ辐照装置参数构建了有效可用的模拟辐射场，提出了新型工作模体的结构和填料设计方法。采用蒙特卡罗方法和随机填充方法（RCS）模拟计算剂量计套管材料与壁厚、填料小球尺寸、空心填料小球尺寸与壁厚、小球填充方式等影响模体剂量学性能的主要因素的分布规律。在满足计算置信度的前提下，参数优化取值范围为：套管采用壁厚为3~5 mm的铝管，对辐射场干扰不超过4.372 23%；填料选择外径为1~4 cm、壁厚为1.1~11.5 mm、材料等效性好、货物密度模拟范围为0.1~0.5 g/cm³的聚丙烯小球，对辐射场干扰不超过9.998 44%；均匀填充和随机填充模式对辐射场干扰基本持平，且均不超过10%。结果表明，当前设计可行有效，投入低、兼顾参数多且量程更宽，适合推广应用。     

Robust predictive extended state observer for a class of nonlinear systems with time-varying input delay

ABSTRACT

This paper deals with asymptotic stabilisation of a class of nonlinear input-delayed systems via dynamic output feedback in the presence of disturbances. The proposed strategy has the structure of an observer-based control law, in which the observer estimates and predicts both the plant state and the external disturbance. A nominal delay value is assumed to be known and stability conditions in terms of linear matrix inequalities are derived for fast-varying delay uncertainties. Asymptotic stability is achieved if the disturbance or the time delay is constant. The controller design problem is also addressed and a numerical example with an unstable system is provided to illustrate the usefulness of the proposed strategy.     

A novel minimum weight formulation of topology optimization implemented with reanalysis approach

In this paper, we develop an efficient diagonal quadratic optimization formulation for minimum weight design problem subject to multiple constraints. A high-efficiency computational approach of topology optimization is implemented within the framework of approximate reanalysis. The key point of the formulation is the introduction of the reciprocal-type variables. The topology optimization seeking for minimum weight can be transformed as a sequence of quadratic program with separable and strictly positive definite Hessian matrix, thus can be solved by a sequential quadratic programming approach. A modified sensitivity filtering scheme is suggested to remove undesirable checkerboard patterns and mesh dependence. Several typical examples are provided to validate the presented approach. It is observed that the optimized structure can achieve lighter weight than those from the established method by the demonstrative numerical test. Considerable computational savings can be achieved without loss of accuracy of the final design for 3D structure. Moreover, the effects of multiple constraints and upper bound of the allowable compliance upon the optimized designs are investigated by numerical examples.     

基于(火用)效率目标的环冷机余热回收系统操作参数优化

摘要：针对烧结环冷机余热回收利用率不高的难题，采用分析法建立了评价某钢铁厂烧结环冷机余热回收系统运行效率的效率模型。基于多孔介质模型、局部非热平衡方程、真实气体SRK方程建立环冷机内气固两相换热模型。通过CFD仿真模拟，探究料层高度、循环风机输入烟气温度、烧结矿底部入口风速三项可控环冷机运行工艺参数对系统效率的影响规律。结果表明，料层厚度在1～1.5 m区间每增加0.1 m，效率增加0.8%～1.1%；循环风温在100～140℃之间每增加10℃，效率增加1.4%～1.5%；烧结矿底部入口风速在0.9～1.9 m/s之间每增加0.1 m/s，效率降低0.18%～0.24%。在此基础上，基于工业运行数据建立效率正交试验优化模型，提高了该余热回收系统3.42%的效率。     

Robust orientation control of multi‐DOF cell based on uncertainty and disturbance estimation

Multiple degrees‐of‐freedom (multi‐DOF) cell orientation control is a vital important technique involved in single cell surgery applications. Currently, few studies have been performed toward automation of multi‐DOF cell orientation control using robotically controlled optical tweezers. In this paper, a robust control framework is developed to perform multi‐DOF cell rotational control with consideration of model uncertainties and external disturbances. Both simulation and experimental studies are presented to illustrate the performance of the proposed control strategy. The main contributions of this work lie in that this is the first time to develop a unified framework to achieve multi‐DOF cell orientation control without the need for accurate dynamic model parameters and/or any knowledge about uncertainty characteristic, which greatly enhances the robustness of the overall system.     

基于协同优化算法的流速仪检定系统设计

提出了一种小型轻便的流速仪检定系统的设计方案,并运用改进的多学科协同优化方法求解各学科设计变量的最优解。首先介绍了算法思想及改进措施,并根据系统设计要求建立了各学科的设计变量、目标函数和约束条件；其次,运用遗传算法求解各学科设计变量的最优解,并根据优化结果完善了系统的设计方案,同时运用计算机仿真等方法验证了优化结果的可行性。结果表明,优化后的检定系统满足流体力学效应、匀速运动时间、系统重量等设计要求,同时证明了协同优化算法解决多学科设计优化问题的有效性。     

A hierarchical simple particle swarm optimization with mean dimensional information

To reduce the negative influence of the overemphasis of gbest the dimensional information of particle is introduced to be a new example. This additional information source is incorporated into simple PSO to establish a simpler position model. Another two simpler position updating models, cognition only model and social only model, based on the simple PSO algorithm are presented as well. Time hierarchy strategy is extended from probability hierarchy, both aiming to make full use of advantages of three models. Three models are used with time or probability hierarchy to update each particle’s position. Thus, two proposed algorithms THSPSO and PHSPSO are finally obtained. Experiments are conducted on fifteen benchmark functions. The results demonstrate the two proposed algorithms both have excellent performances for basic functions compared with other popular PSO variants. Probability hierarchy strategy is more effective than time hierarchy strategy in general.