Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

基于优化粒子数和分段权值的粒子群直线电机PID整定

以工程中直线电机伺服系统为研究对象,提出一种优化粒子数量加分段式惯性权重递减的粒子群PID控制器参数优化算法。优化粒子数量的方法可降低函数调用次数,通过对近两代的全局最优值进行比较,得到的误差值如果大于设定值,认为是在初始寻优阶段,保持粒子数量,否则在最终优化阶段,减少粒子数量,所减少的粒子特征是最接近最佳粒子的粒子,以保证在欧氏距离内实现粒子的分散性。最后再结合指数衰减曲线加线性递减曲线构成的分段式惯性权重递减策略提升算法的全局寻优和局部寻优能力。经数值验证分析,该优化算法在保证遍历性的同时,在一定程度上提高了算法的运行速度和寻优精度。实验仿真结果表明,该算法对PID控制器进行参数优化,直线电机系统响应速度快,超调量小,调节时间短。     

LD27-2油田稠油油藏蒸汽吞吐中后期注采参数优化研究

蒸汽吞吐是稠油油藏开发的最有效措施之一，但是对于海上油田的特殊条件，在进行蒸汽吞吐3~4轮后，即意味着进入蒸汽吞吐中后期。此时，如何调整注采参数，是海上稠油油藏高效开发的关键。针对LD27-2油田稠油油藏的开发特点，在地质建模和高度历史拟合的情况下，对LD27-2油田稠油油藏开发状况进行多轮次预测；基于生产历史拟合的油藏数值模型，开展了不同蒸汽干度、注汽强度、注汽强度递增等条件下A22H井和A23H井蒸汽吞吐至开采至10年的油藏数值模拟，明确不同注采参数的影响规律，优化了LD27-2油田稠油油藏蒸汽吞吐中后期注采参数。     

Modeling of sequence length distribution for olefin copolymerization with vanadium-based catalyst

Some thermodynamic and mechanical properties of a polyolefin, such as the melting temperature and the rigidity, are dependent on the nature of its sequence distribution. Accurate modeling of sequence length distribution (SLD) is important in precisely tuning and optimizing the properties of polymers produced. In this article, we proposed a model to predict the molecular weight distribution (MWD) and SLD for olefin copolymerization with vanadium-based catalyst. Due to the 2,1-insertion of α-olefin with vanadium-based catalyst, the SLD is expressed by uninterrupted methylene sequence distribution instead of conventional triad sequence distribution. To obtain a reliable model, parameter estimation with experimental data is first conducted. The SLD model along with the estimated kinetic parameters can be used to predict unmeasurable sequence length fraction. For the experimental conditions studied, the average methylene sequence length is predicted to change from 10 to 4 units as the propylene/ethylene mole feed ratio increases from 1.1 to 3.4.     

Optimal parameter estimation for PEMFC using modified monarch butterfly optimization

The present study develops a new optimization method called monarch butterfly optimization algorithm for optimal parameter estimation of the polymer electrolyte membrane fuel cell (PEMFC). After designing the proposed methodology, it is implemented to 250 MW PEMFC stack under different operating conditions to show the system efficiency and the results are compared with some state-of-the-art methods including Grass Fibrous Root Optimization Algorithm, hybrid Teaching Learning Based Optimization-Differential Evolution Algorithm, and the basic MBO algorithm. Two operational conditions in 3/5 bar and 80°C and 2.5/3 bar, 70°C are used for model verification. The main idea is to minimize the sum of square error (SSE) between the estimated and the actual data. Simulation results in the first condition give an SSE of value 7.277667729 with 9.28434e−16 SD value and in the second condition, an SSE of value 4.52810115 with 0.043581628 standard deviations has been reached as the minimum value among the other compared methods that indicate the accuracy and the robustness of the suggested method toward the analyzed methods. The algorithm also gives a convergence speed of 540 iterations and 370 iterations for conditions 1 and 2, respectively that are the fastest in the study.     

基于地表温度和植被指数的黑龙江省旱情遥感动态监测

干旱灾害是一种影响范围广、时间跨度大的自然灾害,对社会经济发展尤其是给农业生产造成重大损失。遥感技术具有观测空间尺度大、实时性强的特点,有利于大范围、实时、动态的旱情监测。利用MODIS的LST和NDVI遥感数据,依托站点实测土壤含水率数据,分析土壤含水率与地表温度和植被指数之间的关系,考虑土壤类型,构建温度植被多项式模型,进行表层土壤水分反演,基于此开展2018年3~7月黑龙江省旱情遥感监测应用研究。监测结果显示,监测期内黑龙江省经历了两次规模较大的干旱过程,干旱的核心区域为黑龙江省西南部区域,与实际情况相吻合。研究表明,考虑土壤类型的温度植被多项式模型对旱情遥感监测具有良好的应用效果。     

ZKB型直线振动筛侧板裂纹研究及寿命分析

为了解直线振动筛侧板裂纹的综合性能,首先对侧板进行静力学分析得到侧板危险区域。其次对该区域进行裂纹布置,应用断裂力学理论对振动筛侧板进行应力强度因子的计算,分析侧板危险区域裂纹扩展特性,同时针对不同形状、大小的裂纹进行参数分析,得到振动筛侧板裂纹扩展规律。最后对侧板进行疲劳寿命计算,得到含初始裂纹处侧板的疲劳寿命及安全系数,为侧板的设计优化提供理论指导。     

RV减速器摆线针轮齿廓修形回差影响分析

针对RV减速器回差精度问题,建立了摆线针轮齿廓修形的回差精度数值分析模型,采用几何法求解各种常见修形方式产生的几何回差,同时考虑摆线针轮传动中的弹性回差,推导出摆线轮齿廓修形的回差影响公式,并讨论了同一摆线轮齿廓修形方式下不同的修形参数与同一修形参数下不同的修形方式对回差的影响,得出在同一修形量的条件下,等距加移距的组合修形方式的回差影响最小,移距修形的回差影响最大。对RV-40E型减速器样机进行试验验证,与传统回差公式相比较,文章推导的回差公式精度提高6%左右。     

Disturbance observer-based adaptive boundary iterative learning control for a rigid-flexible manipulator with input backlash and endpoint constraint

In this article, an observer-based adaptive boundary iterative learning control law is developed for a class of two-link rigid-flexible manipulator with input backlash, the unknown external disturbance, and the endpoint constraint. To tackle the backlash nonlinearities and ensure the vibration suppression, the disturbance observers based upon the iterative learning conception are considered in the adaptive boundary control design. A barrier Lyapunov function is incorporated with boundary control law to restrict the endpoint state. Based on the defined barrier composite energy function, the tracking angle error convergence of the rigid part is guaranteed, and the vibrations of the flexible part are suppressed through the rigorous analysis. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed control.     

地质统计学反演在薄煤层预测中的应用

曙光煤矿煤层多为薄煤层,利用地震数据常规反演技术预测开采区域煤层厚度的分辨能力有限,远低于煤层开采的需要。引入基于MCMC算法的地质统计学反演技术对曙光煤矿采区内薄煤层进行厚度预测。预测结果与常规解释结果进行对比,并利用已有钻孔资料进行验证,发现该方法的分辨率可达到1 m,对煤层厚度、煤中夹矸厚度的预测误差分别控制在0.5、0.1 m以内。有效解决了曙光煤矿薄煤层预测问题。