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Extended model predictive control scheme for smooth path following of autonomous vehicles

《机械工程前沿（英文）》 2022年第17卷第1期页码 4-4 doi: 10.1007/s11465-021-0660-4

摘要： This paper presents an extended model predictive control (MPC) scheme for implementing optimal path following of autonomous vehicles, which has multiple constraints and an integrated model of vehicle and road dynamics. Road curvature and inclination factors are used in the construction of the vehicle dynamic model to describe its lateral and roll dynamics accurately. Sideslip, rollover, and vehicle envelopes are used as multiple constraints in the MPC controller formulation. Then, an extended MPC method solved by differential evolution optimization algorithm is proposed to realize optimal smooth path following based on driving path features. Finally, simulation and real experiments are carried out to evaluate the feasibility and the effectiveness of the extended MPC scheme. Results indicate that the proposed method can obtain the smooth transition to follow the optimal drivable path and satisfy the lateral dynamic stability and environmental constraints, which can improve the path following quality for better ride comfort and road availability of autonomous vehicles.

关键词： autonomous vehicles vehicle dynamic modeling model predictive control path following optimization algorithm

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Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

《能源前沿（英文）》 doi: 10.1007/s11708-023-0912-6

摘要： With the promotion of “dual carbon” strategy, data center (DC) access to high-penetration renewable energy sources (RESs) has become a trend in the industry. However, the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids. In this paper, a multi-timescale optimal scheduling model is established for interconnected data centers (IDCs) based on model predictive control (MPC), including day-ahead optimization, intraday rolling optimization, and intraday real-time correction. The day-ahead optimization stage aims at the lowest operating cost, the rolling optimization stage aims at the lowest intraday economic cost, and the real-time correction aims at the lowest power fluctuation, eliminating the impact of prediction errors through coordinated multi-timescale optimization. The simulation results show that the economic loss is reduced by 19.6%, and the power fluctuation is decreased by 15.23%.

关键词： model predictive control interconnected data center multi-timescale optimized scheduling distributed power supply landscape uncertainty

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machine-learning-based system identification of dynamical systems under control: application towards the modelpredictive control of a highly nonlinear reactor system

《化学科学与工程前沿（英文）》 2022年第16卷第2期页码 237-250 doi: 10.1007/s11705-021-2058-6

摘要： Advanced model-based control strategies, e.g., model predictive control, can offer superior control of key process variables for multiple-input multiple-output systems. The quality of the system model is critical to controller performance and should adequately describe the process dynamics across its operating range while remaining amenable to fast optimization. This work articulates an integrated system identification procedure for deriving black-box nonlinear continuous-time multiple-input multiple-output system models for nonlinear model predictive control. To showcase this approach, five candidate models for polynomial and interaction features of both output and manipulated variables were trained on simulated data and integrated into a nonlinear model predictive controller for a highly nonlinear continuous stirred tank reactor system. This procedure successfully identified system models that enabled effective control in both servo and regulator problems across wider operating ranges. These controllers also had reasonable per-iteration times of ca. 0.1 s. This demonstration of how such system models could be identified for nonlinear model predictive control without prior knowledge of system dynamics opens further possibilities for direct data-driven methodologies for model-based control which, in the face of process uncertainties or modelling limitations, allow rapid and stable control over wider operating ranges.

关键词： nonlinear model predictive control black-box modeling continuous-time system identification machine learning industrial applications of process control

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多目标自适应优化模型预测控制——降低氧化锌回转窑的碳排放 Article

Ke Wei, Keke Huang, Chunhua Yang, Weihua Gui

《工程（英文）》 2023年第27卷第8期页码 96-105 doi: 10.1016/j.eng.2023.01.017

摘要：

The zinc oxide rotary kiln, as an essential piece of equipment in the zinc smelting industrial process, is presenting new challenges in process control. China's strategy of achieving a carbon peak and carbon neutrality is putting new demands on the industry, including green production and the use of fewer resources; thus, traditional stability control is no longer suitable for multi-objective control tasks. Although researchers have revealed the principle of the rotary kiln and set up computational fluid dynamics (CFD) simulation models to study its dynamics, these models cannot be directly applied to process control due to their high computational complexity. To address these issues, this paper proposes a multi-objective adaptive optimization model predictive control (MAO-MPC) method based on sparse identification. More specifically, with a large amount of data collected from a CFD model, a sparse regression problem is first formulated and solved to obtain a reduction model. Then, a two-layered control framework including real-time optimization (RTO) and model predictive control (MPC) is designed. In the RTO layer, an optimization problem with the goal of achieving optimal operation performance and the lowest possible resource consumption is set up. By solving the optimization problem in real time, a suitable setting value is sent to the MPC layer to ensure that the zinc oxide rotary kiln always functions in an optimal state. Our experiments show the strength and reliability of the proposed method, which reduces the usage of coal while maintaining high profits.

关键词： Zinc oxide rotary kiln Model reduction Sparse identification Real-time optimization Model predictive control Process control

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Fuzzy force control of constrained robot manipulators based on impedance model in an unknown environment

LIU Hongyi, WANG Fei, WANG Lei

《机械工程前沿（英文）》 2007年第2卷第2期页码 168-174 doi: 10.1007/s11465-007-0028-4

摘要： To precisely implement the force control of robot manipulators in an unknown environment, a control strategy based on fuzzy prediction of the reference trajectory in the impedance model is developed. The force tracking experiments are executed in an open-architecture control system with different tracking velocities, different desired forces, different contact stiffnesses and different surface figurations. The corresponding force control results are compared and analyzed. The influences of unknown parameters of the environment on the contact force are analyzed based on experimental data, and the tunings of predictive scale factors are illustrated. The experimental results show that the desired trajectory in the impedance model is predicted exactly and rapidly in the cases that the contact surface is unknown, the contact stiffness changes, and the fuzzy force control algorithm has high adaptability to the unknown environment.

关键词： predictive tracking corresponding stiffness algorithm

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HVAC系统的模糊预测函数控制器设计

吕红丽,贾磊,王雷,高瑞

《中国工程科学》 2006年第8卷第9期页码 65-68

摘要：

针对暖通空调HVAC系统中由于存在高度非线性、时变特征以及扰动和不确定性等因素而难以控制的特点，提出基于Takagi-Sugeno(T-S)模糊模型的预测函数控制器设计方法。该方法通过最小二乘辨识算法建立系统的模糊T-S模型，然后基于模糊全局线性化预测模型，采用预测函数控制算法设计系统控制律。仿真实验结果表明该算法是一种跟踪性能好、鲁棒性强的有效控制方法。与常规的PID控制器相比，该方法具有超调量小、调整时间短等优良的动态性能。

关键词： T-S模糊模型预测函数控制最小二乘算法 HVAC系统

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时滞系统的辨识及NARMA模型的修正

王冬青

《中国工程科学》 2006年第8卷第2期页码 39-43

摘要：

对现有神经网络对非线性时滞系统的时滞辨识方法进行了补充说明和分析，同时指出现有的NARMA模型修正方法对时滞系统的不当之处。以时滞系统神经网络预测控制为例，介绍了NARMA模型的正确修正方法，仿真证明了所提出的修正方法能获得好的控制性能及抗干扰能力。

关键词：辨识 NARMA模型神经网络预测控制

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Design and evaluation of a novel biopsy needle with hemostatic function

《机械工程前沿（英文）》 2023年第18卷第2期 doi: 10.1007/s11465-022-0738-7

摘要： Biopsy is a method commonly used for early cancer diagnosis. However, bleeding complications of widely available biopsy are risky for patients. Safer biopsy will result in a more accurate cancer diagnosis and a decrease in the risk of complications. In this article, we propose a novel biopsy needle that can reduce bleeding during biopsy procedures and achieve stable hemostasis. The proposed biopsy needle features a compact structure and can be operated easily by left and right hands. A predictive model for puncture force and tip deflection based on coupled Eulerian–Lagrangian (CEL) method is developed. Experimental results show that the biopsy needle can smoothly deliver the gelatin sponge hemostatic plug into the tissue. Although the hemostatic plug bends, the overall delivery process is stable, and the hemostatic plug retains in the tissue without being affected by the withdrawal of the needle. Further experiments indicate that the specimens are well obtained and evenly distributed in the groove of the outer needle without scattering. Our proposed design of biopsy needle possesses strong ability of hemostasis, tissue cutting, and tissue retention. The CEL model accurately predicts the peak of puncture force and produces close estimation of the insertion force at the postpuncture stage and tip position.

关键词： cancer diagnosis biopsy needle hemostatic function predictive model coupled Eulerian−Lagrangian

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飞航导弹高精度自适应预测控制设计

孙明玮,陈增强,袁著祉,任强,杨明

《中国工程科学》 2005年第7卷第10期页码 23-27

摘要：

飞航导弹的飞行主要是通过姿态稳定与调节来实现的。通过以小扰动模型为基础的导弹动力学特性分析，建立了导弹姿态控制回路的串级控制结构，并且以离散模型作为基于递推最小二乘法的自适应预测控制的被控对象，把原先响应较慢的质心控制转换为反应较快而且精度高的弹道角控制。根据导弹的特性，在姿态内回路采用广义预测控制，在弹道外回路采用一种积分形式的预测控制。在参考信号上，实现了质心指令到弹道指令的有效变换，为高精度小超调跟踪奠定了基础。这种方法实现了姿态参考信号与导引指令的统一，姿态控制与质心控制的统一，充分降低了对气动等数据的精度要求，参数选择简单。数值仿真结果说明了这种方法的有效性；提出了进一步的研究方向。

关键词：飞航导弹自适应控制模型预测控制鲁棒性

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Real-time mobile robot teleoperation via Internet based on predictive control

WANG Shihua, XU Bugong, WANG Shihua, ZHOU Yeming, LIU YunHui

《机械工程前沿（英文）》 2008年第3卷第3期页码 299-306 doi: 10.1007/s11465-008-0049-7

摘要： A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme based on the modified Smith predictor proposed is selected. To ensure the stability and transparency of the system, a dynamic model manager is designed based on the information exchange between the sensors at the master and slave sides. To precisely predict the time delay, a new timer synchronization algorithm is proposed. To decrease delay- jitter, a new data buffer scheme is performed. Force feedback and a virtual predictive display are introduced to enhance the real-time efficiency of teleoperation. The usefulness and effectiveness of the proposed method and system are proven by teleoperation experiments via the internet over a long distance.

关键词： predictive feedback virtual predictive distance synchronization algorithm

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Predictive model to decouple the contributions of friction and plastic deformation to machined surface

Subhash ANURAG, Yuebin GUO,

《机械工程前沿（英文）》 2010年第5卷第3期页码 247-255 doi: 10.1007/s11465-010-0097-7

摘要： Temperature on the machined surface is critical for surface integrity and the performance of a precision component. However, the temperature of a machined surface is challenging for in-situ measurement. Furthermore, the individual contribution of tool/work friction and plastic deformation of work materials to surface temperature is very difficult to quantify because the measured temperature is always the resultant temperature. This lack of understanding on the temperature distribution blocks the design of effective cutting tool geometries and materials to minimize surface temperature. This study provides a finite element method based on a predictive model to decouple the contributions of tool/work friction and material plastic deformation to surface temperature in a dry cutting process. The study shows that the plastic deformation of work material contributes to the majority of surface temperature, whereas the tool/work friction contribution is secondary. High temperatures are produced when more materials are plowed under the cutting edge. A large tool/work friction leads to higher surface temperatures, and the use of a cutting tool with physical properties in process simulation significantly improves the accuracy of predicted surface temperatures. Residual stress reversal from subsurface maximum residual to surface maximum residual stress may occur when tool/work friction increases.

关键词： surface temperature friction residual stress finite element analysis (FEA) dry cutting tool property

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用于并网逆变器的改进三矢量无差拍模型预测直接功率控制策略 None

Chen-wen CHENG, Heng NIAN, Long-qi LI

《信息与电子工程前沿（英文）》 2018年第19卷第11期页码 1420-1431 doi: 10.1631/FITEE.1601874

摘要：用于并网逆变器的传统模型预测直接功率控制，在每个控制周期只使用一个逆变器电压矢量，导致并网电流和功率出现大量谐波分量，降低电能质量。为提高稳态性能，预测控制需要很高的采样频率，同时由于计算复杂，预测算法需要较长执行时间，二者存在矛盾。为解决这个问题，提出一种新的无差拍模型预测直接功率控制策略，在每个控制周期使用2个有效电压矢量和1个零电压矢量。采用三矢量策略保证开关频率恒定，提高电流和功率质量。不同于传统三矢量模型预测直接功率控制策略，该方法根据功率误差而非电网电压矢量位置选择三个矢量，保证矢量计算时间始终为正。同时，无需迭代计算，有利于在数字信号处理芯片上执行算法。最后，搭建1 kW逆变器实验平台，验证了该方法的有效性。

关键词：并网逆变器；模型预测控制；直接功率控制；三矢量；恒定开关频率；功率误差

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用于灵敏快速测量超阻隔渗透的预测仪器 Article

完颜剑峰, 曹坤, 陈志平, 李云, 刘晨曦, 吴润卿, 张晓东, 陈蓉

《工程（英文）》 2021年第7卷第10期页码 1461-1470 doi: 10.1016/j.eng.2021.02.017

摘要：

测量柔性有机显示器件对水蒸气的高阻隔性，是确保其可靠性所面临的重大工程挑战。一方面，目前缺少10^-6 g·m^-2·d^-1量级的水渗透率测试手段；另一方面，目前也没有标准的超阻隔样品用于渗透率测量的校准。为了对渗透过超阻隔材料的痕量水蒸气流量进行高灵敏、短周期测量，本文将渗透模型集成至基于渗透分子动态积累、检测和抽空的高灵敏质谱测量中，从而开发出了一种具有预测功能的测量仪器。通过使用标准聚合物样品进行校准，确保了测量结果的可靠性。校准后的水蒸气渗透检测下限在10^-7g·m^-2·d^-1量级，满足超阻隔渗透的测量灵敏度要求。本文利用渗透实验数据对所开发的预测渗透模型进行了测试评估，使得利用非稳态数据预测稳态渗透率成为可能，实现在更短的时间内有效开展超阻隔测量。

关键词：水蒸气渗透超阻隔预测模型四极杆质谱仪

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A comprehensive review of wind power based power system frequency regulation

《能源前沿（英文）》 2023年第17卷第5期页码 611-634 doi: 10.1007/s11708-023-0876-6

摘要： Wind power (WP) is considered as one of the main renewable energy sources (RESs) for future low-carbon and high-cost-efficient power system. However, its low inertia characteristic may threaten the system frequency stability of the power system with a high penetration of WP generation. Thus, the capability of WP participating in the system frequency regulation has become a research hotspot. In this paper, the impact of WP on power system frequency stability is initially presented. In addition, various existing control strategies of WP participating in frequency regulation are reviewed from the wind turbine (WT) level to the wind farm (WF) level, and their performances are compared in terms of operating principles and practical applications. The pros and cons of each control strategy are also discussed. Moreover, the WP combing with energy storage system (ESS) for system frequency regulation is explored. Furthermore, the prospects, future challenges, and solutions of WP participating in power system frequency regulation are summarized.

关键词： frequency regulation strategies wind turbine generators grid-forming control model predictive control energy storage system

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The CatMath: an online predictive platform for thermal + electrocatalysis

《化学科学与工程前沿（英文）》 2023年第17卷第12期页码 2156-2160 doi: 10.1007/s11705-023-2371-3

摘要： The catalytic volcano activity models are the quantified and visualized tools of the Sabatier principle for heterogeneous catalysis, which can depict the intrinsic activity optima and trends of a catalytic reaction as a function of the reaction descriptors, i.e., the bonding strengths of key reaction species. These models can be derived by microkinetic modeling and/or free energy changes in combination with the scaling relations among the reaction intermediates. Herein, we introduce the CatMath—an online platform for generating a variety of common and industrially important thermal + electrocatalysis. With the CatMath, users can request the volcano models for available reactions and analyze their materials of interests as potential catalysts. Besides, the CatMath provides the function of the online generation of Surface Pourbaix Diagram for surface state analysis under electrocatalytic conditions, which is an essential step before analyzing the activity of an electrocatalytic surface. All the model generation and analysis processes are realized by cloud computing via a user-friendly interface.

关键词： CatMath catalysis volcano activity plots Surface Pourbaix Diagrams online platform

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标题作者时间类型操作

Extended model predictive control scheme for smooth path following of autonomous vehicles

期刊论文

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

期刊论文

machine-learning-based system identification of dynamical systems under control: application towards the modelpredictive control of a highly nonlinear reactor system

期刊论文

多目标自适应优化模型预测控制——降低氧化锌回转窑的碳排放

Ke Wei, Keke Huang, Chunhua Yang, Weihua Gui

期刊论文

Fuzzy force control of constrained robot manipulators based on impedance model in an unknown environment

LIU Hongyi, WANG Fei, WANG Lei

期刊论文

HVAC系统的模糊预测函数控制器设计

吕红丽,贾磊,王雷,高瑞

期刊论文

时滞系统的辨识及NARMA模型的修正

王冬青