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China Petroleum Processing & Petrochemical Technology 2024年第3期26卷 122-135页

作者： Chu Kaihui qi zhidong qin Hao Shan Liang School of Automation Nanjing University of Science and TechnologyNanjing 210094China

Considering the multivariable and fractional-order characteristics of proton exchange membrane fuel cells(PEMFCs),a fractional-order subspace identification method(FOSIM)is proposed in this paper to establish a fractionalorder state space(FOSS)model,which can be expressed as a multivariable configuration with two inputs,hydrogenflow rate and stack current,and two outputs,cell voltage and *** on this model,a novel constrained optimal control law named the Hildreth model predictive control(H-MPC)strategy is created,which employs a Hildreth quadratic programming algorithm to adjust the output power of fuel cells through adaptively regulating hydrogen flow and stack *** semi-physical simulation results demonstrate that,compared with proportional-integral-derivative and quadratic programming MPC(QP-MPC),the proposed H-MPC exhibits better tracking ability and strong robustness against variations of PEMFC power.

关键词： PEMFC fractional-order subspace identification method fractional-order state space H-MPC

基于IECSDE算法的PEMFC改进分数阶子空间辨识模型

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计算机工程 2024年第6期50卷 346-357页

作者：秦灏戚志东于灵芝童新南京理工大学自动化学院江苏南京210094

为准确描述质子交换膜燃料电池(PEMFC)在其发电过程中的特性及变量影响关系,提出一种基于信息交流布谷鸟搜索差分进化(IECSDE)算法的改进分数阶子空间辨识方法来建立PEMFC分数阶模型。首先基于状态空间方程建立PEMFC模型,为了描述PEMFC... 详细信息

为准确描述质子交换膜燃料电池(PEMFC)在其发电过程中的特性及变量影响关系,提出一种基于信息交流布谷鸟搜索差分进化(IECSDE)算法的改进分数阶子空间辨识方法来建立PEMFC分数阶模型。首先基于状态空间方程建立PEMFC模型,为了描述PEMFC的分数阶特性,将分数阶微分理论融入到模型中,引入Poisson滤波函数预处理实验数据,解决数据多阶不可导的问题,同时引入变步长记忆法处理分数阶微分时的权系数,提高子空间辨识精度。其次在辨识过程中的参数对于建模效果具有重大影响,因此基于IECSDE算法并对其进行优化,对布谷鸟搜索(CS)算法中的控制参数进行自适应处理,受到粒子群优化(PSO)算法的启发,改进随机游走方式提高收敛精度和速度,并引入差分进化(DE)算法与改进CS算法分别对种群进行优化,同时在寻优过程中进行信息交流提高种群的多样性和算法的鲁棒性。仿真结果表明,IECSDE算法的寻优能力在8种测试函数下比其他5种优化算法至少提升了10倍;通过对PEMFC测控平台收集到的实验数据进行模型辨识,所建立的模型将误差缩小到基于短记忆法的分数阶子空间辨识方法误差的20%,输出功率误差控制在0~0.1之间,输出电压误差控制在0~0.2之间,能够精准地模拟PEMFC发电过程。

关键词：质子交换膜燃料电池分数阶子空间辨识变步长记忆法优化算法信息交流

PEMFC Identification Based on a Fractional-Order Hammerstein State-Space Model with ADE-BH Optimization

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China Petroleum Processing & Petrochemical Technology 2023年第2期25卷 155-164页

作者： qin Hao qi zhidong Ye Weiqin Sun Chengshuo Nanjing University of Science and Technology Nanjing 210094China

Considering the fractional-order and nonlinear characteristics of proton exchange membrane fuel cells(PEMFC),a fractional-order subspace identification method based on the ADE-BH optimization algorithm is proposed to establish a fractional-order Hammerstein state-space model of ***,a Hammerstein model is constructed by connecting a linear module and a nonlinear module in series to precisely depict the nonlinear property of the *** the modeling process,fractional-order theory is combined with subspace identification,and a Poisson filter is adopted to enable multi-order derivability of the data.A variable memory method is introduced to reduce computation time without losing ***,to improve the optimization accuracy and avoid obtaining locally optimum solutions,a novel ADEBH algorithm is employed to optimize the unknown parameters in the identification *** this algorithm,the Euclidean distance serves as the theoretical basis for updating the target vector in the absorption-generation operation of the black hole(BH)***,simulations demonstrate that the proposed model has small output error and high accuracy,indicating that the model can accurately describe the electrical characteristics of the PEMFC process.

关键词： PEMFC Hammerstein model Fractional subspace identification ADE-BH optimization

Improved quantum bacterial foraging algorithm for tuning parameters of fractional-order PID controller

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Journal of Systems Engineering and Electronics 2018年第1期29卷 166-175页

作者： LIU Lu SHAN Liang DAI Yuewei LIU Chenglin qi zhidong School of Automation Nanjing University of Science and Technology Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of AutomationJiangnan University

The quantum bacterial foraging optimization(QBFO)algorithm has the characteristics of strong robustness and global searching ability. In the classical QBFO algorithm, the rotation angle updated by the rotation gate is discrete and constant,which cannot affect the situation of the solution space and limit the diversity of bacterial population. In this paper, an improved QBFO(IQBFO) algorithm is proposed, which can adaptively make the quantum rotation angle continuously updated and enhance the global search ability. In the initialization process, the modified probability of the optimal rotation angle is introduced to avoid the existence of invariant solutions. The modified operator of probability amplitude is adopted to further increase the population *** tests based on benchmark functions verify the effectiveness of the proposed algorithm. Moreover, compared with the integerorder PID controller, the fractional-order proportion integration differentiation(PID) controller increases the complexity of the system with better flexibility and robustness. Thus the fractional-order PID controller is applied to the servo system. The tuning results of PID parameters of the fractional-order servo system show that the proposed algorithm has a good performance in tuning the PID parameters of the fractional-order servo system.

关键词： bacterial foraging algorithm fractional-order quantum rotation gate proportion integration differentiation(PID) servo system

PEMFC Fractional-order Subspace Identification Model

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China Petroleum Processing & Petrochemical Technology 2022年第3期24卷 151-160页

作者： Sun Chengshuo qi zhidong qin Hao Shan Liang School of Automation Nanjing University of Science and TechnologyNanjing210094

A proton exchange membrane fuel cell(PEMFC)is a new type of hydrogen fuel cell that plays an indispensable role in an energy ***,the multivariable and fractional-order characteristics of PEMFC make it difficult to establish a practical ***,a fractional-order subspace identification model based on the adaptive monarch butterfly optimization algorithm with opposition-based learning(ALMBO)algorithm is proposed for *** the fractional-order theory into the subspace identification method by adopting a Poisson filter for with input and output data,a weight matrix is proposed to improve the identification ***,the ALMBO algorithm is employed to optimize the parameters of the Poisson filter and fractional order,which introduces an opposition-based learning strategy into the migration operator and incorporates adaptive weights to improve the optimization accuracy and prevent falling into a locally optimal ***,the PEMFC fractional-order subspace identification model is established,which can accurately describe the dynamic process of PEMFC.

关键词： PEMFC fractional subspace identification weight matrix ALMBO

基于分数阶PID控制的质子交换膜燃料电池前级功率变换器

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电工技术学报 2019年第A1期34卷 235-243页

作者：戚志东裴进胡迪南京理工大学自动化学院

针对质子交换膜燃料电池(PEMFC)输出为大电流、宽电压而难以实际应用的问题,首先提出一种以四开关Buck-Boost变换器为主拓扑的PEMFC预稳压模块,采用双沿开关管触发策略减小电感电流脉动,并基于高频开关网络等效原理建立准确的动态模型;... 详细信息

针对质子交换膜燃料电池(PEMFC)输出为大电流、宽电压而难以实际应用的问题,首先提出一种以四开关Buck-Boost变换器为主拓扑的PEMFC预稳压模块,采用双沿开关管触发策略减小电感电流脉动,并基于高频开关网络等效原理建立准确的动态模型;然后设计一种分数阶PID控制器实现模块的稳压补偿,并采用一种随机惯性权重PSO算法整定控制器的参数。仿真与实验结果表明,与整数阶控制器相比,分数阶PID控制器具有更好的补偿效果,在系统参数或结构变化时表现出较强的鲁棒性,所提出的模块具有高效可靠的预稳压功能。

关键词：质子交换膜燃料电池四开关Buck-Boost变换器分数阶PID控制器预稳压

Research on Modeling of PEMFC Based on Fractional Order Subspace Identification

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Research on Modeling of PEMFC Based on Fractional Order Subs...

Research on PEMFC Fractional Impedance Characteristic Modeling

第37届中国控制会议

作者： Weiping Ge zhidong qi Changsen Xue Minqiang Xu School of Automation Nanjing University of Science and Technology

In this paper, a subspace identification method based on fractional calculus has been proposed for Proton Exchange Membrane Fuel Cell（PEMFC） system, which can solve the problem that the integer order models cannot describe the fractional order characteristics involved in the working process of PEMFC. Specifically, on the basis of integer order subspace method, the Poisson moment functional is introduced to filter the experimental data, which guarantees that the input and output signals can be differential at different fractional order. Moreover, the short memory principle is adopted to reduce the amount of computation. The problem of identifying the system fractional order is transformed into a parameter optimization problem according to the cost function. In the end, the simulation results are presented to show the effectiveness of the modeling approach.

关键词： PEMFC fractional order subspace identification short memory principle

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Research on PEMFC Fractional Impedance Characteristic Modeli...

Variable Sampling Domain and Map Compression Based on Greedy RRT Algorithm for Robot Path Planning

第30届中国控制与决策会议

作者： Changsen Xue zhidong qi Minqiang Xu Weiping Ge Nanjing University of Science ＆ Technology

The establishment of accurate mathematical model of Proton Exchange Membrane Fuel Cell（PEMFC） is an effective method to reduce the research cost and improve the efficiency. According to fractional parts in PEMFC, a new model of PEMFC fractional impedance characteristic that has a significant influence in the output voltage of PEMFC is proposed in this paper. And aiming at the problem that Particle Swarm Optimization（PSO） algorithm falls easily into the local optimum, a random factor based on fitness variance is added to dynamically adjust the inertia weight which can improve the global exploration ability of the algorithm. The improved PSO algorithm is adapted to identify the parameters of the proposed model by dynamic response of PEMFC in medium current density section. The simulation results show that the proposed fractional model can not only fit the steady state polarization curve well in all current density segments, but also show the dynamic response of PEMFC output voltage.

关键词： PEMFC Impedance characteristic Fractional model Parameters optimization

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Variable Sampling Domain and Map Compression Based on Greedy...

Parameter identification of the fractional-order systems based on a modified PSO algorithm

第三十九届中国控制会议

作者： Zhiqiang Wang Liang Shan Lu Chang Bo qiu zhidong qi School of Automation Nanjing University of Science and Technology

The traditional rapidly-exploring random tree（RRT） algorithm and the improved algorithms use a fixed sampling domain in each iteration. This way of sampling will result in much repeated exploration. Also, a fixed step causes the inefficiency of expansion in open areas and the incremental algorithm consumes much time in collision detection. In order to solve these problems, this paper proposes an improved RRT algorithm based on a variable sampling domain and a map compression algorithm along with a strategy of greedy growing（VSDGC-RRT）. A variable sampling domain and the greedy strategy increase the utilization of the sample node and reduce the number of iterations. The map compression algorithm reduces time consumption in collision detection. These improvements can make the tree expand more rapidly to the target. The simulation results indicate that the improved algorithm can effectively reduce the quantity of iterations and take less time while retaining the probabilistic integrity of the traditional RRT.

关键词： RRT Path Planning Variable Sampling Domain Greedy Growing Map Compression

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Journal of Southeast University(English Edition) 2018年第1期34卷 6-14页

作者： Liu Lu Shan Liang Jiang Chao Dai Yuewei Liu Chenglin qi zhidong School of Automation Nanjing University of Science and TechnologyNanjing 210094China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan UniversityWuxi 214122China

In order to better identify the parameters of the fractional-order system,a modified particle swarm optimization(MPSO)algorithm based on an improved Tent mapping is *** MPSO algorithm is validated with eight classical test functions,and compared with the POS algorithm with adaptive time varying accelerators(ACPSO),the genetic algorithm(GA),a d the improved PSO algorithm with passive congregation(IPSO).Based on the systems with known model structures a d unknown model structures,the proposed algorithm is adopted to identify two typical fractional-order *** results of parameter identification show that the application of average value of position information is beneficial to making f 11 use of the information exchange among individuals and speeds up the global searching *** introducing the uniformity and ergodicity of Tent mapping,the MPSO avoids the extreme v^ue of position information,so as not to fall into the local optimal *** brief the MPSOalgorithm is an effective a d useful method with a fast convergence rate and high accuracy.

关键词： particle swarm optimization Tent mapping parameter identification fractional-order systems passive congregation