Article
Thermodynamics
Tabbi Wilberforce, Hegazy Rezk, A. G. Olabi, Emmanuel I. Epelle, Mohammad Ali Abdelkareem
Summary: One of the primary challenges in fuel cell modeling is determining specific boundary conditions, which are often not fully provided by the manufacturer. This study proposed using five different algorithms to determine seven unknown parameters that affect the mathematical modeling of the cell. The artificial ecosystem-based algorithm showed the best results compared to other algorithms, indicating its effectiveness in improving accuracy and predicting performance.
Article
Automation & Control Systems
Andreu Cecilia, Daniele Astolfi, Ramon Costa-Castello
Summary: Fuel cells require real-time monitoring of internal variables, such as liquid water saturation. However, the nonlinearity and sensor noise pose challenges for typical observers like the extended Kalman filter (EKF). To overcome these limitations, this study proposes a novel nonlinear observer that can accurately estimate liquid water saturation in fuel cells.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Lingwei Wu, Youfang Yu, Zhiming Lin, Qiuzhen Yan, Xiangbin Liu
Summary: This paper presents an adaptive iterative learning control scheme for tracking a class of nonlinearly parametric time-delay systems, utilizing a time-varying boundary layer and various compensation techniques to improve the performance of iterative learning control algorithms.
Article
Engineering, Civil
Kun Liu, Guanhua Huang, Jiri Simunek, Xu Xu, Yunwu Xiong, Quanzhong Huang
Summary: The study compared four assimilation schemes for estimating time-varying soil hydraulic parameters, finding that the partitioned update parameter correction method has higher computational efficiency and assimilation stability. It improves the accuracy of parameter estimations and pressure head simulations in comparison with traditional methods.
JOURNAL OF HYDROLOGY
(2021)
Article
Automation & Control Systems
Jing Na, Yashan Xing, Ramon Costa-Castello
Summary: The paper presents an alternative adaptive parameter estimation framework for nonlinear systems with time-varying parameters, which can directly estimate the unknown parameters and achieve faster convergence rate through new adaptive laws and exponential error convergence; Comparative simulation results show that the proposed approaches can achieve better estimation performance than several other algorithms, and the robustness against bounded disturbances is also studied.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
Jin Young Park, In Seop Lim, Eun Jung Choi, Yeong Ho Lee, Min Soo Kim
Summary: As fuel cell technology enters the commercialization stage, issues regarding activation time and fuel consumption become prominent with the increase in fuel cell capacity. A new method of reverse-flow activation has been proposed to reduce activation time and fuel consumption in polymer electrolyte membrane fuel cells, demonstrating significant improvement in experimental results compared to conventional methods.
Article
Economics
Jiti Gao, Bin Peng, Yayi Yan
Summary: In this article, a new class of time-varying VAR models is introduced, allowing the coefficients and covariance matrix of error innovations to change smoothly over time to better capture dynamics. The article establishes a set of asymptotic properties including impulse response analyses, information criterion for lag selection, and a Wald-type test for determining constant coefficients. Simulation studies are conducted to evaluate the theoretical findings, and empirical relevance and usefulness of the proposed methods are demonstrated through an application on U.S. government spending multipliers.
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
(2023)
Article
Computer Science, Information Systems
Yihui Lei, Jiamei Luo, Tengxiao Chen, Lei Ding, Bolin Liao, Guangping Xia, Zhengqi Dai
Summary: This paper proposes a nonlinear activated integration-enhanced neural network model based on a coalescent activation function. The model accelerates convergence speed without significant efficiency loss and solves the time-varying Sylvester equation in various noise situations.
Article
Engineering, Electrical & Electronic
Yashan Xing, Jing Na, Mingrui Chen, Ramon Costa-Castello, Vicente Roda
Summary: This article proposes an alternative framework for real-time parameter estimation in fuel cell systems, using an unknown system dynamics estimator and an adaptive law to estimate and converge parameters. Experimental results validate the effectiveness of the proposed schemes.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Chemistry, Physical
S. Vengatesan, R. Venkadesh, A. V. R. Shivaram, M. Wasim Khan
Summary: The mechanical aspect of understanding the dynamic behaviour is crucial in the stack assembly of fuel cell configuration to avoid catastrophic failure. Dynamic analysis of a PEMFC is performed to understand its response during complex loading nature. The thickness of the bipolar plate is observed to play a vital role in the vibration behavior of the PEMFC.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Automation & Control Systems
Ning Xu, Feng Ding
Summary: This article focuses on the identification of time-varying systems. Unlike conventional polynomial approximation approaches, the changing laws of the time-varying parameters are taken into account to establish the identification model. The concept of the invariant matrix is introduced to characterize the time-varying parameters and establish the state-space model. Two state estimation algorithms, stacked and detached, are proposed to estimate the time-varying parameters and enhance computational efficiency. Numerical simulation examples are provided to demonstrate the effectiveness of the proposed algorithms.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Joseph E. Gaudio, Anuradha M. Annaswamy, Eugene Lavretsky, Michael A. Bolender
Summary: This article presents a new parameter estimation algorithm for the adaptive control of time-varying plants. The algorithm utilizes a matrix of time-varying learning rates to ensure fast convergence of parameter estimation error trajectories. It is applicable to problems with unknown time-varying parameters, and guarantees global boundedness of system state and parameter errors.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Engineering, Electrical & Electronic
Man Shi, Hongwen He, Jianwei Li, Mo Han, Nana Zhou
Summary: Path planning and tracking are crucial for autonomous vehicles, but they face challenges. This research proposes an optimized design and control method using multidimensional information to improve performance and robustness.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Energy & Fuels
Pedro Fornaro, Thomas Puleston, Paul Puleston, Maria Serra-Prat, Ramon Costa-Castello, Pedro Battaiotto
Summary: This article presents a new insight into parameter estimation of vanadium redox flow batteries (VRFB) and proposes an estimation method suitable for hybrid fast-charging stations. The method utilizes a recursive least square estimation algorithm with forgetting factor, combined with a sliding mode finite-time convergent differentiation algorithm to accurately estimate the battery's state and internal parameters.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Automation & Control Systems
Gabriele Perozzi, Denis Efimov, Jean-Marc Biannic, Laurent Planckaert
Summary: The objective of this paper is to develop an algorithm for estimating time-varying wind parameters using a detailed quadrotor model. The algorithm aims to achieve time convergence optimization, robustness to measurement noises, and guaranteed convergence to true values under mild applicability conditions.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Yashan Xing, Lucile Bernadet, Marc Torrell, Albert Tarancon, Ramon Costa-Castello, Jing Na
Summary: This paper proposes an offline tuning strategy and an online parameter estimation method for calibrating the solid oxide fuel cell mathematical model. The offline tuning strategy is designed to tune the model under various operation conditions using particle swarm optimization and gradient-based search methods. The online parameter estimation method employs an adaptive optimal learning law to minimize a cost function with estimation error information. Experimental verification is conducted on a practical solid oxide fuel cell test bench.
Article
Engineering, Electrical & Electronic
Bin Wang, Ramon Costa-Castello, Jing Na, Oscar de la Torre, Xavier Escaler
Summary: This paper proposes a new adaptive estimation approach for online parameter estimation of a piezoelectric cantilever beam. By introducing the Galerkin method and separating the time and space variables of the PDE, the unknown parameters of the derived ODE model can be estimated in real time.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Engineering, Electrical & Electronic
Yingbo Huang, Huidong Hou, Jing Na, Haoran He, Jing Zhao, Zhenghao Shi
Summary: This paper presents a novel control method for half-vehicle active suspension systems driven by hydraulic actuators. It introduces a coordinate transform approach to reformulate the strict-feedback system into a canonical form without using the backstepping method. A modified high-gain observer (HGO) is studied to rebuild the unknown system states of the nonlinear active suspension system. To eliminate the effect of unknown nonlinearities, a simple robust unknown system dynamics estimator (USDE) is developed. Finally, the observer and estimator are integrated to design an output feedback controller to regulate the vehicle motion. Comparative experiments demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Jorge L. Anderson, Jeronimo J. More, Paul F. Puleston, Ramon Costa-Castello
Summary: Fuel cells (FCs) are a promising technology with high efficiency, reliability, and clean energy for various applications. However, the discontinuous control action of sliding mode control leads to undesired effects in real nonideal systems. In this paper, a switched/time-based adaptive super-twisting algorithm (STA) is proposed for FC module control, which exhibits low chattering and similar robustness compared to traditional STA.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Mauro Carignano, Ramon Costa-Castello
Summary: This work proposes a rule-based strategy to simulate the energy management strategy of Toyota Mirai and validates the model and strategy with experimental data. Compared to optimal strategies, Toyota Mirai's strategy has certain advantages in fuel economy, but there is greater room for improvement in terms of fuel cell and battery demand.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Electrochemistry
Alejandro Clemente, Manuel Montiel, Felix Barreras, Antonio Lozano, Ramon Costa-Castello
Summary: This study presents a vanadium redox flow battery model that considers the most important variables in the system. The model is divided into electrochemical, thermal, hydraulic, and voltage submodels. Analytic analysis is used to reduce the system order, and a calibration of the model parameters is conducted using real experimental data. The model is validated by comparing real measured voltage with estimated voltage. Results from short and long-term operation are presented for state of charge and state of health estimation validation.
ELECTROCHIMICA ACTA
(2023)
Article
Chemistry, Physical
P. Cardona, R. Costa-Castello, V. Roda, J. Carroquino, L. Valino, M. Serra
Summary: The growth of hydrogen fuel cell vehicles has generated a significant amount of research on hydrogen refuelling stations, particularly on-site green stations that produce hydrogen from renewable energy sources. This paper develops a linear model and uses a Model Predictive Controller to optimize the operation of a green hydrogen refuelling station in Zaragoza, Spain. The simulation results demonstrate the economic advantage of using the Model Predictive Controller compared to rule-based control solutions.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Energy & Fuels
Alejandro Clemente, Andreu Cecilia, Ramon Costa-Castello
Summary: This study proposes an observer-based methodology for real-time estimation of the state of charge of a Vanadium redox flow battery. Unlike previous research, this work introduces a new estimator that distinguishes between the concentration in the tank and cell parts of the system. It also provides an estimation of the state of charge that can handle both balanced and unbalanced situations. The proposed nonlinear observer is validated through simulation and experimentation.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Automation & Control Systems
Xingling Shao, Fei Zhang, Wendong Zhang, Jing Na
Summary: This article investigates a finite-time composite learning-based elliptical enclosing control for nonholonomic robots under a GPS-denied environment. A novel bearing measurement-based relative position observer is proposed to assure estimation errors decay without GPS. An elliptical guidance law is established to yield the reference velocity and angular rate using observation outcomes. A finite-time composite neural learning driven by weight and tracking errors is devised to achieve precise disturbance compensation and error convergence.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Energy & Fuels
Thomas Puleston, Andreu Cecilia, Ramon Costa-Castello, Maria Serra
Summary: This paper presents a novel observer architecture for estimating the concentrations of the four vanadium species in a vanadium redox flow battery. The proposed architecture consists of a high-gain observer, a dynamic inverter, and a static selector. The method does not rely on the assumption of balanced electrolytes and only requires a single voltage and current measurement. Comprehensive simulation tests show that the observer performs remarkably well, estimating the concentrations, State of Charge, and State of Health with a relative error below 2%.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Automation & Control Systems
Xiaomei Wang, Jing Na, Ben Niu, Xudong Zhao, Tingting Cheng, Wenqi Zhou
Summary: This paper proposes an adaptive bipartite secure consensus asymptotic tracking control scheme based on event-triggered strategy for the nonlinear multi-agent systems (MASs) under denial-of-service (DoS) attacks. The paper successfully addresses the bipartite consensus control problem with unbalanced communication topology by incorporating the concept of shortest path into the hierarchical algorithm. An anti-attack bipartite control strategy is proposed using improved forms of tracking errors and virtual controllers, and a modified event-triggered mechanism based on relative threshold strategy ensures asymptotic convergence of bipartite consensus tracking errors.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Jintao Zhang, Xingling Shao, Wendong Zhang, Jing Na
Summary: This article proposes a path-following control method that enhances transient performances for networked mobile robots traveling over a single curve. By using a coordinated error based on projective arc length, a path-following controller is designed for multiple robots, achieving a queue formation pattern with equal arc spacing at a uniform velocity. Additionally, a tracking differentiator-based prescribed performance control scheme is proposed to enforce tracking deviations of geometric and dynamic objectives before a specified time. The developed scheme allows for cooperative behavior over a general curve and arbitrary designation of desired settling time for each robot, while ensuring convergence of all error variables.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Automation & Control Systems
Jorge Luis Anderson, Jeronimo Jose More, Paul Federico Puleston, Vicente Roda, Ramon Costa-Castello
REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL
(2023)
Article
Automation & Control Systems
Chao Zhang, Xuemei Ren, Jing Na, Dongdong Zheng
Summary: This article proposes a safe dual-layer nested adaptive prescribed performance control approach for nonlinear systems, which ensures predefined transient and steady-state performances for the discontinuous reference signal. A monitoring mechanism and a novel dual-layer nested adaptive sliding mode compensation technique are introduced to handle system uncertainties effectively.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Zhijiang Gao, Pak Kin Wong, Jing Zhao, Zhixin Yang, Yingbo Huang, Jing Na
Summary: This article addresses the optimal control problem for magnetorheological fluid-based semiactive suspension systems with input saturation and time-varying delay. A robust switched H∞ method based on the Takagi-Sugeno fuzzy theory is proposed to handle this problem. A novel hybrid model incorporating the fluid flow mechanism and hysteresis phenomenon model is used to separate the passive and active components of the MRF damper. Linear matrix inequality conditions are derived to capture the features of input saturation and time-varying delay, and a Lyapunov-Krasovskii function is employed to ensure stability. Numerical examples demonstrate the effectiveness of the proposed method in dealing with the MRF-SAS system with input saturation and time-varying delay.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)