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A Novel Adaptive Sliding Mode Control of Microbial Fuel Cell in the Presence of Uncertainty
Xiuwei Fu,Li Fu,Hashem Imani Marrani 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.6
Model-based control strategies for microbial fuel cell are able to create a balance between fuel supply, mass, charge and electric charge, performance effi ciency. This paper designs a new adaptive sliding mode control scheme of single chamber single population microbial fuel cell. The adaptive method estimates parametric uncertainty and nonlinear terms while the sliding mode method achieves microbial fuel cell performance targets. The signifi cant advantage of the suggested scheme is its capability to provide robustness against parametric uncertainties and handle systems nonlinearity. The Lyapunov technique has been used to demonstrate robust stability in the face of nonlinearity and uncertainty. Numerical simulations confi rms that the proposed control method is able to meet the desired specifi cation in the presence of varieties of parametric uncertainty.
Fu Li,Fu Xiuwei,Imani Marrani Hashem 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.1
Microbial fuel cells are one of the most important elements in the renewable energy supply chain. To increase the effi ciency and performance of the fuel cell, designing a suitable control method is essential to achieve reliable performance and output stability. By considering the parametric uncertainties on the microbial fuel cell model as well as nonlinear terms, this paper presents a novel fi nite time adaptive sliding mode control method that achieves optimal performance of fuel cell in a fi nite time and also ensures the stability of the closed loop system. Sliding mode method without linearization or elimination of nonlinear terms has been used as a robust method to overcome uncertainty eff ects and guarantees proper operation of the fuel cell in the presence of the eff ects. The fi nite time convergence of the states is also assured by using of the proposed method. Furthermore, it uses an adaptive method to determine the sliding mode control coeffi cients which eliminates the necessity to know the upper bound of uncertainty. Finally, the simulation results show the effi ciency and stability of the proposed method in diff erent operating conditions.
Guanglei Zhao,Zhao Wang,Xiuwei Fu 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.4
This paper investigates the event-triggered consensus problem of multi-agent systems with uncertainties and input saturation. First, a fully distributed robust consensus low-gain feedback control strategy is proposed, in which some global information, such as the communication graph and the scale of network, is not needed. Then, by defining an internal dynamic variable to memory the past state, an adaptive dynamic event-triggering mechanism is proposed, which contributes to reducing the usage of communication resources and also does not rely on any global information. Furthermore, Lyapunov-based consensus analysis results are presented, and it is also formally shown that Zeno behavior can be excluded with the proposed consensus protocols. Finally, a numerical example is provided to illustrate the effectiveness of the proposed results.
Gu Yan,Sun Jianhua,Fu Xiuwei 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.2
Given the importance of synchronization in chaotic systems, this paper presents a new approach to achieve this goal. Simultaneous consideration of time-varying delays, disturbances, uncertainties, and nonlinear terms in a fractional order chaotic system poses a fundamental challenge for achieving the synchronization goal and this paper presents a novel complex approach resulting from neural network and sliding mode approaches to overcome it. The Chebyshev neural network has been used to estimate the delayed nonlinear functions as well as the uncertain parts of the fractional order chaotic system, and the robust sliding mode technique has been considered to ensure stability against the effects of multiple inconveniences. Finally, simulation and comparison in MATLAB environment confirms the efficiency and ability of the proposed scheme in achieving the goal of robust synchronization despite the uncertainty, variable time delay, disturbance and nonlinear terms.