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Automation & Control Systems
Yongliang Yang, Liqiang Tang, Wencheng Zou, Da-Wei Ding
Summary: This article proposes a robust adaptive controller design method for strict feedback nonlinear systems with unmodeled dynamics and input saturation. By using command filters and compensating signals, the drawbacks of conventional methods are overcome. A dynamic signal is designed based on input-to-state stability theory to tackle the effect of unmodeled dynamics, and stability analysis proves the effectiveness of the proposed controller design scheme in simulation experiments.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Xiaowei Yang, Wenxiang Deng, Jianyong Yao
Summary: This article proposes an asymptotic adaptive command filtered control approach for uncertain non-linear systems with parametric uncertainties, mismatched and matched disturbances. The proposed method combines disturbance observer, adaptive control, and command filter technique to achieve asymptotic tracking and avoid complexity explosion.
Article
Automation & Control Systems
Jinlin Sun, Haibo He, Jianqiang Yi, Zhiqiang Pu
Summary: This article presents a new command-filtered composite adaptive neural control scheme for uncertain nonlinear systems. The proposed approach achieves finite-time convergent composite adaptive control for higher-order nonlinear systems with unknown nonlinearities, parameter uncertainties, and external disturbances. The scheme utilizes radial basis function neural networks to approximate the unknown functions of the system and updates the weights of the networks using prediction errors and tracking errors. The proposed control scheme ensures high-precision tracking and NN approximation performances simultaneously and avoids singularity problems in the finite-time backstepping framework.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Jiapeng Liu, Qing-Guo Wang, Jinpeng Yu
Summary: In this study, we develop a modified adaptive control scheme for uncertain nonlinear systems based on command-filtered backstepping. Our main task is to construct the virtual stabilizing functions in the presence of the uncertain control gain functions. The proposed strategy overcomes the problem of input saturation and ensures the convergence of all system signals. Simulation and experimental results validate the effectiveness of our control strategy for numerical nonlinear systems and a PMSM control platform.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Shuchao Hou, Lin Zhao
Summary: This article studies fixed-time output feedback tracking control for nonlinear systems based on the command filtered backstepping method. The neural network approximation technique is used to estimate uncertain dynamics. The fixed-time filter is introduced to overcome complexity explosion and is combined with a compensation signal to reduce filtering error. The results show that the proposed fixed-time control strategy successfully achieves the expected tracking error near the origin within a predetermined convergence time, without requiring knowledge of the system's initial value.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Huaguang Zhang, Yang Liu, Jing Dai, Yingchun Wang
Summary: This article introduces an adaptive fuzzy finite-time control approach for uncertain strict-feedback nonlinear systems with backlashlike hysteresis and stochastic disturbances. The proposed control scheme effectively overcomes complexity and singularity issues, providing good tracking performance for systems with such characteristics. The effectiveness of the strategy is further validated through simulation examples.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Xingxing You, Songyi Dian, Kai Liu, Bin Guo, Guofei Xiang, Yuqi Zhu
Summary: In this article, the issue of adaptive fuzzy finite-time tracking control for uncertain fractional-order nonlinear systems with external disturbance is investigated. A new finite-time fractional-order command filtered implementation scheme is proposed for the adaptive backstepping method. By employing the proposed command filter, adaptive backstepping technique, and fractional Lyapunov's direct method, a novel adaptive fuzzy finite-time controller is designed. A simulation example is provided to demonstrate the effectiveness and availability of the proposed control strategy.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Yan Yan, Xiqin He, Libing Wu, Qingkun Yu
Summary: This article focuses on adaptive event-triggered control (ETC) for a family of switched nonlinear systems with full-state constraints. A first-order command filter is introduced to reduce complexity, and compensating signals are designed to cancel filtering errors. By combining the filtered control and backstepping technology, a new event-triggered controller based on fuzzy logic systems (FLSs) is proposed, which reduces triggering frequency and handles mismatch problems. The control scheme based on barrier Lyapunov functions (BLFs) guarantees no violation of full-state constraints and convergence of tracking error to the origin's neighborhood. The effectiveness of the proposed control scheme is illustrated through two simulation examples.
INFORMATION SCIENCES
(2023)
Article
Automation & Control Systems
Yulin Li, Huanqing Wang, Xudong Zhao, Ning Xu
Summary: This article presents an event-triggered adaptive neural tracking control strategy for uncertain fractional-order nonstrict-feedback nonlinear systems, addressing inherent shortcomings in traditional backstepping control methods and design challenges in fractional-order cases.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Xiaonan Xia, Jianwen Pan, Tianping Zhang, Yu Fang
Summary: In this paper, a command filter based dynamic surface control method is proposed for stochastic nonlinear systems with input delay, stochastic unmodeled dynamics, and full state constraints. The stability and constraint satisfaction of the system are achieved through error compensation and coordinate transformations.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Wei Sun, Shun-Feng Su, Jianwei Xia, Guangming Zhuang
Summary: A novel adaptive fuzzy prescribed performance tracking control method is proposed in this article, effectively addressing the control problem of strict-feedback stochastic uncertain nonlinear systems. The effectiveness of the method is verified through simulation examples.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Zeyu Yang, Jin Huang, Zhanyi Hu, Hui Yin, Zhihua Zhong
Summary: This study introduces an adaptive constraint-following control scheme for an uncertain nonlinear mechanical system, which aims to approximately follow prescribed constraints using adaptive control. Through Lyapunov minimax analysis, it is demonstrated that the resulting control ensures the uniform boundedness and uniform ultimate boundedness of the system, despite uncertainties and measurement errors.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Xinfeng Zhu, Wenwu Ding, Tianping Zhang
Summary: This article proposes an adaptive prescribed performance tracking control method for a class of pure-feedback nonlinear systems with full-state time-varying constraints. By using hyperbolic tangent function and radial basis function neural networks to approximate unknown nonlinear functions, and overcoming the shortcomings of the dynamic surface method with error compensation mechanism, the stability of the system and the output tracking performance are achieved. Based on Lyapunov stability theory, it is shown that all signals in the closed-loop system are semiglobal uniformly ultimately bounded and the output tracking error converges to the prescribed performance bound.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Andrea L'Afflitto
Summary: This paper presents the first model reference adaptive control system for nonlinear, time-varying, hybrid dynamical plants affected by uncertainties, with unknown resetting events. The proposed framework allows for instantaneous variations in the reference model's trajectory to rapidly reduce tracking error, while still following a user-defined signal. The paper also introduces an extension of the classical LaSalle-Yoshizawa theorem to time-varying hybrid dynamical systems. Numerical simulation demonstrates the key features and advantages of the proposed adaptive control system over a classical model reference adaptive control system.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2023)
Article
Automation & Control Systems
Jiling Ding, Weihai Zhang
Summary: This article proposes a new adaptive finite-time tracking control method for nonlinear systems with uncertain parameters, utilizing command filters and compensation signals to solve the trajectory tracking problem. The proposed control method ensures the tracking error remains in a small neighborhood of the origin in finite time.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
K. Merve Dogan, Benjamin C. Gruenwald, Tansel Yucelen, Jonathan A. Muse
INTERNATIONAL JOURNAL OF CONTROL
(2018)
Article
Automation & Control Systems
Ehsan Arabi, Benjamin C. Gruenwald, Tansel Yucelen, Nhan T. Nguyen
INTERNATIONAL JOURNAL OF CONTROL
(2018)
Article
Automation & Control Systems
K. Merve Dogan, Benjamin C. Gruenwald, Tansel Yucelen, Jonathan A. Muse, Eric A. Butcher
INTERNATIONAL JOURNAL OF CONTROL
(2019)
Article
Automation & Control Systems
Benjamin C. Gruenwald, Ehsan Arabi, Tansel Yucelen, Animesh Chakravarthy, Drew McNeely
INTERNATIONAL JOURNAL OF CONTROL
(2020)
Article
Automation & Control Systems
Benjamin C. Gruenwald, Tansel Yucelen, Jonathan A. Muse, Daniel Wagner
Article
Automation & Control Systems
Ehsan Arabi, Tansel Yucelen, Benjamin C. Gruenwald, Mario Fravolini, Sivasubramanya Balakrishnan, Nhan T. Nguyen
SYSTEMS & CONTROL LETTERS
(2019)
Article
Automation & Control Systems
K. Merve Dogan, Benjamin C. Gruenwald, Tansel Yucelen, Jonathan A. Muse
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2019)
Article
Automation & Control Systems
Tansel Yucelen, Benjamin C. Gruenwald, K. Merve Dogan, Animesh Chakravarthy, Alok Menon
Summary: This paper investigates a class of coupled dynamical systems with actuated and unactuated components, proposing a mixed state and output feedback framework for model reference adaptive control. By integrating nominal and adaptive control laws, the stability of the closed-loop coupled dynamical system is ensured, along with user-defined bounds on system error trajectories.
INTERNATIONAL JOURNAL OF CONTROL
(2021)
Article
Automation & Control Systems
Benjamin C. Gruenwald, Tansel Yucelen, Animesh Chakravarthy
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2020)
Proceedings Paper
Automation & Control Systems
Benjamin C. Gruenwald, Tansel Yucelen, Animesh Chakravarthy
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC)
(2018)
Proceedings Paper
Automation & Control Systems
Benjamin C. Gruenwald, Ehsan Arabi, Tansel Yucelen, Animesh Chakravarthy, Drew McNeely
2017 AMERICAN CONTROL CONFERENCE (ACC)
(2017)
Proceedings Paper
Automation & Control Systems
Ali Albattat, Tansel Yucelen, Benjamin C. Gruenwald, S. Jagannathan
PROCEEDINGS OF THE ASME 10TH ANNUAL DYNAMIC SYSTEMS AND CONTROL CONFERENCE, 2017, VOL 1
(2017)
Article
Engineering, Electrical & Electronic
Benjamin C. Gruenwald, Tansel Yucelen, Jonathan A. Muse
Article
Engineering, Aerospace
Benjamin C. Gruenwald, Tansel Yucelen, K. Merve Dogan, Jonathan A. Muse
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2020)