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6th IEEE International Conference Methods and Systems of Navigation and Motion Control (MSNMC)

作者： Kucherov, D. Kozub, A. Natl Aviat Univ Dept Computerized Control Syst Kiev Ukraine Natl Univ Def Ukraine Usage Space Syst & GIS Software Dept Kiev Ukraine

ISBN: (纸本)9781728181356

In this paper, we consider the synthesis of a flight control system of an unmanned aerial vehicle like a quadrotor based on a backstepping procedure. The control object has a mathematical model in the form of the system of second-order differential equations, and it has essential nonlinear dynamics. The paper investigates a way of design the algorithm state feedback control based that stabilizing the final state. Some simulation results are presented, as well.

关键词： unmanned aerial vehicle controller setting Quadrotor backstepping algorithm

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An Extended State Observer Based Adaptive backstepping Controller for Microgrid

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IEEE TRANSACTIONS ON SMART GRID 2024年第1期15卷 171-178页

作者： Panda, Swagat Kumar Subudhi, Bidyadhar Indian Inst Technol Goa Sch Elect Sci Ponda 403401 India

This paper proposes development of a robust distributed secondary control scheme for a photovoltaic (PV) source integrated and inverter-interfaced islanded AC microgrid (MG). The control objective is to regulate the voltage, frequency, and achieve the desired active and reactive power sharing among the distributed generations (DGs) while supporting plug and play operation (PnP) and handling abnormal situations. The above objectives are to be achieved in face of uncertainties in inverter switching pulses, intermittent nature of PV source, dynamic load changes, and disturbances. A backstepping (BS) controller is designed to track the nominal voltage and frequency, whilst an extended state observer (ESO) is designed to estimate the disturbance. The stability of the MG with ESO-BS controller is proved by using Lyapunov stability theory, and graph theory. To verify the effectiveness of the proposed controller, both numerical simulation in MATLAB, and experimentation on OPAL-RT at different operating conditions are pursued. The proposed controller is compared with the distributed averaging based secondary control (Simpson-Porco et al., 2015), secondary controller based on MG centralized controller (MGCC) (Shafiee et al., 2014). It is observed that the proposed controller outperforms in terms of enhanced robustness and steady-state performance.

关键词： Voltage control Uncertainty backstepping Frequency control Power system stability Microgrids Switches Microgrid secondary control backstepping algorithm uncertainties extended state observer

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Modified Simple Adaptive-Robust backstepping algorithm 19

Modified Simple Adaptive-Robust Backstepping Algorithm

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19th International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Furtat, Igor B. Tupichin, Evgeny A. ITMO Univ Inst Problems Mech Engn Russian Acad Sci St Petersburg Russia Lukoil Overseas Secondment BV Aktau Region Mangista Kazakhstan

ISBN: (纸本)9781479950812

The simple adaptive-robust control algorithm for time-invariant uncertain linear plants is proposed. Only scalar input and output of the plant are available for measurement. algorithm provides tracking of a plant output to a reference signal with required accuracy. Simulations results illustrating an efficiency of proposed scheme are presented.

关键词： adaptive-robust control backstepping algorithm disturbance compensation

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Fixed-time Adaptive Event-triggered Control for a Class of Uncertain Nonlinear Systems with Input Hysteresis

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2023年第8期21卷 2541-2553页

作者： Wang, Jianhui Wang, Chen Wu, Yushen Li, Yonghua Du, Yongping Chen, Kairui Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China Qiannan Normal Univ Nationalities Sch Comp & Informat Duyun 558000 Guizhou Peoples R China

The problem of fixed-time adaptive event-triggered control for uncertain nonlinear systems with input hysteresis is investigated. An adaptive dynamic threshold event-triggered control scheme is proposed to schedule the update of control signals and realize the online compensation of input hysteresis. Furthermore, a fixed-time adaptive event-triggered controller is proposed based on the fixed-time stability theorem. The controller can ensure that the tracking error converges into a small and adjustable set in a fixed time, and the convergence time is independent of the initial system states. Meanwhile, all the closed-loop signals are bounded, and the Zeno behavior is excluded. Finally, the feasibility of the method is verified by some simulation examples.

关键词： Adaptive control backstepping algorithm event-triggered control fixed-time control input hysteresis

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Observer-based adaptive fuzzy output feedback control for functional constraint systems with dead-zone input

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2023年第2期20卷 2628-2650页

作者： Yu, Tianqi Liu, Lei Liu, Yan-Jun Liaoning Univ Technol Coll Sci Jinzhou 121001 Peoples R China

This paper develops an adaptive output feedback control for a class of functional constraint systems with unmeasurable states and unknown dead zone input. The constraint is a series of functions closely linked to state variables and time, which is not achieved in current research results and is more general in practical systems. Furthermore, a fuzzy approximator based adaptive backstepping algorithm is designed and an adaptive state observer with time-varying functional constraints (TFC) is constructed to estimate the unmeasurable states of the control system. Relying on the relevant knowledge of dead zone slopes, the issue of non-smooth dead-zone input is successfully solved. The time-varying integral barrier Lyapunov functions (iBLFs) are employed to guarantee that the states of the system remain within the constraint interval. By Lyapunov stability theory, the adopted control approach can ensure the stability of the system. Finally, the feasibility of the considered method is conformed via a simulation experiment.

关键词： fuzzy state observer time-varying functional constraints (TFC) dead-zone input adaptive fuzzy control backstepping algorithm

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Terminal super-twisting sliding mode based on high order sliding mode observer for two DOFs lower limb system

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MEASUREMENT & CONTROL 2023年第7-8期56卷 1455-1470页

作者： Tran, Tri Duc Duong, Van Tu Nguyen, Huy Hung Nguyen, Tan Tien Vietnam Natl Univ Ho Chi Minh City Ho Chi Minh City Vietnam Ho Chi Minh City Univ Technol HCMUT Fac Mech Engn Ho Chi Minh City Vietnam Ho Chi Minh City Univ Technol HCMUT Natl Key Lab Digital Control & Syst Engn DCSELab 268 Ly Thuong Kiet StDist 10 Ho Chi Minh City Vietnam Saigon Univ Fac Elect & Telecommun Ho Chi Minh City Vietnam

In this paper, a novel backstepping terminal super-twisting sliding mode (TSTSM) with high order sliding mode observer (HOSMO) is proposed to control the two degrees of freedom (DOFs) Serial Elastic Actuator (SEA), inspired by a lower limb of humanoid robots. First, the dynamic model, extended from our previous study, is presented for developing the control algorithm. Secondly, the backstepping technique is utilized to separate the overall system into two subsystems. One of the challenges of SEA is to deal with the evident oscillations caused by the elastic element, which might lead to the degrading performance of load position control. In order to reduce this adverse effect, a TSTSM is proposed to control the position tracking of two subsystems. The advantages of TSTSM are the finite-time convergence despite the bounded perturbation and the dramatic reduction of the chattering phenomenon. To construct and implement the TSTSM controller, it requires the knowledge of all states, which is not available in the current lower limb system setup. Therefore, a HOSMO is utilized to estimate the unknown states. Finally, experiment results are carried out to assess the effectiveness of the proposed controller and compare it with those of different control schemes.

关键词： Super twisting algorithm sliding mode SEA humanoid robot super-twisting observer terminal sliding mode backstepping algorithm

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Compound FAT-based prespecified performance learning control of robotic manipulators with actuator dynamics

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ISA TRANSACTIONS 2022年 131卷 246-263页

作者： Keighobadi, Javad Xu, Bin Alfi, Alireza Arabkoohsar, Ahmad Nazmara, Gholamreza Shahrood Univ Technol Fac Elect Engn Shahrood Iran Northwestern Polytech Univ Sch Automation Xian Shaanxi Peoples R China Aalborg Univ Dept Energy Technol Aalborg Denmark

In the framework of the backstepping algorithm, this article proposes a new function approximation technique (FAT)-based compound learning control law for electrically-driven robotic manipulators with output constraint. The Fourier series expansion is adopted in the learning-based design to approximate unknown terms in the system description. The accuracy of FAT approximation is also studied by defining an identification error, which is derived from a serial-parallel identifier. Furthermore, the output constraint is taken into account by integrating the error transformation, the performance function and the dynamic surface control in a compact framework. Following this idea, new compound adaptation laws are then constructed. The proposed compound learning controller confirms that all the signals of the overall system are uniformly ultimately bounded, ensuring the tracking error within the predefined bounds during operation. Different simulation scenarios applied to a robotic manipulator with motor dynamics illustrate the capability of the control algorithm.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Compound learning control FAT-based control Prespecified control Output constraint backstepping algorithm Robotic manipulator

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Adaptive Fuzzy Practical Fixed-Time Tracking Control of Nonlinear Systems

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2021年第3期29卷 664-673页

作者： Chen, Ming Wang, Huanqing Liu, Xiaoping Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 14051 Peoples R China Bohai Univ Dept Math Jinzhou 121013 Peoples R China Lakehead Univ Dept Elect Engn Thunder Bay ON P7B 5E1 Canada

This article investigates an adaptive practical fixed-time control strategy for the output tracking control of a class of strict feedback nonlinear systems. By utilizing a backstepping algorithm, finite-time Lyapunov stable theory, and fuzzy logic control, a novel adaptive practical fixed-time controller is constructed. Fuzzy logic systems are introduced to approximate the unknown items of the system. Theoretical analysis proves that under the presented control strategy, the closed-loop system is practically fixed-time stable, and the tracking error converges to a small neighborhood of the origin within a fixed-time interval, in which the convergence time has no connection with the initial states of the system. In the meantime, all the signals of the closed-loop system are bounded. Finally, a numerical example is presented to indicate the feasibility and effectiveness of the proposed method.

关键词： Convergence backstepping Fuzzy logic Adaptive systems Nonlinear systems Closed loop systems Lyapunov methods Adaptive control backstepping algorithm fuzzy logic control practical fixed-time control

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Robust adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems with unknown control directions

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2021年第14期43卷 3103-3119页

作者： Doudou, Sofiane Khaber, Farid Univ Jijel Dept Automat Jijel Algeria Univ Setif 1 QUERE Lab Setif 19000 Algeria

In this paper, the adaptive fuzzy backstepping control problem is considered for a class of single-input single-output (SISO) unknown uncertain nonaffine nonlinear systems in strict-feedback form. Within this approach, Nussbaum gain functions are introduced to solve the problem of unknown control directions. The unknown nonlinear functions are approximated by employing adaptive fuzzy systems. The stability analysis of the closed-loop system in the sense of Lyapunov guarantees the global boundedness property for all the signals and states, and at the same time, steers the tracking error to a small neighborhood of the origin. The feasibility of the developed control approach is illustrated by numerical simulation.

关键词： backstepping algorithm adaptive control fuzzy systems strict feedback nonaffine nonlinear systems unknown control directions

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Adaptive neural network asymptotic tracking control for nonstrict feedback stochastic nonlinear systems

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NEURAL NETWORKS 2021年 143卷 283-290页

作者： Liu, Yongchao Zhu, Qidan Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China Harbin Engn Univ Key Lab Intelligent Technol & Applicat Marine Equ Minist Educ Harbin 150001 Peoples R China

The adaptive neural network asymptotic tracking control issue of nonstrict feedback stochastic nonlinear systems is studied in our article by adopting backstepping algorithm. Compared with the existing research, the hypothesis about unknown virtual control coefficients (UVCC) is overcome in the control design. By using the bound estimation scheme and some smooth functions, associating with approximation-based neural network, the asymptotic tracking controller is recursively constructed. With the aid of Lyapunov function and beneficial inequalities, the asymptotic convergence character and stability with stochastic disturbance and unknown UVCC can be ensured. Finally, the theoretical finding is verified via a simulation example. (C) 2021 Published by Elsevier Ltd.

关键词： Asymptotic tracking control backstepping algorithm Neural network Stochastic nonlinear systems

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