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第40届中国控制会议

作者： You Wu Xue-Jun Xie Institute of Automation Qufu Normal University

This paper investigates adaptive fuzzy preassigned finite-time tracking control for high-order nonlinear systems with full-state constraints. Fuzzy systems are utilized to remove frequently-used growth assumptions on completely unknown nonlinearities. By integrating nonlinear transformed functions with a key coordinate transformation into control design, full-state constraints can be handled without imposing feasibility conditions in traditional barrier Lyapunov function-based methods. It is rigorously proved that the states of fuzzy systems remain within a specific compact set, on which fuzzy approximation is ***, asymmetric full-state constraints aren’t violated for all time, and the tracking error converges to the prescribed small region around zero in a preassigned finite-time. A simulation example shows the effectiveness of this control scheme.

关键词： High-order nonlinear systems full-state constraints adaptive fuzzy finite-time control feasibility conditions

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Performance Guaranteed Tracking Control for Nonlinear Systems With Time-Varying Output constraints and full-state constraints

Performance Guaranteed Tracking Control for Nonlinear System...

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第43届中国控制会议

作者： Xiaorui Wu Wenrui Li Yang Gao Chen Qian Yifei Wu Qingwei Chen School of Automation Nanjing University of Science and Technology

This paper proposes a low-complexity predefined performance tracking control scheme for a class of unknown nonlinear systems with time-varying output constraints and fullstate constraints. To address time-varying output constraints, a tubular adaptive boundary constraint function is designed to enable close adherence to predefined performance while meeting the constraints, without oscillations or overshoots. full-state constraints are handled by incorporating them into the performance function, ensuring compliance during tracking. Compensation terms in the controller relax assumptions on the system and enhance robustness against uncertainties. Stability analysis shows rapid convergence of the tracking error to a small region during stable periods, with bounded signals in the closed-loop *** results validate the effectiveness of the proposed control scheme.

关键词： Low-complexity Performance Guaranteed Uncertain Nonlinear Systems Output constraints full-state constraints

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Preassigned Finite-Time Control of High-Order Nonlinear Systems with Time-Varying Powers and full-state constraints

Preassigned Finite-Time Control of High-Order Nonlinear Syst...

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第40届中国控制会议

作者： Ruiming Xie Yungang Liu School of Control Science and Engineering Shandong University

This paper studies adaptive preassigned finite-time control of high-order nonlinear systems with unknown timevarying powers and full-state constraints. Neural network approximation is employed to remove frequently used assumptions imposed on unknown system nonlinearities. By introducing lower and higher powers, finite-time performance functions and nonlinear transformed functions into dynamic surface control design, full-state constrained controller is designed without imposing feasibility conditions on virtual controllers in traditional barrier Lyapunov function-based control methods. It is proved that all the closed-system signals are semi-globally bounded, full-state constraints are not violated, and system states converge to prescribed small regions around zero after a preassigned finite-time.

关键词： High-order nonlinear systems unknown time-varying powers full-state constraints adaptive neural networks preassigned finite-time control feasibility conditions

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full-state-Constrained Non-Certainty-Equivalent Adaptive Control for Satellite Swarm Subject to Input Fault

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 482-495页

作者： Zhiwei Hao Xiaokui Yue Haowei Wen Chuang Liu National Key Laboratory of Aerospace Flight Dynamics School of AstronauticsNorthwestern Polytechnical UniversityXi’an 710072China IEEE

Satellite swarm coordinated flight(SSCF)technology has promising applications,but its complex nature poses significant challenges for control *** response,this paper proposes an easily solvable adaptive control scheme to achieve high-performance trajectory tracking of the SSCF system subject to actuator efficiency losses and external *** existing adaptive controllers based on the certaintyequivalent(CE)principle show unpredictability and nonconvergence in their online parameter *** overcome the above vulnerabilities and the difficulties caused by input failures of SSCF,this paper proposes an adaptive estimator based on scaling immersion and invariance(I&I),which reduces the computational complexity while improving the performance of the parameter ***,a barrier Lyapunov function(BLF)is applied to satisfy both the boundedness of the system states and the singularity avoidance of the *** is proved that the estimator error becomes sufficiently small to converge to a specified attractive invariant manifold and the closed-loop SSCF system can obtain asymptotic stability under full-state ***,numerical simulations are performed for comparison and analysis to verify the effectiveness and superiority of the proposed method.

关键词： Dynamic scaling full-state constraints input faulttolerance non-CE adaptive control satellite swarm

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Adaptive state-feedback stabilization of state-constrained stochastic high-order nonlinear systems

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Science China(Information Sciences) 2021年第10期64卷 39-49页

作者： Rongheng CUI Xuejun XIE Institute of Automation Qufu Normal University

This paper presents an adaptive state-feedback strategy for state-constrained stochastic highorder nonlinear systems. By adding a power integrator and adaptive backstepping techniques, a new adaptive controller is constructed without imposing feasibility conditions, which guarantees that all closed-loop signals are bounded almost surely, full-state constraints are not violated almost surely, and the trivial solution of the closed-loop system is stochastically asymptotically stable.

关键词： stochastic high-order nonlinear systems full-state constraints feasibility conditions statefeedback stabilization adaptive control

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Removing Feasibility Conditions on Adaptive Fuzzy Control of state-Constrained High-Order Nonlinear Systems

Removing Feasibility Conditions on Adaptive Fuzzy Control of...

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第三十九届中国控制会议

作者： You Wu Xue-Jun Xie Institute of Automation Qufu Normal University

This paper investigates adaptive fuzzy control for full-state constrained high-order nonlinear systems. Fuzzy systems are employed to approximate unknown system nonlinearities. By integrating nonlinear transformed functions into control design,full-state constraints can be handled without imposing feasibility conditions on virtual controllers. It is rigorously proved that fuzzy approximation is valid on a crucial compact set, full-state constraints aren’t violated for all time, and the tracking error converges to a small compact set around zero. A simulation example shows the effectiveness of this control scheme.

关键词： High-order nonlinear systems full-state constraints adaptive fuzzy control feasibility conditions

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