A prescribed-performance-based adaptive finite-time tracking control scheme circumventing the dependence on the system initial condition

Liu, Hui; Li, Xiaohua

doi:10.1016/j.amc.2023.127912

Cited by 6 publications

(1 citation statement)

References 39 publications

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“…For instance, Liu et al [33][34][35][36] introduced a finite-time performance function to construct a finite time prescribed performance control (FTPPC), which can make the tracking error converge to a smaller predetermined region in a finite time with a faster convergence rate and always stay within the region later. Besides that, Song et al [37][38][39] introduced a novel constraint processing technology to improve the PPC approach, which can relax the restriction on initial error. Nevertheless, the FTPPC scheme is relatively new and still has a large space for development.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered adaptive tracking control for nonlinear systems with input saturation and unknown control directions

Chang,

Hou,

Bai

et al. 2023

Intl J Robust & Nonlinear

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This article is concerned with event‐triggered adaptive tracking control design of strict‐feedback nonlinear systems, which are subject to input saturation and unknown control directions. In the design procedure, a smooth nonlinear function is employed to approximate the saturation function so that the controller can be designed under the framework of backstepping. The Nussbaum gain technique is employed to address the issue of the unknown control directions. A predetermined time convergent performance function and a nonlinear mapping technique are introduced to guarantee that the tracking error can converge in the predetermined time with a fast convergence rate and a high accuracy. Then the event‐triggered adaptive prescribed performance tracking control strategy is proposed, which not only ensures the boundedness of all the closed‐loop signals and the convergence of tracking error but also reduces the communication burden from the controller to the actuator. At last, the simulation study further tests the availability of the proposed control strategy.

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Section: Introductionmentioning

confidence: 99%

Event‐triggered adaptive tracking control for nonlinear systems with input saturation and unknown control directions

Chang,

Hou,

Bai

et al. 2023

Intl J Robust & Nonlinear

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Integral reinforcement learning‐based optimal tracking control for uncertain nonlinear systems under input constraint and specified performance constraints

Chang,

Liu,

et al. 2024

Intl J Robust & Nonlinear

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This article addresses the optimal tracking control problem with prescribed performance for uncertain nonlinear systems subject to input constraint and unknown disturbances. First, a fixed‐time monotonic convergence function is introduced to restrain tracking error, and a nonlinear mapping technique is employed to transform the constrained error into an unconstrained variable, then the fixed‐time output tracking issue is boiled down to the boundedness problem of the transformed variable. With the aid of a nonquadratic cost function, the input constraint is encoded into the optimization problem. To solve the unknown disturbances, an auxiliary system and an auxiliary disturbance policy are constructed, and the optimal control problem is formulated as a two‐player zero‐sum game. Moreover, a Hamilton–Jacobi–Isaacs (HJI) equation associated with this nonquadratic zero‐sum game is established to give the optimal control and the worst‐case disturbance policy solution. Subsequently, to avoid using knowledge of the system dynamics, three neural network approximators, namely, actor, critic, and disturbance, which are tuned online and simultaneously for approximating the solution of HJI, are constructed based on the integral reinforcement learning algorithm. Theoretical analysis shows that the reconstructed error system states and the weight estimation errors are semi‐globally uniformly ultimately bounded. Finally, the simulation study further tests the availability of the proposed control strategy.

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Self-modified flexible prescribed performance control for a class of strict feedback systems with input saturation and actuator faults

Wu,

Huang,

2024

Nonlinear Dyn

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A prescribed-performance-based adaptive finite-time tracking control scheme circumventing the dependence on the system initial condition

Cited by 6 publications

References 39 publications

Event‐triggered adaptive tracking control for nonlinear systems with input saturation and unknown control directions

Event‐triggered adaptive tracking control for nonlinear systems with input saturation and unknown control directions

Integral reinforcement learning‐based optimal tracking control for uncertain nonlinear systems under input constraint and specified performance constraints

Self-modified flexible prescribed performance control for a class of strict feedback systems with input saturation and actuator faults

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