Fixed-Time Fuzzy Control of Uncertain Robots With Guaranteed Transient Performance

Zhu, Chi; Yang, Chenguang; Jiang, Yiming; Zhang, Hui

doi:10.1109/tfuzz.2022.3194373

Cited by 28 publications

(15 citation statements)

References 33 publications

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“…However, in complex environments, the dynamic models of robots are not exactly known due to parametric uncertainty and disturbances 13 . The presence of model uncertainty will not only degrade the control performance, but also lead to the inability to guarantee the safety of system 14,15 . It is a challenge to design a safety‐critical controller for robots in the presence of model uncertainty.…”

Section: Introductionmentioning

confidence: 99%

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Safety‐critical control for robotic systems with uncertain model via control barrier function

Zhang

Zhai

Xiong

et al. 2023

Intl J Robust & Nonlinear

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Usually, it is difficult to build accurate dynamic models for real robots, which makes safety-critical control a challenge. In this regard, this article proposes a double-level framework to design safety-critical controller for robotic systems with uncertain dynamics. The high level planner plans a safe trajectory for low level tracker based on the control barrier function (CBF). First, the high level planning is done independently of the dynamic model by quadratic programs subject to CBF constraint. Afterward, a novel method is proposed to learn the uncertainty of drift term and input gain in nonlinear affine-control system by a data-driven Gaussian process (GP) approach, in which the learning result of uncertainty in input gain is associated with CBF. Then, a Gaussian processes-based control barrier function (GP-CBF) is designed to guarantee the tracking safety with a lower bound on the probability for the low level tracker. Finally, the effectiveness of the proposed framework is verified by the numerical simulation of UR3 robot.

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Section: Introductionmentioning

confidence: 99%

“…13 The presence of model uncertainty will not only degrade the control performance, but also lead to the inability to guarantee the safety of system. 14,15 It is a challenge to design a safety-critical controller for robots in the presence of model uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Safety‐critical control for robotic systems with uncertain model via control barrier function

Zhang

Zhai

Xiong

et al. 2023

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…Following this idea, the finite-time prescribed performance control is studied for nonstrict feedback nonlinear systems with adaptive fuzzy control [31], [32], multivariable strict feedback nonlinear systems with neural network control [33], strict feedback nonlinear systems with disturbance observer-based control [34], and stochastic nonlinear systems with adaptive backstepping control [35]. On the other hand, based on exponential performance functions, finite-time adaptive fuzzy control with event-triggered mechanism for uncertain strict-feedback nonlinear systems [36] and multiagent systems [37] and a fixed-time version for uncertain robot systems [38] are established. Particularly, fuzzy logic systems [31] and dynamic surface control [32]- [34], [36], [37] are used to deal with the differential explosion problem, and thus complex calculations can be avoided.…”

Section: Introductionmentioning

confidence: 99%

“…(A1) To well define the error transformation function at the initial time, the initial value of the prescribed performance function depends on the initial value of the tracking error [11]- [14], [19]- [24], [26], [28], [29], [34]- [38], [43]. (A2) To suppress the influence of the error surface defined in dynamic surface control on the energy function, derivatives of virtual controllers are bounded or defined on a compact set [31], [34], [39].…”

Section: Introductionmentioning

confidence: 99%

“…(A3) The system states are be constrained in a compact set while using fuzzy logic systems or neural networks to approximate the unknown nonlinearities [11]- [13], [20], [21], [24], [25], [27], [30]- [38]. Therefore, in addition to avoiding high computational complexity including the differential explosion and Nussbaum-type functions, to guarantee global performance is also theoretically challenging.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Fuzzy Tracking Control with Global Prescribed-Time Prescribed Performance for Uncertain Strict-Feedback Nonlinear Systems

Mao¹,

Wu²,

Liu³

et al. 2022

Preprint

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Adaptive fuzzy control strategies are established to achieve global prescribed performance for uncertain strictfeedback nonlinear systems with prescribed time. Firstly, a class of prescribed-time prescribed performance function is designed to quantify the transient and steady performance constraints of the tracking error. Secondly, based on dynamic surface control methods, controllers with or without approximating structures are established to guarantee that the tracking error satisfies prescribed transient performance and converges into a prescribed bounded set within prescribed time. In particular, the settling time and initial value of the prescribed performance function are completely independent of initial conditions of the tracking error and system parameters, which improves existing results. Moreover, with a novel Lyapunov-like energy function, not only the differential explosion problem frequently occurring in backstepping techniques is solved, but the drawback of the semiglobal boundedness of tracking error induced by dynamic surface control can be overcome. The validity and effectiveness of the main results are verified by numerical simulations on practical examples.

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Nonsingular fixed‐time fault‐tolerant control for multiple Euler–Lagrange systems without continuous communication

Hua,

Yao,

Liu

et al. 2023

Intl J Robust & Nonlinear

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This article is concerned with the fixed‐time fault‐tolerant control problem of multiple Euler–Lagrange systems (MELSs) with intermittent communication, actuator faults and input disturbances. A nonsingular fixed‐time control framework with three parts is built for the above problem. In the first part, a novel adaptive controller is proposed for MELSs to ensure the fixed‐time stability of sliding modes while successfully solving the actuator faults, parameter uncertainties and unknown disturbances. In the second part, the fixed‐time estimators based on event‐triggered communication are designed by an error decomposition approach. In the third part, an auxiliary system is introduced for the singularity problem and sufficient condition for achieving the consensus is rigorously proved by synthesizing the results of the above two parts. The key feature of the proposed control framework is that the convergence time is constrained by a constant without involving initial states, and the singularity problems of fixed‐time control is avoided. Finally, simulation examples are provided to prove the efficacy of the proposed algorithms.

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Fixed-Time Fuzzy Control of Uncertain Robots With Guaranteed Transient Performance

Cited by 28 publications

References 33 publications

Safety‐critical control for robotic systems with uncertain model via control barrier function

Safety‐critical control for robotic systems with uncertain model via control barrier function

Adaptive Fuzzy Tracking Control with Global Prescribed-Time Prescribed Performance for Uncertain Strict-Feedback Nonlinear Systems

Nonsingular fixed‐time fault‐tolerant control for multiple Euler–Lagrange systems without continuous communication

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