Adaptive fuzzy tracking for flexible-joint robots with random noises via command filter control

Sun, Wei; Diao, Shuzhen; Su, Shun‐Feng; Wu, Yuqiang

doi:10.1016/j.ins.2021.06.025

Cited by 25 publications

(6 citation statements)

References 38 publications

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“…Figures 2A, 3A, 4–9 are illustrations for the method proposed in this article. Figures 2B and 3B are simulation illustrations for the method proposed in Reference 41. From the simulation results, it can be seen that both schemes can achieve satisfactory convergence performance.…”

Section: Simulation Resultsmentioning

confidence: 96%

“…Tracking error for the single‐link robot. (A) Finite‐time frame in this article; (B) without finite‐time frame in Reference 41…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Trajectories of the link position

q

and the desired trajectory

{q}_d

. (A) Finite‐time frame in this article; (B) without finite‐time frame in Reference 41…”

Section: Simulation Resultsmentioning

confidence: 99%

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Adaptive finite‐time fault‐tolerant control for flexible‐joint robotic stochastic systems with input saturation and sensor fault

Wang

Liu

2022

Adaptive Control & Signal

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A new fault-tolerant approach to input saturation and sensor faults is presented for flexible-joint robotic stochastic nonlinear systems with finite-time convergence performance. More precisely, a new command filter is designed and embedded into the backstepping framework, which greatly reduces the amount of calculation. By using the estimation ability of fuzzy logic system and less adjustable parameters, the problems of sensor faults and unknown functions are solved, which facilitates the design of controllers. A smooth function and mean-value theorem are used to deal with the difficulty associated with system signals. A novel simpler controller is developed to ensure that the trajectory tracking error converges to a sufficiently small neighborhood around the origin within finite time, while there are random noises. Finally, the effectiveness of the presented scheme is verified by simulation results.

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Section: Simulation Resultsmentioning

confidence: 96%

“…Tracking error for the single‐link robot. (A) Finite‐time frame in this article; (B) without finite‐time frame in Reference 41…”

Section: Simulation Resultsmentioning

confidence: 99%

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Adaptive finite‐time fault‐tolerant control for flexible‐joint robotic stochastic systems with input saturation and sensor fault

Wang

Liu

2022

Adaptive Control & Signal

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“…They achieved system stability through a backstepping controller with a tangent-type constraints term. Sun et al [10] tackle the problem of controlling flexible joint robots subjected to random disturbances from the external environment. They proposed a finite-time adaptive fuzzy command filtered backstepping control approach.…”

Section: Introductionmentioning

confidence: 99%

“…(1) Unlike [5]- [10], this paper considers real practical problems the robot may encounter in various environments. Therefore, the control law developed in this paper has more substantial applicability compared with the previous methods.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neural Task Space Control for Robot Manipulators With Unknown and Closed Control Architecture Under Random Vibrations

2022

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Robot manipulators are now used in various domains and environments, where they can be subjected to random vibrations. Random vibrations mainly affect the torque control signal, and a torque controller is therefore required to be designed for stabilization purposes. However, for security or intellectual property protection reasons, most commercialized robots are manufactured with unknown and inaccessible torque controller interface such that the user can only design a position/velocity controller. This paper proposes an adaptive task-space velocity controller free from the inner controller's structure and exhibiting stochastic and deterministic disturbances rejection to deal with these issues. To deal with the unknown inner controller, the paper exploits the fact that most torque controllers use a velocity feedback term, and it considers the other terms as an unknown functions vector. To cope with random disturbances, it is demonstrated that the random excitation matrix can be linearly parameterized, and therefore, a direct adaptive method is constructed. Using radial basis function neural network (RBF NN), an indirect adaptive method is developed to cope with deterministic uncertainties. Through Lyapunov theory, the paper proves that all the closed-loop signals are bounded in probability. The effectiveness of the proposed approach is further demonstrated through simulation comparisons.INDEX TERMS Robot manipulators, Adaptive task-space control, Closed inner controller, Random vibrations, Neural networks.

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Command filtered backstepping‐based containment control for a class of multi‐agent systems with uncertainty

Jiang

Yang

Gao

et al. 2023

Intl J Robust & Nonlinear

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SummaryIn this paper, a novel containment control scheme is designed for multi‐agent systems with unknown parameters and unknown control coefficients. To achieve the containment control goal, containment reference signals are generated using a certain number of dynamic leaders. Then, the followers directly receiving the reference signals can track their generated reference signals, and the rest of the followers track a certain number of estimated signals generated by designed dynamic equations. Under the backstepping framework, uncertainties of a multi‐agent system are compensated for through the adaptive bound estimation method. Additionally, the command filtered technique is adopted to avoid the cumbersome steps of multiple derivative calculations, and to simplify the operations of the control scheme. Finally, the stability of the closed‐loop multi‐agent system is proved based on the Lyapunov theory. The advantage of the proposed scheme is that the containment reference signal and the position between followers can be adjusted arbitrarily by adjusting the relevant parameters. Through simulations, the effectiveness and superiority of the designed controller are verified.

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Adaptive fuzzy tracking for flexible-joint robots with random noises via command filter control

Cited by 25 publications

References 38 publications

Adaptive finite‐time fault‐tolerant control for flexible‐joint robotic stochastic systems with input saturation and sensor fault

Adaptive finite‐time fault‐tolerant control for flexible‐joint robotic stochastic systems with input saturation and sensor fault

Adaptive Neural Task Space Control for Robot Manipulators With Unknown and Closed Control Architecture Under Random Vibrations

Command filtered backstepping‐based containment control for a class of multi‐agent systems with uncertainty

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