Predefined performance adaptive control of robotic manipulators with dynamic uncertainties and input saturation constraints

Lyu, Weizhi; Zhai, Di‐Hua; Xiong, Yuhan; Xia, Yuanqing

doi:10.1016/j.jfranklin.2021.07.025

Cited by 21 publications

(15 citation statements)

References 46 publications

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“…Since the simplest adaptive neural network (NN) controller is used to handle the model uncertainties, the main differences of this article lie in the prescribed performance control strategy and the anti-saturation strategy in comparison with the existing works. Compared with the classical prescribed performance control with input saturation, the difference in computational complexity is that the proposed control designs two auxiliary dynamic systems, that is, the performance function dynamic system (7) and the anti-saturation compensator (26), where for all i = 1, 2, … , n, 𝜌 i (t) ∈ R 1 , 𝜃 ∈ R 1 . On the one hand, the dynamic performance function (7) is different from the classical design of continuous and monotonically decreasing exponential function, where n one-dimensional continuous dynamic systems are introduced into the control design for an n-DOF robotic system.…”

Section: Joint Velocity Controlmentioning

confidence: 99%

“…On the one hand, the dynamic performance function (7) is different from the classical design of continuous and monotonically decreasing exponential function, where n one-dimensional continuous dynamic systems are introduced into the control design for an n-DOF robotic system. On the other hand, a new adaptive factor 𝜃 is also introduced into the anti-saturation compensator (26), which is also a one-dimensional continuous dynamic system. To sum up, compared with the existing work, the proposed design needs to calculate additional n + 1 one-dimensional continuous dynamic system, as shown in (7) and (26).…”

Section: Joint Velocity Controlmentioning

confidence: 99%

“…On the other hand, a new adaptive factor 𝜃 is also introduced into the anti-saturation compensator (26), which is also a one-dimensional continuous dynamic system. To sum up, compared with the existing work, the proposed design needs to calculate additional n + 1 one-dimensional continuous dynamic system, as shown in (7) and (26).…”

Section: Joint Velocity Controlmentioning

confidence: 99%

“…Theorem 1. For the closed-loop robotic system composed of the robot dynamics (1), the desired control torque (25), the anti-saturation compensator (26), and the adaptive NN estimator (27), if the control gains satisfy…”

Section: Closed-loop Stability Analysismentioning

confidence: 99%

“…17,[20][21][22] Fruitful prescribed performance control methods have been developed for robotic system. 18,[23][24][25][26][27] In Reference 28, the origin and current research status of the prescribed performance control methodology are concluded. In Reference 29, a novel prescribed performance-based neural adaptive control scheme is developed for a class of robotic manipulators including motor dynamics under model uncertainties without velocity, acceleration, and input current measurements.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Initial configurations‐independent predefined performance control of robotic manipulator with input saturation

Zhai

Xia

2022

Intl J Robust & Nonlinear

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This article develops a guaranteed predefined performance control scheme for a class of robotic manipulators with input saturation and unknown uncertainties.The main advantage is that it can provide convenient and quantifiable predefined performance control, by integrating the  1 -class performance function in the prescribed performance control framework and designing an adaptive anti-saturation compensator. The maximum overshoot, the settling time, and the steady-state error can be specified independently and are not limited by the initial configurations of the robotic system, where the introduction of  1 -class performance function simplifies the control design. By introducing the adaptive neural network estimator and anti-saturation compensator, the proposed robust controller is also available in the presence of dynamic uncertainties, external disturbance, and actuator saturation. The proposed adaptive anti-saturation compensator can be easily incorporated into the guaranteed predefined performance control, which simplifies the stability analysis. Numerical results based on simulations demonstrate the effectiveness of the proposed method.

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Section: Joint Velocity Controlmentioning

confidence: 99%

Section: Joint Velocity Controlmentioning

confidence: 99%

Section: Joint Velocity Controlmentioning

confidence: 99%

Section: Closed-loop Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Initial configurations‐independent predefined performance control of robotic manipulator with input saturation

Zhai

Xia

2022

Intl J Robust & Nonlinear

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Adaptive fixed‐time minimal learning force/position control of uncertain manipulators subject to input saturation

Fang

et al. 2023

Adaptive Control & Signal

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This article solves the fixed-time force/position control problem for constrained manipulators in the presence of input saturation and uncertain dynamics. Under the fixed-time stability theory, a novel fixed-time auxiliary dynamic system (ADS) is first presented to compensate for the effects of input saturation nonlinearity. System uncertainties are estimated by using radial basis function neural networks (RBF NNs) and only need to tune one neural parameter online. In addition, with a fixed-time sliding mode surface and the proposed fixed-time ADS, a novel fixed-time adaptive neural force/position controller is designed which can not only ensure the fixed-time stability of the position tracking error but also enable the manipulator to track the desired force trajectory. By using the Lyapunov method, the boundedness of all signals in the closed-loop system is proved. Finally, the effectiveness of the proposed method is demonstrated by comparative simulation works.

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Command filter‐based adaptive control of flexible‐joint manipulator with input saturation and output constraints

Miao

Zhang

2023

Asian Journal of Control

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This paper focuses on the topic of adaptive neural tracking control for flexible‐joint manipulator systems with output restrictions and input saturation. With the aid of the error compensation mechanism, command filter‐based adaptive neural control is proposed for robotic systems driven by permanent magnet synchronous machine (PMSM). An auxiliary signal produced by the first‐order linear system designed by the property of unmodeled dynamics is used to erase the dynamical uncertainties. The input saturation of system is estimated by ‐function with mathematical transformation. Using barrier Lyapunov function (BLF), each component constraint of output is tackled. During the virtual control design phase, radial basis function neural networks (RBFNNs) may reliably assess the unknown nonlinear continuous function. All the variables in the closed‐loop system are proved to be semiglobally uniform ultimate bounded (SGUUB) by integrating all compensation signals into the overall Lyapunov function and using the defined compact set in the stability analysis of dynamic surface control (DSC). An applied example on robotic system is used to verify the effectiveness of the constructed design idea.

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Predefined performance adaptive control of robotic manipulators with dynamic uncertainties and input saturation constraints

Cited by 21 publications

References 46 publications

Initial configurations‐independent predefined performance control of robotic manipulator with input saturation

Initial configurations‐independent predefined performance control of robotic manipulator with input saturation

Adaptive fixed‐time minimal learning force/position control of uncertain manipulators subject to input saturation

Command filter‐based adaptive control of flexible‐joint manipulator with input saturation and output constraints

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