Finite time parameter estimation-based adaptive predefined performance control for servo mechanisms

Wang, Shubo; Na, Jing; Yu, Haisheng; Chen, Qiang

doi:10.1016/j.isatra.2018.11.029

Cited by 17 publications

(12 citation statements)

References 41 publications

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“…where x d is the desired trajectory. According to (15), the funnel error can be defined as e time derivative of ( 20) is…”

Section: Controller Designmentioning

confidence: 99%

“…To address this problem, the conventional PID controller was designed for robotic manipulators, but PID cannot achieve the satisfactory control performance [9]. To improve the tracking performance of robotic manipulators, a variety of control strategies were proposed for robotic systems such as adaptive control [10,11], nonlinear control [12], and backstepping control [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Predefined Performance Neural Control for Robotic Manipulators with Unknown Dead Zone

Shao

Zhang

et al. 2020

Mathematical Problems in Engineering

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This paper proposes an adaptive predefined performance neural control scheme for robotic manipulators in the presence of nonlinear dead zone. A neural network (NN) is utilized to estimate the model uncertainties and unknown dynamics. An improved funnel function is designed to guarantee the transient behavior of the tracking error. The proposed funnel function can release the assumption on the conventional funnel control. Then, an adaptive predefined performance neural controller is proposed for robotic manipulators, while the tracking errors fall within a prescribed funnel boundary. The closed-loop system stability is proved via Lyapunov function. Finally, the numerical simulation results based on a 2-DOF robotic manipulator illustrate the control effect of the presented approach.

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“…where x d is the desired trajectory. According to (15), the funnel error can be defined as e time derivative of ( 20) is…”

Section: Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Predefined Performance Neural Control for Robotic Manipulators with Unknown Dead Zone

Shao

Zhang

et al. 2020

Mathematical Problems in Engineering

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show abstract

“…Using the finite-time stability theory can greatly shorten the working time of the system and reduce the energy consumption of the system. 4,[45][46][47][48][49][50] However, the arrival time varies with the initial value of the system. Compared with the finite-time control, the arrival time of the controlled system using the fixed-time scheme does not vary with the initial value of the system.…”

Section: Introductionmentioning

confidence: 99%

“…The existing control strategies are difficult to provide satisfactory performance since there are no such restrictions. Using the finite‐time stability theory can greatly shorten the working time of the system and reduce the energy consumption of the system 4,45‐50 . However, the arrival time varies with the initial value of the system.…”

Section: Introductionmentioning

confidence: 99%

Adaptive event‐triggered synchronization control for bilateral teleoperation system subjected to fixed‐time constraint

Zhao

Liu

Wang

2022

Adaptive Control & Signal

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Summary The time‐constrained positional synchronization control problem for a class of bilateral teleoperation systems is investigated and a novel fixed‐time event‐triggered control scheme is developed. Different from existing methods, the controller is triggered in a nonperiodic manner, which reduces considerably the triggering frequency of control devices. This not only saves communication resource, but also extends the lifespan of system devices because of the reduction of switching times. The control settling time is further considered by introducing a fixed‐time stability theorem. Theoretical analysis as well as a simulation example verifies that the proposed control method can reduce remarkably the amount of control signals transmitted between the master and slave while ensuring that the system output tracking error converges to a small neighborhood close to zero within a fixed‐time frame.

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“…However, if this reaching law based on hyperbolic functions is applied to the control system of the BL-IM, it will complicate the control system and reduce the real-time performance of the motor. To improve the transient and steady-state performance, a modified funnel variable, which relaxes the limitation of the original funnel control, is developed by using the tracking error to replace the scaling factor (Wang et al, 2019). Adding this method to the control system of the BL-IM can increase the control accuracy of the current component, but a tracking error applied to the closed-loop suspension current control will increase the calculation and decrease the response speed of the control system.…”

Section: Introductionmentioning

confidence: 99%

Predictive current control of a bearingless induction motor model based on fuzzy dynamic objective function

Yang

et al. 2020

Transactions of the Institute of Measurement and Control

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A control strategy for a bearingless induction motor (BL-IM) based on the fuzzy dynamic objective function is proposed in this paper. Firstly, based on the discrete mathematical model of the BL-IM, the stator current and flux linkage are predicted according to the given stator current and flux linkage, the objective function of model predictive current control (MPCC) is designed. Secondly, the fuzzy control algorithm is introduced in the objective function of the MPCC to dynamically assign the weighting factors before the current component on the d- q axis and the influence of the objective function on the performance of the BL-IM is analyzed under different weighting factors. By discretizing the rotational speed deviation Δ ω and rotational speed deviation rate, fuzzy reasoning is performed to obtain the optimal fuzzy dynamic function. Finally, the optimal fuzzy dynamic function is selected as the objective function of the MPCC to perform the simulations and experiments. The results show that the performance of the BL-IM under the MPCC strategy based on the fuzzy dynamic objective function is improved compared with the traditional MPCC and the vector control based on the fuzzy PID, due to its better dynamic and suspension performance. Meanwhile, the stability of rotor current component is enhanced.

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Finite time parameter estimation-based adaptive predefined performance control for servo mechanisms

Cited by 17 publications

References 41 publications

Adaptive Predefined Performance Neural Control for Robotic Manipulators with Unknown Dead Zone

Adaptive Predefined Performance Neural Control for Robotic Manipulators with Unknown Dead Zone

Adaptive event‐triggered synchronization control for bilateral teleoperation system subjected to fixed‐time constraint

Predictive current control of a bearingless induction motor model based on fuzzy dynamic objective function

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