Constrained Adaptive Robust Trajectory Tracking for WIP Vehicles Using Model Predictive Control and Extended State Observer

Yue, Ming; An, Cong; Li, Zhijun

doi:10.1109/tsmc.2016.2621181

Cited by 51 publications

(26 citation statements)

References 42 publications

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“…Assumption 1 has been well recognized in the literature and is indeed the same as those used in the DOBs and ESOs. 27,28,56,57 The assumption on the boundedness of the derivative of unknown nonlinearities F is needed in the proof of the convergence of the proposed UIO as shown in the next section and can be practically fulfilled in practice.…”

Section: Problem Formulationmentioning

confidence: 99%

Unknown input observer‐based robust adaptive funnel motion control for nonlinear servomechanisms

Wang

Ren

et al. 2018

Intl J Robust & Nonlinear

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Summary In this paper, an unknown input observer is proposed for servomechanisms with unknown dynamics (eg, nonlinear friction, parameter uncertainties, and external disturbance). An unknown input observer is developed by introducing auxiliary filtered variables in terms of first‐order low‐pass filters, where only one constant (filter parameter) needs to be tuned. A modified funnel variable is developed by using the tracking error to replace the scaling factor to improve the transient and steady‐state performance of the control systems. Then, a sliding mode surface with the new transformed error is defined and used to design a funnel nonsingular terminal sliding mode controller to achieve finite‐time convergence. In addition, the proposed funnel nonsingular terminal sliding mode controller method avoids the singularity problem in the conventional sliding mode control via modifying the terminal sliding manifold. Finally, experimental results are given to illustrate the effectiveness of the suggested control scheme.

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Section: Problem Formulationmentioning

confidence: 99%

Unknown input observer‐based robust adaptive funnel motion control for nonlinear servomechanisms

Wang

Ren

et al. 2018

Intl J Robust & Nonlinear

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“…To improve the anti-interference ability for the conventional MPC, a feasible solution is to take an adaptive MPC strategy, where the prediction model is updated online to cater for the divergence caused by the model mismatches. 16,17 In the work of Wang et al, 18 an adaptive MPC for direct-drive elevators is designed by updating the model via an extended state observer (ESO) and subsequently solving the optimal control problem based on the updated dynamics. In the work of Song, 19 an observer-based predictive vector-resonant current control strategy for permanent magnet synchronous machines is proposed, where an ESO is constructed in order to predict system behaviors and estimate the nonperiodic disturbances caused by parameter variations.…”

Section: Introductionmentioning

confidence: 99%

“…To improve the anti‐interference ability for the conventional MPC, a feasible solution is to take an adaptive MPC strategy, where the prediction model is updated online to cater for the divergence caused by the model mismatches 16,17 . In the work of Wang et al, 18 an adaptive MPC for direct‐drive elevators is designed by updating the model via an extended state observer (ESO) and subsequently solving the optimal control problem based on the updated dynamics.…”

Section: Introductionmentioning

confidence: 99%

Adaptive model predictive control with extended state observer for multi‐UAV formation flight

Zhang

Sun

Deng

2020

Adaptive Control & Signal

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This article studies the adaptive model predictive control with extended state observers (ESO) to deal with multiple unmanned aerial vehicles formation flight in presence of external disturbances and system uncertainties. Specifically, to deal with the mismatch of predictive model caused by external disturbances and system uncertainties, ESOs are introduced to estimate the lumped disturbances, where the ultimately bounded property of observer system can be guaranteed by using the Lyapunov stability theorem. With these observations, the distributed adaptive model predictive controller is designed to achieve trajectory tracking and disturbance rejection simultaneously for multiple unmanned aerial vehicles, as well as taking the state and input saturation into account. Moreover, the stability of proposed model predictive controller is analyzed. Finally, the simulation examples are provided to illustrate the validity of the proposed control scheme.

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“…To estimate uncertain perturbations, many new methods are proposed for observer design [19]- [22]. By reducing the sensitivity of the controller to uncertainty, [23]- [27] propose solutions from different perspectives.…”

Section: Introductionmentioning

confidence: 99%

Manipulator Trajectory Tracking of Fuzzy Control Based on Spatial Extended State Observer

et al. 2020

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This paper mainly studies the trajectory tracking control problem of the manipulator of TianGong-2 when capturing floating objects in the experimental cabin. Microgravity environment will lead to the existing control system of space robot can not produce good control effect. Different gravity environments change the design requirements of space robots, and the ground test cannot meet these space requirements. In this paper, a fuzzy control strategy based on a spatial extended state observer(FC-SESO) is proposed to solve these inconsistent problems. First, a spatial extended state observer is designed to estimate the influence of disturbance on the system. In order to estimate the disturbance quickly and accurately, a disturbance model including gust is established. Second, in order to ensure the rapid convergence of the desired trajectory, the fuzzy control law is derived. Based on Lyapunov stability theory, the stability of the control system based on the spatial extended state observer is proven. Finally, the proposed system is simulated and captured on the Tiangong-2 manipulator platform to verify the effectiveness of the control algorithm. INDEX TERMS Fuzzy control, microgravity, spatial extended state observer, trajectory tracking control.

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Constrained Adaptive Robust Trajectory Tracking for WIP Vehicles Using Model Predictive Control and Extended State Observer

Cited by 51 publications

References 42 publications

Unknown input observer‐based robust adaptive funnel motion control for nonlinear servomechanisms

Unknown input observer‐based robust adaptive funnel motion control for nonlinear servomechanisms

Adaptive model predictive control with extended state observer for multi‐UAV formation flight

Manipulator Trajectory Tracking of Fuzzy Control Based on Spatial Extended State Observer

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