Adaptive Smith Predictor for Teleoperation of UAVs using Parameter Estimation Techniques

Teng, Tianhang; Grant, Peter R.

doi:10.2514/6.2019-1077

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…Disturbances like strong winds, low-adherence roads, and bumps can alter vehicle dynamics. Parameter estimation techniques presented in articles [48], [49] can be useful for changes in dynamics that last from medium to high duration. These techniques use sliding window batch estimation, the estimations itself are delayed (due to convergence time).…”

Section: Srpt Teleoperation Approach With Reference-pose Decider Driv...mentioning

confidence: 99%

Performance of Successive Reference Pose Tracking vs Smith Predictor Approach for Direct Vehicle Teleoperation Under Variable Network Delays

Prakash,

Vignati,

Sabbioni

2024

IEEE Trans. Veh. Technol.

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Section: Srpt Teleoperation Approach With Reference-pose Decider Driv...mentioning

confidence: 99%

Performance of Successive Reference Pose Tracking vs Smith Predictor Approach for Direct Vehicle Teleoperation Under Variable Network Delays

Prakash,

Vignati,

Sabbioni

2024

IEEE Trans. Veh. Technol.

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“…However, disturbances like strong winds, low-adherence roads, and bumps can alter vehicle dynamics. Parameter estimation techniques presented in articles [41], [42] can be useful for changes in dynamics that last from medium to high duration. These techniques use sliding window batch estimation, which means that estimations have a lead time.…”

Section: Srpt Teleoperation Approach With Reference-pose Decider Driv...mentioning

confidence: 99%

Vehicle Teleoperation: Human in the Loop Performance Comparison of Smith Predictor with Novel Successive Reference-Pose Tracking Approach

Prakash

Vignati

Sabbioni

et al. 2022

Sensors

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Vehicle teleoperation has the ability to bridge the gap between completely automated driving and manual driving by remotely monitoring and operating autonomous vehicles when their automation fails. Among many challenges related to vehicle teleoperation, the considered ones in this work are variable time delay, saturation of actuators installed in vehicle, and environmental disturbance, which together limit the teleoperation performance. State-of-the-art predictive techniques estimate vehicle states to compensate for the delays, but the predictive states do not account for sudden disturbances that the vehicle observes, which makes the human-picked steer inadequate. This inadequacy of steer deteriorates the path-tracking performance of vehicle teleoperation. In the proposed successive reference-pose-tracking (SRPT) approach, instead of transmitting steering commands, the reference trajectory, in the form of successive reference poses, is transmitted to the vehicle. This paper introduces a method of generation of successive reference poses with a joystick steering wheel and compares the human-in-loop path-tracking performance of the Smith predictor and SRPT approach. Human-in-loop experiments (with 18 different drivers) are conducted using a simulation environment that consists of the integration of a real-time 14-DOF Simulink vehicle model and Unity game engine in the presence of bidirectional variable delays. Scenarios for performance comparison are low adhesion ground, strong lateral wind, tight corners, and sudden obstacle avoidance. Result shows significant improvement in reference tracking and in reducing human effort in all scenarios using the SRPT approach.

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“…However, this method is too ideal to improve the UAV flight quality in the presence of disturbance and time-varying delay. Teng and Grant [20] improved this algorithm and, based on a low speed UAV linear longitudinal model, adapted the predictor model for real-time using online parameter estimation techniques; then they designed a constant time delay Smith predictor. However, the time delay is always a time-varying system in the WSN.…”

Section: Introductionmentioning

confidence: 99%

“…There have been many researches on time delay prediction, including deterministic objects, objects with parameter uncertainties, fixed delay time and random delay time systems. However, all of these studies [19][20][21][22] can be classified as networked control problems of low dynamic objects. That is to say, the operator sends the control command directly to the remote actuator of the passive object through the WSN.…”

Section: Introductionmentioning

confidence: 99%

Universal Adaptive Neural Network Predictive Algorithm for Remotely Piloted Unmanned Combat Aerial Vehicle in Wireless Sensor Network

Fang

Fan

et al. 2020

Sensors

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Remotely piloted unmanned combat aerial vehicle (UCAV) will be a prospective mode of air fight in the future, which can remove the physical restraint of the pilot, maximize the performance of the fighter and effectively reduce casualties. However, it has two difficulties in this mode: (1) There is greater time delay in the network of pilot-wireless sensor-UCAV, which can degrade the piloting performance. (2) Designing of a universal predictive method is very important to pilot different UCAVs remotely, even if the model of the control augmentation system of the UCAV is totally unknown. Considering these two issues, this paper proposes a novel universal modeling method, and establishes a universal nonlinear uncertain model which uses the pilot’s remotely piloted command as input and the states of the UCAV with a control augmentation system as output. To deal with the nonlinear uncertainty of the model, a neural network observer is proposed to identify the nonlinear dynamics model online. Meanwhile, to guarantee the stability of the overall observer system, an adaptive law is designed to adjust the neural network weights. To solve the greater transmission time delay existing in the pilot-wireless sensor-UCAV closed-loop system, a time-varying delay state predictor is designed based on the identified nonlinear dynamics model to predict the time delay states. Moreover, the overall observer-predictor system is proved to be uniformly ultimately bounded (UUB). Finally, two simulations verify the effectiveness and universality of the proposed method. The results indicate that the proposed method has desirable performance of accurately compensating the time delay and has universality of remotely piloting two different UCAVs.

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Adaptive Smith Predictor for Teleoperation of UAVs using Parameter Estimation Techniques

Cited by 7 publications

References 28 publications

Performance of Successive Reference Pose Tracking vs Smith Predictor Approach for Direct Vehicle Teleoperation Under Variable Network Delays

Performance of Successive Reference Pose Tracking vs Smith Predictor Approach for Direct Vehicle Teleoperation Under Variable Network Delays

Vehicle Teleoperation: Human in the Loop Performance Comparison of Smith Predictor with Novel Successive Reference-Pose Tracking Approach

Universal Adaptive Neural Network Predictive Algorithm for Remotely Piloted Unmanned Combat Aerial Vehicle in Wireless Sensor Network

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