Tracking Control for Wheeled Mobile Robot Based on Delayed Sensor Measurements

Guechi, El-Hadi; Belharet, Karim; Blažič, Sašo

doi:10.3390/s19235177

Cited by 6 publications

(2 citation statements)

References 37 publications

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“…Wang et al in [ 28 ] proposed a smooth controller with time-varying feedback parameters that solves the tracking and the stabilization tasks. Lastly, Guechi et al in [ 29 ] solved the trajectory tracking problem by designing a novel fuzzy predictor observer for dealing with the delay measurements and a parallel-distributed compensation control for the mechanical structure.…”

Section: Introductionmentioning

confidence: 99%

A Novel Dynamic Three-Level Tracking Controller for Mobile Robots Considering Actuators and Power Stage Subsystems: Experimental Assessment

García-Sánchez

Tavera-Mosqueda

Silva‐Ortigoza

et al. 2020

Sensors

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In order to solve the trajectory tracking task in a wheeled mobile robot (WMR), a dynamic three-level controller is presented in this paper. The controller considers the mechanical structure, actuators, and power stage subsystems. Such a controller is designed as follows: At the high level is a dynamic control for the WMR (differential drive type). At the medium level is a PI current control for the actuators (DC motors). Lastly, at the low level is a differential flatness-based control for the power stage (DC/DC Buck power converters). The feasibility, robustness, and performance in closed-loop of the proposed controller are validated on a DDWMR prototype through Matlab-Simulink, the real-time interface ControlDesk, and a DS1104 board. The obtained results are experimentally assessed with a hierarchical tracking controller, recently reported in literature, that was also designed on the basis of the mechanical structure, actuators, and power stage subsystems. Although both controllers are robust when parametric disturbances are taken into account, the dynamic three-level tracking controller presented in this paper is better than the hierarchical tracking controller reported in literature.

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Section: Introductionmentioning

confidence: 99%

A Novel Dynamic Three-Level Tracking Controller for Mobile Robots Considering Actuators and Power Stage Subsystems: Experimental Assessment

García-Sánchez

Tavera-Mosqueda

Silva‐Ortigoza

et al. 2020

Sensors

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show abstract

“…For this problem, many scholars have focused on the model uncertainty and nonlinear unmodeled dynamics. The intelligent algorithm using a fuzzy logic system and a neural network as an approximate estimator is widely studied [30][31][32]. For intelligent algorithms, some recent works can be found in [33][34][35].…”

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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Artificial Neural Network Design for Non Linear Takagi–Sugeno Systems: Application to Tracking of Trajectory, State and Fault Estimation of MIABOT Robot

Miri,

Guerfel,

Khedher

et al. 2023

Studies in Systems, Decision and Control

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Tracking Control for Wheeled Mobile Robot Based on Delayed Sensor Measurements

Cited by 6 publications

References 37 publications

A Novel Dynamic Three-Level Tracking Controller for Mobile Robots Considering Actuators and Power Stage Subsystems: Experimental Assessment

A Novel Dynamic Three-Level Tracking Controller for Mobile Robots Considering Actuators and Power Stage Subsystems: Experimental Assessment

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

Artificial Neural Network Design for Non Linear Takagi–Sugeno Systems: Application to Tracking of Trajectory, State and Fault Estimation of MIABOT Robot

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