Event-Triggered Model-Free Adaptive Control for Wheeled Mobile Robot With Time Delay and External Disturbance Based on Discrete-Time Extended State Observer

Huang, Jiahui; Chen, Hua; Shen, Chao

doi:10.1115/1.4063996

Cited by 4 publications

(1 citation statement)

References 32 publications

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“…Huang et al presented a strategy based on Differential Evolution and Sliding Mode Control for Full-Form Dynamic Linearization Model-Independent Adaptive Control (DESO-based FFDL MFAC). They applied this solution to address trajectory tracking issues for wheeled mobile robots (WMR) with time delays and bounded disturbances, demonstrating its effectiveness through testing 16 . Li et al integrated fuzzy optimization with MFAC to govern the heading control of underwater vehicles, substantiating its efficacy through simulation and practical experiments 17 .…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Zhou,

Wang,

Jiang

et al. 2024

Preprint

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In the context of wind energy systems, maintaining optimal power output in wind turbines when wind speeds exceed rated values necessitates precise regulation of blade pitch through the pitch control system. However, challenges in accurately modeling nonlinear control systems and enhancing control responsiveness arise due to factors such as actuator constraints, unmodeled dynamics, and random wind speed fluctuations. This paper proposes an improved model-free control, termed Input-Output Model-Free Adaptive Control (IO-MFAC). It enhances the system's adaptability to stochastic wind and improves tracking capabilities by adaptively adjusting the input difference based on the output difference through the new cost function. Moreover, to demonstrate the stability of IO-MFAC, its monotonic convergence is theoretically confirmed. Simulations conducted on the FAST simulator and hardware-in-the-loop experiments demonstrate that IO-MFAC outperforms basic MFAC under constant wind and turbulent conditions, exhibiting superior dynamic tracking performance, control effectiveness, and practical utility.

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Section: Introductionmentioning

confidence: 99%

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Zhou,

Wang,

Jiang

et al. 2024

Preprint

View full text Add to dashboard Cite

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Analyzing the LMS Weight Error Covariance Matrix: An Exact Expectation Approach

Igreja,

Lara,

Tarrataca

et al. 2024

Circuits Syst Signal Process

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Data-Driven Tracking Control of a Cushion Robot With Safe Autonomous Motion Considering Human-Machine Interaction Environment

Sun,

Shan,

Chang

et al. 2024

Journal of Dynamic Systems, Measurement, and Control

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This study proposes a data-driven safety controller with velocity constraints for a cushion robot. We constructed a mathematical description of the human-machine interaction environment by decomposing the generalized input force and coefficient matrix in the dynamic model. We established a new equivalent data model, which considered various human-machine interaction environments using a pseudo-Jacobian matrix. A stochastic configuration network (SCN) estimation method for variations in the human-machine interaction environment was proposed, with hidden layer nodes added at random. We designed a safe autonomous navigation path and proposed a data-driven control method that limited the actual velocity while stabilizing the tracking error system. In addition, the desired motion velocity of the robot was designed. This approach has the advantage of ensuring safety at a specified velocity. We also demonstrated and validated the effectiveness of the proposed data-driven algorithm using simulation-based comparative analysis and an experimental study.

show abstract

Event-Triggered Model-Free Adaptive Control for Wheeled Mobile Robot With Time Delay and External Disturbance Based on Discrete-Time Extended State Observer

Cited by 4 publications

References 32 publications

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Analyzing the LMS Weight Error Covariance Matrix: An Exact Expectation Approach

Data-Driven Tracking Control of a Cushion Robot With Safe Autonomous Motion Considering Human-Machine Interaction Environment

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