State feedback based on grey wolf optimizer controller for two-wheeled self-balancing robot

Jasim, Wesam M.

doi:10.1515/jisys-2022-0035

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…Eq (6), ( 20), ( 23), (38) and ( 39) are substituted into Eq (37). The resultant equation can be represented as follows.…”

Section: Plos Onementioning

confidence: 99%

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Modelling and robust controller design for an underactuated self-balancing robot with uncertain parameter estimation

Choudhry,

Wasim,

Ali

et al. 2023

PLoS ONE

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A comprehensive literature review of self-balancing robot (SBR) provides an insight to the strengths and limitations of the available control techniques for different applications. Most of the researchers have not included the payload and its variations in their investigations. To address this problem comprehensively, it was realized that a rigorous mathematical model of the SBR will help to design an effective control for the targeted system. A robust control for a two-wheeled SBR with unknown payload parameters is considered in these investigations. Although, its mechanical design has the advantage of additional maneuverability, however, the robot’s stability is affected by changes in the rider’s mass and height, which affect the robot’s center of gravity (COG). Conventionally, variations in these parameters impact the performance of the controller that are designed with the assumption to operate under nominal values of the rider’s mass and height. The proposed solution includes an extended Kalman filter (EKF) based sliding mode controller (SMC) with an extensive mathematical model describing the dynamics of the robot itself and the payload. The rider’s mass and height are estimated using EKF and this information is used to improve the control of SBR. Significance of the proposed method is demonstrated by comparing simulation results with the conventional SMC under different scenarios as well as with other techniques in literature. The proposed method shows zero steady state error and no overshoot. Performance of the conventional SMC is improved with controller parameter estimation. Moreover, the stability issue in the reaching phase of the controller is also solved with the availability of parameter estimates. The proposed method is suitable for a wide range of indoor applications with no disturbance. This investigation provides a comprehensive comparison of available techniques to contextualize the proposed method within the scope of self-balancing robots for indoor applications.

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“…Eq (6), ( 20), ( 23), (38) and ( 39) are substituted into Eq (37). The resultant equation can be represented as follows.…”

Section: Plos Onementioning

confidence: 99%

“…Jasim has used grey wolf optimization-based State feedback controller for two-wheeled self-balancing robot. Neither he has considered payload in SBR nor external disturbances [ 37 ].…”

Section: Introductionmentioning

confidence: 99%

Modelling and robust controller design for an underactuated self-balancing robot with uncertain parameter estimation

Choudhry,

Wasim,

Ali

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

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Development of a gray box system identification model to estimate the parameters affecting traffic accidents

Zargari

Rad

2023

Nonlinear Engineering

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In this study, the gray box method has been used to model traffic accidents for the first time. This work examines the problem of estimating and identifying a single-input single-output state-space system. In this way, the state-space model was used, which has both a black box section (experimental data) and the parameters have been estimated by acquiring prior knowledge (white box). First, the state-space of the desired system is formed, and the algorithm for estimating the parameters and their convergence and the state vector estimation algorithm are written. In comparison, the system changes from nonlinear to linear. The parameters and prior knowledge are entered from the system. Finally, by implementing the presented method on the data related to the factors affecting accidents in Qazvin (Iran), the accuracy of the presented materials is investigated. The error output shows that initially, the error increased slightly, but then it shows a downward trend, and with the increase in the data, the error tends to zero (0.658). The results also show good fit and optimal accuracy of the model in less processing time.

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State feedback based on grey wolf optimizer controller for two-wheeled self-balancing robot

Cited by 2 publications

References 23 publications

Modelling and robust controller design for an underactuated self-balancing robot with uncertain parameter estimation

Modelling and robust controller design for an underactuated self-balancing robot with uncertain parameter estimation

Development of a gray box system identification model to estimate the parameters affecting traffic accidents

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